- Email: [email protected]
National Hospice Study analysis plan
J Chron Dis Vol. 36, No.
II.
pp. 737-780.
1983
0021.9681183 S3.oO+O.W
Printed in Great Britain. All rights reserved
NATIONAL
Copyright
HOSPICE
STUDY
ANALYSIS
c’ 1983 Pergamon Press Ltd
PLAN*
DAVID S. GREER’, VINCENT MoR’, SYLVIA SHERWOOD~,JOHN N. MORRIS~ and HOWARD
BIRNBAUM’
‘Principal Investigator, National Hospice Study; Dean of Medicine, Professor of Community Health, Brown University, *Assistant Professor, Section of Community Health, Brown University and Project Director of the National Hospice Study, 3Director, Department of Social Gerontological Research, Hebrew Rehabilitation Center for Aged, Boston; Clinical Professor (Research), Brown University, 4Associate Director, Department of Social Gerontological Research, Hebrew Rehabilitation Center for Aged, Boston and ‘Associate Director, Division of Health Studies Section, Abt Associates, Inc., Cambridge, MA; Clinical Assistant Professor (Research), Brown University, Providence, RI 02912, U.S.A. 10 October 1982)
(Receioed
Contents Section
I
David S. Greer, Vincent Mor, Sylvia Sherwood and Howard Birnbaum Se&on
of hospice
752
Methodology for determining the impact on patient/family quality of life
of hospice
758
Determining costs
763
Comparisons of the patients receive
765
Organizational
770
National
projections
the impact
of hospice
on health
care
intervention
terminal
cancer
VI
Vincent Mor, Bruce R. Foulke and Howard Birnbaum Section
for determining the impact and their families
V
Vincent Mor and David S. Greer Section
Methodology on patients
IV
Howard Birnbaum and David Kidder Section
747
and Overview
III
John N. Morris and Sylvia Sherwood Section
Introduction
II
Vincent Mor, Howard Birnbaum, John N. Morris, David S. Greer, and Sylvia Sherwood Section
738
and
facility
cost analyses
VII
Howard Birnbaum David Kidder
and
Appendix
A
776
Abridged program
description for eligible
Appendix
B
778
National
Hospice
*Supported in part by the National Hospice Study grants from the Robert Wood Johnson Foundation
of the hospice demonstration Medicare patients
Study
data
sources
funded by DHHS/HCFA Grant No. 99-P-97793/1-0 and the John A. Hartford Foundation. 737
and
DAVID S. GKEERet ul
738
Abstract-Since the founding of the first hospice in the United States in 1974, the number of health care organizations providing hospice services has grown rapidly. In 1978, the U.S. General Accounting Office identitied 59 operational hospices [l]. A survey undertaken by the National Hospice Organization (NHO) in 1980 found 235 operational programs and many more actively planning to deliver services. By the summer of 1981. the Joint Commission on the Accreditation of Hospitals (JCAH), in studying the feasibility of a voluntary hospice accreditation program, had 650 responses to a national survey [2]. Finally, the 1981 NH0 directory identifies 464 operational “provider programs” as well as 33 functioning state-level hospice organizations with an additional 353 programs in various stages of establishing hospice programs of care [3]. The growth of the movement and the public recognition it has received have catalyzed advocacy of Federal support for hospice services. In 1979, the Congress responded by mandating a study to delineate the implications of inclusion of hospice services in the Medicare program. The Health Care Financing Administration (HCFA) then selected 26 hospices (from an applicant pool of 233) to participate in a two-year expertmental program. These demonstration sites receive reimbursement for services provided Medicare beneficiaries not otherwise avatlable under current regulations. The special reimbursement provisions went into effect on October 1, 1980. (See Appendix A: Description of the Hospice Reimbursement Program.) In the spring of 1980, the Robert Wood Johnson Foundation and the John A. Hartford Foundation Joined with the Health Care Financing Administration (HCFA) to solicit proposals for a national evaluation of hospice care as a basis for future Federal fiscal policy and legislation. Brown University was selected as the evaluation center by competitive process and the grant was awarded on September 30. 1980. The evaluation employs a quasi-experrmental design in whtch the impact of hospice care (with and without reimbursement) on yuulir,, of I!fr and cos1.5 are compared to non-hospice (conventional) terminal care. Eight hundred patients and families in 24 comparison sites located in three regional areas (Southern New England, Northern Midwest and Southern California) are expected to participate. Primary data collection began on August I. 1981. Analyses of differential outcome are performed using standard linear multiple regression and logistic multiple regression with separate models for each comparison group. Effects are tested by separately estimating the specific response variable for the prototype (average) hospice patient for each model.
Section I-Introduction
and Overview
HOSPICE can be conceived of as a repertoire of services based on a humanistic philosophy of care for terminally ill patients and their families. The implementation of the hospice concept is highly diverse [ 1,471. This diversity is expressed in the institutional affiliations hospice programs have, the range of services provided directly or under contract and in the eligibility criteria utilized [7,4]. Despite this diversity, there are commonalities among the organizations that call themselves hospices. In this section, we briefly describe the hospice philosophy, its programmatic elements, and their conceptual relationship to the outcomes examined in this study. The National Hospice Organization’s 1979 “Standards of a Hospice Program of Care” [5] states the hospice philosophy:
“Hospice affirms life. Hospice exists to provide support and care for persons in the last phases of incurable disease so that they might live as fully and comfortably as possible. Hospice recognizes dytng as a normal process whether or not resulting from disease. Hosptce neither hastens nor postpones death. Hospice exists in the hope and belief that. through appropriate care and the premonition of a caring community sensitive to their needs, patients and families may be free to attain a degree of mental and spiritual preparation for death that is satisfactory to them.”
The hospice
philosophy
includes
the following:
(1) Patient and family know of the terminal condition. (2) Further medical treatment and intervention are indicated only on a supportive basis. (3) Pain control should be available to patients as needed to prevent rather than ameliorate pain. (4) Interdisciplinary teamwork is essential in caring for patient and family. (5) Family members and friends should be active in providing support during the death and bereavement process. (6) Trained volunteers should provide additional support as needed.
National
The following
provisions
Hospice
Study
are characteristic
Analysis
739
Plan
of hospice
programs:
(a) Health care and services are provided to terminally ill. (b) The patient,,famil_y, and other persons essential to the patient’s care comprise the unit of care. The “hospice patient ‘s,family ” refers to the patient’s immediate relatives; individuals with signt$cant personal ties may be designated as the patient’s “family” by mutual agreement among the patient, the individual, and the hospice organization. (c) Inpatient and home care services are closely integrated to ensure continuity and coordination of care. (d) Care is available 7 days a week, 24 hours a day. (e) Care is planned and provided by a medically supervised interdisciplinary team composed of several individuals with appropriate skills. The team members work together to plan and provide services that will secure the physical, emotional and spiritual welfare of the patient and his/her family. (f) Palliative and supportive cure is directed at allaying the physical and emotional discomfort associated with terminal illness. (g) Bereavement services are provided which may include follow-up visits and supports of the family after the patient dies. (h) An education program is available which has two components: (i) Educating dying. (ii) Teaching (i) Volunteers
the patient, the family
family
and inter-disciplinary
to care for the patient
play an important
team concerning
death
and
in the home.
role in the provision
of care (NHO,
1979).
Implementation of this philosophy by hospices should result in a substantial alteration in the pattern of health care provided to the terminally ill and their families. Changes in the pattern of care which should emerge as a function of the hospice program may be categorized as follows: Locus of cure: in the patient’s home and/or designated hospice beds rather than in hospital and/or nursing homes. Providers of Care: family and/or volunteers rather than health care professionals. Orientation of cure: palliative, preventive, supportive and less resource-intensive than conventional care. These changes in process should improve outcome in both patients if hospice care is superior to conventional care. Postulated changes quality of care are depicted in Fig. 1. The major research questions derived from this conceptual framework. CHANGES
CHANGES
IN PROCESS
and their families in both costs and of this Study are
IN OUTCOME
OF CARE
cost
Quality
LOCUS
of care
4
,.I", K rlu~~~r-basedcare
Providers
HOSPICE PROGRAM
of care
Substitutes home care for hospital-
I I I
__)1
More "informal", volunteer help and support
1 1 ,
\
I
ization
Substitutes nonpaid family and friends for professional and hospital personnel
I ’ 1 I I ( 1
Patient remains in familiar atmosphere with family with social contact and less anxiety and fear
more
Patients cared for by family with more intimacy will be more satisfied with care
’
t Orientation
of care
-
More preventive, palliative, non-curative care
FIG. I. Causal
model
of Hospice
1
Substitutes
less
costly palliative for more costly aggressive care
Intervention
System
’ I ,
With
preventive and palliative patients' pain and other symptoms will be better controlled
care,
I
and its effect on patient
outcome.
DAVID S. GREER rt ul
740
RESEARCH
The major
research
questions
QUESTIONS
pertaining
to the Study
are:
(1) What is the differential impact of hospice, demonstration or non-demonstration, on the quality of life of terminal patients and their families, as compared to “conventional” or “customary” care? (2) What are the differential costs of caring for comparable terminally ill patients in demonstration hospices, non-demonstration hospices and customary care settings? (3) What are the differences in the services which hospice and non-hospice patients receive? (4) What is the likely impact of Medicare reimbursement on the organizational structure, staffing pattern and costs of hospices? (5) What are the likely national cost implications of reimbursed hospice care? OVERVIEW
OF
THE
STUDY
COMPONENTS
The Study consists of several separate but related analyses corresponding to the five major research questions. The specific research questions being examined in each Study component are described below. IMPACT
These analyses
ON
address
PATIENT/FAMILY
the following
QUALITY
OF
LIFE
questions:
(1) What is the impact of hospice, under reimbursed and non-reimbursed conditions, on the quality of life of patients and their satisfaction with the care they receive? (2) What is the impact of hospice, under reimbursed and non-reimbursed conditions, on the satisfaction with care of patients’ families and the prevalence of family problems and grief before and after the patient’s death? (3) What is the impact of hospice organizational structure on the outcomes experienced by patients and families served? Quality of life is a multi-dimensional construct which is conceptualized as a positive mood state, the absence of physical and psychological distress, and positive interpersonal relations. Based on these concepts, a series of measurable domains of patient quality of life pertinent to terminal cancer patients has been identified. These are: -Pain and other symptoms. -Functional status and mobility. -Quality of social interactions. -Satisfaction with life. -Sense of isolation and burden on others. -Satisfaction with care received. With respect to the family, hospice can mitigate grief reaction and decrease social and physical morbidity through the provision of training, education and counseling while the patient is alive and subsequently through bereavement, assessment, and counseling. If families have been educated and supported, the psychological trauma associated with death may be reduced. From this perspective, the outcome areas being assessed are: -Indicators of family secondary morbidity (psycho-social functional symptoms). -Family satisfaction with care received. -Subjectively reported grief reaction (see Section III). IMPACT
These analyses
ON
FAMILY/PATIENT
address
(1) What is the impact non-reimbursed conditions
the following
COSTS
research
OF
distress,
TERMINAL
role loss, and
dys-
ILLNESS
questions:
of the hospice service and care model under reimbursed on the cost of caring for terminally ill patients?
and
National
Hospice
Study
Analysis
Plan
741
(2) What is the impact of the hospice service and care model under reimbursed and non-reimbursed conditions on the sources of payment for services used by patients during the terminal phase of their illness? (3) What is the impact of the hospice service and care model under reimbursed and non-reimbursed conditions on the level of informal support provided terminally ill patients? The patient/family economic analyses address costs, or resource commitments, for treating hospice and non-hospice cancer patients separately from examining the burden of paying for care as shared among payors. The cost analysis
includes:
“Costs” of those services for which standard techniques of computing cost exist are compared for hospice and non-hospice patients. These techniques will be applied to inpatient hospital stays, outpatient visits, nursing home stays, and home care visits. Charges for services for which standard costing techniques are not available are compared separately. These include physicians’ services, drugs, supplies and other expenses. Hours of informal support provided hospice and non-hospice patients are compared without imputing monetary costs to such donated services. The payor burden analysis is based upon billed or billable charges. The percentage of billed and “billable” charges paid by the patient, by Medicare, and by other third-party payors is compared for demonstration and non-demonstration hospice patients as well as conventional care patients (see Section IV).
DOCUMENTING
THE INTERVENTION PATIENTS RECEIVE
WHICH
TERMINAL
This component of the patient/family level study examines differences in the service interventions to which hospice and non-hospice patients are exposed during their final months of life. The analysis addresses the following questions: (1) What is the impact of hospice on the mix of health-related and psycho-social services received by terminally ill patients? (2) What is the impact of hospice on the level of analgesics and tranquilizing prescribed for and consumed by terminally ill patients?
support agents
The likelihood of receiving an array of psycho-social support services, medical treatments and diagnostic procedures is compared across hospice and non-hospice patients. Given the saliency of pain control to the hospice concept, the level of prescribed and consumed analgesic and tranquilizer medications in the last weeks of life is specifically compared in the two groups (see Section V). ORGANIZATIONAL
AND
FACILITY
COST
ANALYSIS
The impact of reimbursement on hospices as organizations is examined by comparing demonstration and non-demonstration hospices on such variables as staff mix, volume of patients served, length of stay, the unit cost of services provided, allocation of staff time, and administrative procedures (see Section VI). The analyses address the following research questions: (1) What is the impact of reimbursing hospices on the unit cost of hospice services? (2) What is the impact of reimbursing hospices on the staffing pattern and service mix of hospices? (3) What is the impact of reimbursing hospices on the mix of patients served and their length of stay? (4) What changes in hospice organizational structure and service goals are associated with reimbursement?
142
DAVID S. GREER et
National
al.
cost estimates
National estimates of the net financial cost or savings associated with hospice care will be developed; i.e. the cost of hospice care minus the cost of the alternative conventional care which would be provided in lieu of hospice care. Two types of national estimates are anticipated: (1) baseline national estimates; and (2) policy alternative national estimates. The baseline national estimates involve extrapolation of the net cost of hospice care from the sites under study to the nation. The policy alternative estimates could be developed for the nation under a range of reimbursement policies for which the evaluation has empirical information. -Medicare coverage of hospice care (relatively complete coverage as under the demonstration vs existing coverage under current Medicare programs); -Different organizational modes of hospice care receiving third-party reimbursement (e.g. hospital-based, home health agency and freestanding); -Various types and amounts of services receiving third-party reimbursement; and -Variable allowable enrollment time for hospice care; i.e. how long a patient is expected to live. Both the baseline and policy alternative estimates could address the current time period since future patient and provider behavior and market-place patterns are likely to change. In developing these estimates, the Study could consider: (1) net total national health care costs; (2) net Medicare programmatic costs; and (3) the net cost to other third parties, including both out-of-pocket, patient/family costs, and costs to private third-party payors (see Section VII). Study sites Hospices can be classified into three types: (a) Hospital-based; (b) Home health agency-based; (c) Freestanding. Hospital-based hospices have inpatient facilities by definition; these may be sequestered and/or specifically designated or may merely be available within the hospital as needed. Freestanding hospices may or may not have an inpatient facility. Home health agencybased hospices are affiliated with existing home care agencies. Demonstration
hospices
In selecting the 26 demonstration HCFA used the following criteria: (a) (b) (c) (d) (e)
sites from
among
the 233 applicant
organizations,
Comprehensiveness of the hospice intervention. Soundness and thoroughness of the service plan in the proposal. Operational at time of review. Sufficient distribution of major hospice types. Representation in each of the DHHS Federal regions.
Proposals were submitted in September of 1979 and successful applicants were notified of award within three months. The hospices are located in 16 different states. Eleven are hospital-based; 7 are home health agency-based and 8 are freestanding. Two of the freestanding hospices have inpatient facilities. Non -demonstration
hospices
The non-demonstration used for selection were:
hospices
were selected by the project
(a) Representative of major hospice types. (b) Reasonable proximity to the project’s regional
investigators.
management
centers.
The criteria
Hospice
National
(c) Similarity (d) Adequate
to demonstration hospices. admissions rate and patient
Eight of the non-demonstration agency-based and 4 are freestanding, noted that 11 of the 26 demonstration “Customary”
Study
Analysis Plan
743
census.
hospices are hospital-based; 2 are home health none of which has inpatient facilities. It should be hospices are located in the same regions.
cure
“Customary” or “conventional” of provider as follows:
care can be classified
(a) University medical center care, supervised (b) Community-based oncological care.
by site of delivery
by academic
oncologists;
and/or
type
and
care usually involves multiple programs and sites and, often, several “Customary” physicians. In most areas of the country, terminal cancer care is directed by oncologists, either as attending physicians or consultants. Customary care sites were selected using the following criteria: (i) Appropriate representation of major categories (above). (ii) Ease of access to patients (e.g. cancer registry or center). (iii) Conditions conducive to follow-up (e.g. integrated records). (iv) Willingness of key providers to participate. (v) Proximity to regional management centers. Patient
samples
There are three distinct, for use in the Study:
but overlapping,
patient
samples
for which data are gathered
-The census of all patients admitted to demonstration (D) or non-demonstration (ND) hospices during the months of ongoing data collection. -All Medicare patients served in D sites during the months of ongoing data collection. -Patient/family units from the D, ND and conventional care (CC) sites who consent to be part of an intensive data collection effort entailing regularfoffow-up visits by field staff and the tracking of medical care costs and utilization. This group is drawn from those patients with a biopsy-confirmed diagnosis of cancer. Table type and Table the two
1 summarizes the number of demonstration and non-demonstration hospices by the estimated number of patients in the census and detailed follow-up samples. 2 summarizes the number of patients in the follow-up sample to be drawn from classes of conventional care settings.
PATIENT Three patients
SAMPLE
strategies are employed to ensure that conventional are similar to patients sampled in hospices:
-Controlled patient selection procedures. -Ex post ,facto exclusion of non-comparable -Statistical control procedures. The first of these is discussed Patient
SELECTION
below.
patient
The others
care
follow-up
sample
types.
are described
in Section
II.
selection procedures
All patients
in the Study
must
have documented
(1) Cancer confirmed by tissue diagnosis. (2) Remote or extensive metastases, except suffices. CD3h:lI ”
evidence
for lung cancer
of:
where regional
metastasis
DAVID S. GREEK et
144
al.
TABLE I. ESTIMATEDSAMPLESIZESBY HOSPICETYPE
Demonstration
Hospice type Free standing
Hospitalbased
Home health agency
Bed status
Facilities (N)
hospices
Non-demonstration
Estimated no. of census
Patients in follow-up sample (N)
Facilities (N)
hospices
Estimated no. of census
Patients in follow-up sample (N)
None designated Designated beds
6
I500
550
4
220
50
2
700
150
0
0
0
Designated beds None designated
9
1000
400
6
800
I50
2
200
75
2
130
50
None designated
7
I800
500
2
415
50
26
5200
1675
I4
1565
300
Total
TABLE 2. CONVENTIONALCAKE SITES
(N)
Patients in follow-up sample (N)
4 8 I2
I50 250 400
Facilities University Medical Center Community-Based Oncological
Care Total
(3) Karnofsky functional/medical status score of 50 or less; i.e. in need of some personal care assistance (applies to conventional care patients only). (4) A principal care person (PCP). (All patients permanently residing in a long-term care facility are excluded.) (5) Age more than 2 1. An admission criterion for patients in most hospices is a physician’s determination that the patient is likely to live less than 6 months. However, the median length of stay is between 30 and 40 days and a fairly high proportion (some 40%) of hospice patients die within 3 weeks of admission. The criteria for selecting conventional care patients are based on the characteristics of hospice patients. A review of hospice patients’ functional status indicated that most patients have mobility limitiations or need for personal care assistance upon admission. The Karnofsky scale maximum of 50 for potential conventional care patients restricts that sample to patients who are at least as impaired as hospice patients and similarly at risk of “imminent death.” The presence of a principal care person (PCP) is a requirement of most hospices in the U.S.A. and a specific criterion for the HCFA demonstration. Persons under 21 are excluded from the follow-up sample. Age over or under 65 is a stratification variable which serves as a proxy for Medicare eligibility. Patient
sampling procedures
In demonstration and non-demonstration hospices, on-site data collectors independently trained and supervised by evaluation staff determine the eligibility of each patient admitted. Eligible patients and their PCP’s are asked to give written consent to participate in the Study by the data collector. If the number of eligible patients admitted exceeds the data collector’s case load capacity at any given time (approx. 10 patient/PCP units), the data collector uses a table of random numbers to select among cases and approaches those randomly selected.
National
Hospice
Study
Analysis
745
Plan
In conventional care sites, data collectors review lists of patients under the care of participating physicians or admitted to the oncology unit of a participating hospital with a designated on-site contact person (generally an oncology nurse clinician). Permission to contact Study-eligible patients is obtained from the physician, and then the patient and his/her PCP are approached, and written consent to participate in the Study is solicited. PATIENT/FAMILY
DATA SAMPLE
CONTACTS MEMBERS
FOR
FOLLOW-UP
Table 3 below lists the interviews and data forms used for the follow-up sample, grouped by type of information. Each of these is described in greater detail in Appendix B. At all sites, a trained field data collector has responsibility for contacting potential sample members and for gathering the requisite data both through personal interview and by abstracting information from available records. Figure 2 depicts the flow of a patient/family unit through the data process. The first follow-up contact occurs seven days after the initial interview and subsequently at 16day intervals. The number of contacts the data collector has with a patient/family unit varies with the length of life of the patient. At a minimum, the initial interview set and the final bereavement interview are obtained. Given a median length of life of 35 days, the median number of follow-up interviews is two. Most PCP’s have a follow-up interview while the patient is living as well as the final bereavement interview. The interview response burden per contact is limited: l/2 hr for the patient and up to 1 hr with the PCP during the initial contact, 15 min per patient follow-up, and 15 min with the PCP at each patient follow-up. At the bereavement interview, the data collector reconciles the service records gathered while the patient was living with bills received from providers to document health service utilization charges and to document out-of-pocket expenses. SUPPLEMENTAL
STUDIES AND DATA SOURCES
SECONDARY
The National Hospice Study compares the quality of life, health care utilization and cost experience of hospice patients and their families with those of similar patients and families not served by hospice. For valid comparison, similar individuals in the hospice and non-hospice groups must be sampled in the hospice and conventional care systems. A broader population-based approach is also desirable to complement the patient comparisons and to ascertain whether patients served by hospices are different from the larger population of terminal cancer patients. To address these issues and to place the findings TABLE 3.PATIENT-LEVEL DATA SOURCESUMMARY Content
Data
Demographic/background
Patient/family
quality
Cost and utilization
source
Patient intake form Medical record abstract of life
(form
name)
form
Initial principal care person (PCP) interview Follow-up PCP interview Bereavement interview Initial patient interview PCP assessment of patient Medication prescription and utilization record Patient follow-up interview Physician telephone interview Health insurance assessment Weekly service record Cost summary abstracts Hospital Outpatient clinic Nursing home Inpatient hospice Home health agency Physician Medicare bill history file
form
Activity
Time
Activity
Time
Activity
Time
Activity
Time
w
r
/\
FO1lOw-uP IntervIew
Patlent
obtain
v
referral to rJro.1ect
FIG. 2. Diagram
B
PCP Assessment -3f Patient ~-
14 days
1
consent
No.
of a patient/family
PCP Follow-up Tnterview
later
Day
Within 3 days wirtten informed
Day No. 0
unit‘s flow through
the data
90
3
Intake
later
PCP Assessment ofPatient_m Medlcatlon Utlllzatlon
7 days
gathering
- 100 days
system.
after
patlent
dies
Review of ierv~ce Record _____
Conduct telephone interview with primary physician
Variable time period
Repeated every 14 days until patlent dies
NW patients
Patient
days
Wlthin
National
Hospice
Study
Analysis
Plan
741
of the components of the National Hospice Study in context, a number activities are being undertaken. Each of these is described briefly. THE
COST
OF
TERMINAL
CANCER
IN
RHODE
of supplemental
ISLAND
The State of Rhode Island offers an ideal opportunity for a population-based comparison of the medical care costs incurred by hospices and non-hospice patients with terminal cancer. In this study, computerized death certificates from the Department of Health are matched with the bill history files of Blue Cross/Blue Shield of Rhode Island-the Medicare fiscal intermediary and health insurer of most of the remaining pobulation-for all deaths in 1980 and 1981 where cancer was a primary or related cause of death. All individuals served by the State’s only hospice during that period have been identified enabling a comparison of the health care costs of the two groups. Census tract designation facilitates comparisons of hospice and non-hospice groups on basic demographic, economic and health care access characteristics of the neighborhoods in which the individuals resided. These data will contribute to our understanding of differences in the characteristics of hospice and non-hospice patients as well as the patterns and costs of health care services they utilized in the last 6 months of their lives. A COMMUNITY
STUDY
OF
CANCER
CARE
Understanding the pattern of health care provided to a population of patients with terminal cancer under fairly “typical” community conditions is an important part of interpreting National Hospice Study results and of assessing the larger implications of policies reimbursing hospice services. A small, southeastern New England city served by two community hospitals and a small hospice organization was selected to undertake such an effort. The death certificates of all persons dying between August 1, 1981 and September 30, 1982 with a diagnosis of cancer are being matched with the cancer registries in both hospitals to characterize hospital service use in the last three months of life. Utilization of surgery, chemotherapy, radiation therapy, etc. in this period is compared for patients known to have been served by the local hospice and those who were not. Additionally, the demographic and family characteristics of the two groups will be compared, as will their prior cancer treatment as documented in the cancer registry. The remainder of this monograph presents the details of the five components of the National Hospice Study. Before describing these, however, Section II describes the analytic methodology used to test the major patient/family level cost and quality of life hypotheses including a specification of statistical power. Section III describes the quality of life analyses including the measures used. Section IV presents the methodology for measuring and comparing health care costs. Section V describes the methods used in comparing the service interventions received by hospice and non-hospice patients. Section VI describes the analytic strategy for comparing changes in demonstration and non-demonstration hospices. Finally, Section VII presents the framework for projecting Study findings to the nation based upon alternate policy options.
Section II-Methodology for Determining the Impact of Hospice on Patients and their Families The non-random selection of Study sites in conjunction with the structure of the Medicare demonstration project made using a classical clinical trial research design impossible. However, the rapidly growing and evolving hospice movement meant that a random sample of hospices drawn only two years ago would have been unrepresentative today. The patient selection procedures and analytic strategy for addressing the major research questions have been designed to adjust for possible pre-existing differences in the samples of hospice and non-hospice patient/family units whose outcomes are being compared.
748
DAVII) S. GKEEKet al.
The principal concern is that hospice and non-hospice patients are not drawn from the same population, by virtue of their choice to select one intervention. Nonetheless, it is anticipated that, in view of the Study eligibility criteria applied, there is considerable overlap in the groups being compared. The purpose of this section is to briefly describe the models and statistical methods used to compare the effects of alternative interventions on the outcomes experienced by terminal cancer patients. The models and procedures are stipulated in advance of our examination of the final data and are aimed at compensating, to the extent possible, for threats to the validity of the findings. These procedures are designed to adjust for differences in the comparison samples. Our further challenge concerns comparisons across Study sites and interventions. The number of hospices, both D and ND, and non-hospice Study sites is small, and they were selected purposively. They cannot, therefore, be viewed as representative of the different interventions. Rather, each facility can be seen as an instance, or “design point”, in the array of points that constitute the particular intervention type. To understand aspects of the interventions that influence its effect as observed on patient outcomes, meaningful characteristics of the Study sites can be introduced into the analytic model.
STRATEGIES
TO
ADJUST
FOR
SAMPLE
DIFFERENCES
Two techniques will be used, either independently or jointly, to adjust for possible differences in the characteristics of the samples exposed to the three interventions. One is based upon standard multiple regression techniques to specify and fit mathematical models that relate patient outcomes to patient and facility characteristics. Another employs multivariate procedures to identify and exclude sample numbers in order to ex post facto construct comparison samples comparably distributed on key patient characteristics. Each of these is described below followed by examples of the hypothesis-testing procedures and the resulting statistical power associated with these tests. Multiple
regression
The four main
steps of the analytical
strategy
are:
(1) the specification of mathematical models relating response variables to patient and facility characteristics; (2) fitting the specified models to the observed data and validating the models; (3) the performance of hypothesis tests, specified in advance of inspection of the data and the evaluation of confidence interval estimates to assess the differences in effects between alternative interventions; and (4) systematic use of fitted models to learn which differences in characteristics of patients or facilities are associated with differences in observed effects. The mathematical models are based upon multiple linear regression techniques in which independent variables (IV’s) describe characteristics of patients at Study intake, properties of the service pattern, and case mix of the Study site and the duration of patients’ exposure to the intervention. The models assume interactions between the type of intervention and the IV’s in the regression equations in terms of how they affect the response variable. Modeling a response variable Y that assesses cost of care or quality of life, the equations will be of the general form:
The subscripted X’s denote patient-level independent variables and the subscripted F’s denote facility-level independent variables. Two such equations will be used: one for all hospice patients, and one for all conventional care patients. Separate equations are required because we anticipate interactions between the intervention and other patient-level independent variables, and
National
because settings.
different
facility-level
Hospice
variables
Study
749
Plan
(the F’s) are pertinent
Hospice Y = B, + B, X, + B2XZ +
Analysis
and available
for the two
equation
. . + BpXp + C, H, + C2H2 +
Customary
+ Cq,,
+ eps.
care equation
Y = D, + D, X, + D,X, + . . + DpXp + E, G, + E2G2 + . . . + Erc, + eps. In these models, “eps” is the random “error” term. We assume that E (eps) = 0, that the variance of eps does not vary as a function of the IV’s in the separate equations (though the variance of eps in the hospice equation need not be the same as the variance of eps in the customary care equation) and that the error terms associated with separate patients in the samples are stochastically independent random variables. Some hypothesis tests and estimators used are predicated on the assumption that eps is normally distributed. The models are designed with these assumptions in mind. The IV’s are selected so that these assumptions will be legitimate and their validity will be tested when the models are fitted to the data. A different mathematical model complete with IV’s is used for each outcome measure. Based upon the expert judgement of professionals intimately familiar with the care of terminal cancer patients, independent variables that are conceptually related to the outcome measure are identified. The array of independent variables from which those included in the models will be chosen is large and range from standard demographic data to attitudinal information presumed to be related to choice of hospice. Listed below are the domains of independent variables and examples of specific measures. Patient
demographics
Age, sex, race, religion, Patient
marital
status.
medical and health status
Cancer Family
education,
type, co-morbid
medical
conditions,
functional
status,
nursing
care needs.
situation
Family size, patient relationship to patient, insurance coverage.
and PCP living family income,
arrangements, other support
PCP employment status, PCP obligations of PCP, patient’s
Prior service utilization Type of prior cancer therapy, with physician’s orders. Patientifamily
prior hospital
or institutional
service use, prior compliance
attitudes
Knowledge of diagnosis and prognosis, importance of religion, afterlife, characterization of the aggressiveness of patient’s treatment. Extrinsic
patient’s
belief
in
factors
These include characteristics of the adjacent catchment area (e.g. prevalence of hospital beds, home health services, skilled nursing homes), characteristics of the Study site, hospice or conventional care. Hospice facility IV’s are of two types: (a) those measuring an attribute of the hospice per se; and (b) those combining an attribute of the facility with a component that measures the patient’s exposure to the facility attribute. These latter IV’s are designed to measure the “dose” of the intervention received by the patient where dose is defined as time exposed to a given facility attribute. We assume a linear relationship between a patient outcome variable and the logarithm of the “dose” measure. Thus, the longer a patient is in hospice, the less the marginal effect upon the outcome measure of an additional day.
750
DAVID S. GKEER et u/.
An example outcome is: Volunteer
relating
exposure
a hospice’s
pattern
and volume
of volunteer
use to relevant
= log ([days the patient spent in home care x service hours provided at home per home care patient spent in the hospice inpatient unit x service hours provided inpatients per patient
patient
no. of volunteer day] + [days the no. of volunteer day]}
These variables assume that the intensity of the volunteer component of a hospice’s service intervention is related to the outcomes patients experience. Criteria for including these IV’s into the model are the same as for the patient-level IV’s, To the extent that relationships to patient outcome are observed, it is reasonable to interpolate findings to similar hospices not specifically included in the study. Validation of the model will rely upon graphical methods and objective computational tests. The graphical methods identify striking violations of model assumptions, and computational tests assess the significance of observed departures from the assumptions. Each graphical method (normal probability plots of residuals, residual plots against IV’s not in the model, and partial regression leverage plots to identify outlier observations) has a counterpart in an objective test [S]. In addition, standard goodness-of-fit tests for the models will be carried out provided the assumption of normality is supported [9]. Once these procedures have been applied and the linear models are accepted, hypotheses about the effects of the alternate interventions can be tested. If the linear models are not accepted, the diagnostic methods will guide our redesign of the models or selection of appropriate non-parametric methods Random
sample simulation
(SIMRAN
’ ) [lo]
An alternate approach to adjust for pre-existing differences among demonstration, non-demonstration and conventional care patients is to identify specific patients or groups of patients who are outliers by reviewing key independent and stratification variables. This is done by using a random sample simulation procedure which identifies the types of patients present in each Study sample and equalizes the proportions of these types across the samples. The procedure to be employed considers the comparison groups as pools of potential sample members. Briefly described, it selects the final comparison samples from the pools of demonstration, non-demonstration and conventional care follow-up patients. The first step in the process considers the total pool of subjects to be the sample universe. In 100 separate trials, the computer algorithm randomly allocates patients into comparison groups. For each set of random comparisons, baseline indices of the number of significant differences found between the different groups are computed on some 100 independent and dependent variables. Additionally, the average ‘I’ of each variable is calculated. The generation of modelled random samples and computation of significant differences and average q’ statistics is repeated until 100 simulated comparison samples are drawn and computations for at least 100 variables are completed. At that point, a frequency distribution of the number of significant differences and the average y ’ for each sample is computed. Percentile scores, ranking the simulated random samples from least to most comparable, form the criterion against which subsequent adjustments to the actual samples are compared. Starting with the patients in the conventional care pool, the computer algorithm selects comparison samples that pass the criterion established (i.e. being no “different” than one of the “better” random samples). Using random procedures, a series of iterations then attempts to select a sample from the larger pool of demonstration subjects which is comparable to the subjects in the smaller, conventional care pool. At each iteration, the number of significant differences between the groups and the size of the average ye’ on the criterion measures is calculated. A randomly selected demonstration sample will be considered acceptable if it is better than average of the simulated random samples. i.e. the comparison samples have fewer significant differences and a smaller average q’ than the
National
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Study
Analysis
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50th percentile established by the previous frequency distributions of “true” random draws. However, even if an acceptable demonstration sample is drawn, the algorithm continues to search (without reducing the sample sizes) until the “best” sample is identified (having the fewest differences and the smallest average q2). If no acceptable frequency-matched sample has been found, the third step is initiated. Demonstration hospice patients considered to be outliers are dropped. Later, subjects from either the non-demonstration or the conventional care groups who are extreme outliers are dropped. Following each adjustment, the procedure again tests the resulting samples against the criterion. Experience has shown that even with very dissimilar pools of potential subjects, comparable samples can be identified for impact evaluation purposes without unduly sacrificing the sample sizes. Given the procedures for selecting the subjects in this Study, it can be assumed that the overall pools will not be extremely dissimilar. In summary, the procedure identifies and selects impact comparison groups having similar distributions on a large array of patient characteristics at comparable points in their “death trajectory”. Based on several a priori criteria, the procedure tests each sample for equivalence along an array of relevant independent measures and selected dependent variables. Only when sample comparability has been demonstrated at the criterion level are the patient outcome hypotheses tested. STATISTICAL
POWER
OF
THE
HYPOTHESIS
TESTS
The major Study hypotheses concerning quality of life and costs will be tested separately for the overall sample and for patients over and under 65 yr of age (Medicare eligibility). In the case of the multiple regression approach, an approximate 9.5% confidence interval estimate for the expected value of the difference between the average response of hospice and non-hospice patients is given by: EY,
- EY,(f)2
x D,
where D = {Z;i(W;W,)-‘Z,MSEu Here,
“t” denotes
EY,
transpose
= B, + B,X, +
+ Z;(W;W,)-‘Z,MSE,}‘~2 and
+ BJ,
+ C,H, + . . . C,H,
EY,=D,,+D,X,+...+D,X,+E,G,+...E,G, Z:,=(l,X
,,...,
Xr,H ,,...,
H4)
Z:=[l,X
,I...,
X,,G
G,)
,,...,
W, = independent
variable
W, = independent
variable
MSE,
design
matrix
design matrix
for the hospice for the customary
= residual
mean
square
error
for hospice
MSE, = residual
mean
square
error
for customary
equation
equation
regression;
care equation
regression;
regression;
and care regression.
Using the SIMRAN’ approach, unadjusted one- or two-way analysis of variance techniques will be used to test Study hypotheses for the relevant response variables on the assumption that the samples are comparable. With either approach, the introduction of facility-level variables into the analyses will be limited to a small number. The statistical power of the hypothesis tests is a function of the variance in the outcome measure, the sample size, and a priori assumptions concerning the size of the differences between the groups which will be accepted as “true”. Preliminary examinations of the major patient-level cost and quality of life variables have made it possible to realistically specify the power of the hypothesis tests associated with these two outcomes.
752
S.
DAVID
TABLE 4. TEST
POWER
THE
TABLE
QUALITY
CONFIDENCE
et ul.
COK SAMPLE
OF
LEVEL
GKEEK
LIFE
(N
SIZE
NECESSAKY
HYPOTHESIS
= SMALLER
OF
AT
THE
To
95”,,
COMPARISON
SAMPLES)
Differences in samples expressed as a percentage of the mean ,I 0
Level of statistical (1 -ill
IO IS 20 30 40 SO
power
0.5
0.6
0.7
0.8
0.9
253 II2 63 28 16 IO
322 I43 X0 36 20 I3
404 I80 101 45 25 I6
512 228 128 57 32 21
683 304 I71 16 43 21
Table 4 presents the sample size necessary at various levels of statistical power (1 - /I) given varying accepted levels of true differences across samples for the principal quality of life outcome measure, the modified Spitzer Quality of Life Index. Estimates of the mean and standard deviation of the measure are based on preliminary examinations of the data. Sample sizes are predicated upon a 95% confidence limit, or at cz = 0.05. The differences between samples are expressed as percentages of the mean on the QLI scale which ranges from 0 to 10. A difference of at least 157; on this scale will be accepted as a true difference, A sample size of 304 conventional care patients will be required to assure that SOo/, of the time we will be correct in assuming a true difference actually exists. Table 5 presents comparable information for the principal patient cost measure--sum of inpatient and home care reimbursable service utilization multiplied by constant cost coefficients. In this case, a coefficient of variation (x,SD] of one (1) is assumed and levels of differences are expressed as percentage from the mean. Upon consideration of the different patterns of service utilization both hospice and non-hospice patients receive, a minimum of a 207< difference in the terminal care health costs associated with the two samples will be accepted as a true difference. At a desired power level of 0.8, a sample size of 404 patients in the conventional care group will be required. Based upon most recent sample size projections, the number of hospice and non-hospice patients necessary to reliably test the major Study hypotheses will be reached.
Section III-Methodology for Determining the Impact of Hospice on Patient/Family Quality of Life The analyses of the impact following hypotheses:
of hospice
on the lives of patients
and their families
test the
Hypothesis 1 The quality oj’patients’ lives in hospices \ilill he better than that experienced by comparable non-hospice patients. Patients will experience fewer discomforting symptoms, less severe pain, more positive mood states, and greater satisfaction with care received. Hypothesis 2 The.fkmi1ie.s of hospice patients
M’ille.uperience ,f&ter physical
ISSUES
In developing -Selection -Timing -Validity
an analysis
AND
problems.
RESOLUTIONS
plan to test these hypotheses,
of outcome areas. of data collection. of patient reports.
and psychosocial
three major
issues arise:
National
Hospice
Study
Analysis
Plan
753
TABLE 5. POWER TABLE FOR SAMPLE SIZES NECESSARYTO TEST
THE
PATIENT
CONFIDENCE
LEVEL
COST (N
HYPOTHESIS = SMALLER
AT OF
95%
THE
COMPARISON
SAMPLES)
Differences in samples expressed as a percentage of the mean
Level of statistical (l-8)
-~
power
%
0.5
0.6
0.7
0.8
0.9
IO 20 30 40 50
800 200 89 50 32
1016 254 113 63 41
1276 319 142 80 51
1616 404 179 101 65
2156 539 239 135 86
Selection
of outcome
Quality state, the relations. quality of
of life is a multi-dimensional construct which is conceptualized as positive mood absence of physical and psychological distress, and satisfactory interpersonal In this study, we have identified a series of measurable dimensions of patient life:
-Severity of pain -Functional status -Quality of social -Satisfaction with -Sense of isolation -Satisfaction with
areas
and other symptoms. and mobility. interactions. life. and burden on others. care received.
Table 6 (segments A through H) lists the scales and measures used to generate the dependent variables which represent the dimensions of patient quality of life. With respect to thefamily, hospice claims to be effective in mitigating grief reaction and decreasing psychosocial and physical morbidity through the provision of training, education and counseling while the patient is alive and, subsequently, through bereavement and counseling. Hospice can also benefit the family indirectly. The family may feel more secure in the knowledge that they have done all they could; death may not be viewed as a failure on their part. Additionally, because the family will have been educated as to what they should expect in the final stages, the psychological trauma associated with death may be reduced. From this perspective, the outcome areas being assessed are: -Indicators of family secondary morbidity dysfunctional symptoms). -Family satisfaction with care received. -Subjectively reported grief reaction.
(psychosocial
The scales and measures to be used to capture 6 (Segments I through L).
distress,
each outcome
role
change,
and
area are listed in Table
Timing of data collection In determining the frequency of follow-up contacts, a number of factors were considered. First, the initial follow-up had to be timed to include the large number of patients who die within two weeks’ time of admission to hospice. Second, for ethical reasons and to maximize the participation rate, the response burden on both patients and families had to be minimized. Finally, we sought a schedule of contacts which would enable the data collector and the patient/family unit to set aside a constant time period on a given day of the week for all visits. The unpredictability of duration of life for terminally ill patients makes it impossible to systematically schedule visits so that one will coincide with the final few days of life, but the schedule assures a last follow-up contact generally no more than two weeks prior to death.
NPJIUNAL
questions
Impact on patient satisfaction with medical care
G
H. Impact on PCP satisfaction with professional care c l”romlal support
Impact on overall quality of life of pallanl
F.
on
the feeling a burden
ImpaLA
E.
of being
“load
RPS’SEAKCH QUESTIONS
diw
support
CBTL‘
of life
professional
3 days
on
Satisfaction with profewonal care of patient (including
Inr
purienr
with
Satisfaction
While
of last
a burden
Character
HRCA QL-Index Uniscale Karnofsky
Sense uthws
Dysphol-ic
of pain
or visiting
Self esteem
Chatting
Impact on patient perceived social Interactlo”\
C.
patient’s of being
STIJDY:
&verily of common symptoms other than pain: Nausea or vomiting Dry mouth Constipation Dizziness bever or chills Shortness of breath Overall assessment
Description
Impact on patient‘s physical symptoms
research
HOWKF
B. Impact on patient report of pain
A.
6.
0utc0mc area
TABLE
assessment
PCP self report
Patient self report
PCP assessment PCP assessment Interviewer ludgement PCP bereavement
Patient self report
Patient self report Patlent self report
Patlent self report
Pallenl self report PCP assessment
PCP
or
OUTCOME
Source data
Patient self report
ON PATI~NT/~AMILY
AREAS
5
IO
I3
5
2
IO
6
4
2
6
Items
AND
Number
A fXTlNC
I
I
2
h
I
1
I
I
2
and
Rand,
Wolf
HR(‘A
e/ (Il., and HRCA
Wolf et al., Rand, and IIRCA
Kastenbaum
HRCA, Spitzcr Spitzer Karnofsky
HRCA
HRCA
Moditied from Li”n’\ Modification of POMS
Rosenberg
HRCA
I
Spitrer Melzack Spitzcr
I
source*
I” gcncral “SC
Item
MEASURbS
1
I
2
I
Outcome measures
of:
OF ASSOCIATEU
Impact on secondary morbidity/grief experienced by family members
Bereavement Physical symptoms Depression Overwhelmed Anxiety Loss of faith Unsettled Anger
PCP self report 5 6 I2 3 3 5 5
8
While patient dice rmd ut hereaoement Symptoms
3
I
I
5
PCP self report
PCP assessment
PCP self report
While putient alive Mood state
Residence change Job related
B.Cr~U~emeflt Social involvement/family interaction
Job related
Ability to meet other needs
While patient alive Social Financial
I
1
I I I I I
1
Sanders Sanders Sanders Sanders Sanders Sanders Sanders
HRCA
Rand
HRCA HRCA
& HRCA
& Rand
Rand and Sanders
HRCA
HRCA
HRCA HRCA
*Linn MW, Linn BS, Harris R: Humanistic Oncology: The Potential in the Omega Experience. Miami, Florida: VA Medical Center. 1980 Melzack R: The McGill pain questionnaire: major properties and scoring methods. Pain 1: 277, 1975 Rand Corporation: Instrumentation for Hospice Study, 1980 Rosenberg M: In Measures of Social Psychological Attitudes. Robinson JP, Shaver PR (Eds). Ann Arbor, Michigan: Institute of Social Research, University of Michigan, 1973 Saunders C, Mauger P, Strong P: A Manual for the Grief Experience Inventory. Loss and Bereavement Resource Center, University of Southern Florida, 1979 Spitzcr WO, Dobson AJ, Hall J, Chester-man E, Levi J, Shepherd R, Catchlove BR: Measuring the Quality of Life of Cancer patients: A Concise QL Index for Use by Physicians. The Royal North Shore Hospital of Sydney, The Commonwealth Institute of Health of Australia at Sydney University, The University of Newcastle and the McGill Cancer Centre Wolf MH, Putname SM, James SA, Stiles WB: The Medical Interview Satisfaction Scale: Development of a scale to measure patient perceptions of physician behavior. J. Behav Med I: 391, 1978
J.
1. Impact on social roles of family members
DAVID S. GREEKet ul.
756
Validity
of patient
reports
During the terminal stages of cancer, some patients are not lucid or able to communicate. The likelihood of this occurring increases as the patient approaches death. Ability to acquire valid data from the patient under these circumstances is diminished. To compensate for this, two strategies have been adopted. First, a PCP Assessment of the patient is completed at each follow-up, even if no interview with the patient is possible. This assessment provides for continuity of measurement for all patients. Secondly, at both the initial and follow-up patient interviews, non-attitudinal measures concerning the patient are obtained by proxy from the PCP if the patient is unable to provide this information.
ANALYTIC
Forms
qf the
dependent
STRATEGY
variables to be tested
Table 6 lists the outcome areas, the associated scales or measures, their sources and the method of obtaining the data. Repeated measurements will make it possible to approach the analysis of each dependent measure in several ways. These can be categorized as: (1) Simple comparisons of a variable at different follow-up interviews (e.g. last, next to last); (2) Summary measures of patient status on a given variable across various intervals (e.g. between the last and an earlier period); (3) Change scores calculated on the basis of the direction and magnitude of change on a given variable between two temporally adjacent follow-up interviews; (4) More complex interactive measures relying on information from both the patient and the principal care person. The simplest form of the dependent measure is an established summated scale as outlined in Table 6. Patient scores on such measures can be compared for each discrete follow-up period. This approach addresses such questions as “What is the impact of hospice (e.g. on patients’ symptom patterns) in the last weeks of life?” This least complex form of each dependent measure construct is the basis for the explicit hypothesis testing. The dependent measures may also take the form of a summated score over the impact period. Each patient’s raw scores at different interviews for a particular outcome measure can be summed with the goal of creating a total index for the variable of interest. Included within the dependent variable array for the patients are a number of previously established scales that can be used in this type of summated format. By summing the scales over time and creating average scores, patients’ status during exposure to hospice (or conventional care) can be characterized. These scales are known to be sensitive to shifts in the status of patients. For example, the Melzack Perceivable Pain Inventory scores the degree of pain-from none to excruciating-based on the patient’s response. A change score measuring the difference in the degree of pain experienced by the patient between any two points in time is constructed by subtracting the pain score recorded at one interview from that of the preceding contact. A final approach relies on comparable information obtained from both the patient and the principal care person to construct a measure of discrepancy of perception. For example, one dependent variable uses both patient and family information regarding the patient’s last three days of life. During the initial interview, the patient is asked: “If the last three days of your life could be exactly they be like?”
the way you want them, what would
The interviewer classifies the response to this open-ended question based on whether particular issues were mentioned. Examples of common response classes are: freedom from pain, at peace with God and in the presence of loved ones. At the bereavement interview,
National
Hospice
Study
Analysis
757
Plan
the PCP is asked to characterize the patient’s final days of life on the same set of issues. On the basis of these two data sources, difference scores are calculated. It is possible to determine whether the last three days live up to the expectations of patients and whether hospice patients are more or less likely to have spent their last days as they wished.
Number
qf dependent uariuhles
The multiplicity of quality of life outcome areas and the variety of forms specific variables can take result in a proliferation of outcome measures. Valid arguments can be made for the relevance of each. However, this multiplicity of variables makes it difficult to integrate and interpret even statistically significant results. Therefore, for the purpose of hypothesis testing, the analyses are reduced to single summary indicators of patient and family outcome within each of the domains listed earlier. However, in order to capitalize on the richness of the data, established statistical techniques, involving a widening of confidence intervals and narrowing of critical regions to compensate for the loss of significance associated with multiple tests, can be used (e.g. the methods of Bonferroni, Tukey and Scheffe).
Examining
diSferences in longetliiy
The procedures for selecting conventional care patients described in Section I seek to ensure that, on average, conventional care patients enter the Study at the same point in their terminal trajectory as do hospice patients. (For hospice patients, Study entry is admission into the hospice.) In the absence of random assignment, the evaluation can only simulate this comparability by monitoring longevity differences between the groups and adjusting the conventional care selection procedures prospectively in the event that differences are observed. If differences in the length of life distributions of hospice and non-hospice study patients are found at the end of the data collection period, there are two possible explanations. (a) Selection hius. That is, the selection criteria were not sufficiently sensitive to ensure that hospice and non-hospice patients entered the Study equidistant from death. (b) An ~fict on morfalify. That is, hospice or conventional care patients having entered the Study at comparable points in the terminal phase live longer: presumably due to the specific nature of the interventions they received. Should a difference in the length of life distributions be observed, the initial interpretation will be that it is a function of selection bias. To test this assumption, differences in length of life will be statistically controlled. Using both multiple regression and sample adjustment procedures, patient longevity will be examined to identify predisposing factors conceptually relevant to “explaining” length of life. These will include: -rate of disease progression-time between initial -cancer diagnosis; -metastatic sites on Study entry; -functional status on Study entry; -prior treatment (surgery, chemotherapy, radiation -cancer type (e.g. lung, breast, etc.); -age; -presence of non-cancer-related medical conditions.
diagnosis
and date of Study
entry;
and combinations);
The predicted longevity of hospice and non-hospice patients will be compared. If greater than one week, additional analyses will be undertaken to isolate other potentially contributing factors. Observed longevity differences will, however, have no bearing on comparative analyses of quality of life or patient cost outcomes since all analyses will be performed retrospectively from time of death.
758
DAVID S. GREER el rtl
Section IV-Determining The patient/family Hypothesis Hospice
economic
the Impact of Hospice on Health Care Costs analyses
test the following
hypotheses:
1 patients
have lower terminul
because less expensive care. Hypothesis 2
home/hospice
The cost qf curing for demonstration ,for comparable
non-demo~srratjon
likely to induce demonstration paid staff for volunteers*. Hypothesis 3
care costs than comparable
care is substituted
non-hospice
for more expensive
patients,
institutional
hospice patients will be higher than the cost of caring
hospice
patients,
hospices to increase
Hospice patients served by hospital-bused higher terminal care costs than comparable
because Medicare reimbursement is the volume of services and/or substitute
hospices or hospices with inpatient beds will have hospice patients served in other settings, because
hospices with inpatient beds will provide more institutional care and less home care than hospices without inpatient beds, and presumably institutional care is more expensive than home care. Hypothesis 4 Medicare hospices,
wjill pay ,fbr relatively
compared
because federal Hypothesis 5
more qf the cost of‘ care ,for patients
to patients in non-demonstration
reimbursement
in demonstration
hospices and conventional
will affect the type and quantity
of services
care settings,
rendered.
Hospice cure will a$Gect the level of informal home care provided to terminal patients (but the direction of the effect is unclear). Family involvement along with greater time spent by the patient at home may lead to an increase in the amount of informal care provided by families; alternatively, the expected increase in forma1 care provided by the hospice may substitute for informal care and lead to a reduction in the amount of informal care provided by families and volunteers. ISSUES
In developing
an analysis
AND
plan to test these hypotheses,
-measuring costs; -timing of the measurement of dependent -pooling observations across sites. Measuring
RESOLUTIONS
variables;
three major
issues arise:
and
costs
Overview. The patient cost analysis uses standard accounting definitions of unit costs for the services used by hospice and conventional care patients. The accounting standards used by Medicare are applied to both Medicare and non-Medicare reimbursable services because they are consistent and widely used. Since the price to payors of specific health care services is rarely equivalent to the cost of producing it?, economic analyses must treat charges for services separately from costs. In a non-profit operation, the total monetary costs of a service should equal total charges, when charges include all direct, indirect and imputed payments. In fact, it is impossible to identify all payments and it is equally impossible to measure all costs. Costs are
*If demonstration hospice care is more expensive than non-demonstration hospice care but less expensive than conventional care, then the effect of hospice reimbursement on system health care costs hinges on the extent to which the waiver system induces people who would have been using conventional care into the hospice system vs the extent to which the waiver simply substitutes reimbursed for non-reimbursed hospice care. tThird party reimbursement procedures and provider billing practices typically involve various types of adjustments. discounts, and cross-subsidies.
National
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159
Plan
absorbed by the system, accepted as uncollectable bad debt and/or shifted onto other payors. For these reasons, the patient/family economic analyses examine costs, derived from resource commitments, separately from charges or how the burden @paying for care is shared among payors. Cost construction. Regional average Medicare unit costs are used to compare hospice and conventional care. These unit costs are applied to Medicare and non-Medicare patients, regardless of whether they are served by hospices or by non-hospice programs. Cost construction depends upon the kind of service provided. In some cases, regional average Medicare costs-per unit of service are multiplied by patient utilization levels (e.g. nursing visits). In others, total charges per patient for services are multiplied by patient utilization levels (e.g. physician visits). In others, total charges per patient for services are multiplied by regional average Medicare cost to charge ratios (e.g. ancillary services). Medicare data for costing are derived from Medicare Cost Reports available from secondary sources. In comparing demonstration and non-demonstration hospice patients, unit of service cost/charge coefficients are developed for each participating hospice for use in the patient level cost analysis (see Section VI). In hospice/conventional care comparisons, these regional averages substitute for the specific hospice cost coefficients to determine the costs of services hospice patients use. In the event that comparable hospice services “cost” substantially more per unit than regional Medicare averages (based on the facility level analyses), the intensity of services (e.g. number of hours of care per visit) can be used to differentially weight hospice patients’ utilization. Thus, the form for defining costs will differ somewhat in performing hospice/non-hospice and demonstration/non-demonstration comparisons. -The hospice/conventional care analyses will compare relative resource utilization using unit cost weights that are constant across facilities (but not across regions), but that vary among patients due to differences in service intensity. -The demonstration/non-demonstration analyses will compare patient costs, within which both levels of utilization and unit costs can vary among patients and facilities. All of the following services, whether or not they are Medicare adjusted to cost bases for the hospice/conventional care analyses:
reimbursed,
will be
Inpatient hospitalization: routine and ancillary costs, adjusted by region and facility (bed size, teaching status); Outpatient visits: costs per visit adjusted by region and facility type; Skilled nursing facility days: costs per day; Home health visits: costs per visit.
type
Analysis of charges. Some services cannot be readily subsumed under this methodology. Physician fees can be related to Medicare standards for “reasonable and customary” charges. This standard may not reflect the costs of a physician’s services. Moreover, there are separate standards for hundreds of different procedures performed by physicians which determine the charge. Drugs, equipment, medical supplies and other expenses are similar. No single regional standard can be developed to translate a drug charge into a measure of cost. The variety of types, brands and sources of drugs makes such a procedure impractical. The same can be said for supplies, medical equipment and other expenditures. For these reasons, we plan to separately analyze variations in charges between hospice and conventional care patients, and between demonstration and non-demonstration hospices for physicians’ visits (not billed through the facility) and for drugs supplies and other treatment related expenses. Much of the variation in these measures reflects billing practices and the relative market “power” of individual physicians. Timing
qf the measurement
All analyses (‘D36’11<
are stratified
of dependent by length
variables
of life. First,
all patients
who live at least a week
760
DA\III) S. GREEK et d
after they entered the sample are analyzed to ascertain the effect of hospice care on total costs in the last week of life. The same analysis is then performed for those living at least 3, 5, 7, etc. weeks. This procedure for analyzing total costs at different lengths of time before death makes it possible to deal with the problem of varying time periods of observation. It also provides a method for approximating a non-linear time relationship of costs to treatment period. Suppose that hospice care reduces hospitalizations predominantly in the last weeks of life and increases home care over the entire time that a patient is in a hospice. As the length of stay in hospice increases, the cost advantages of hospice would decrease. The proposed procedure provides a test of this expectation; it will demonstrate whether length of hospice stay does, in fact, affect the cost savings due to a hospice. The total hospice “effect” for a patient with a given length of participation will be the sum of conventional care minus hospice costs, over a certain number of weekly or bi-weekly periods. Thus, the total cost differential due to hospice is the sum of these individual effects for all sample hospice patients in a specified number of intervals. Pooling
ohseraations
across sites
In testing the patient level cost hypotheses, three jointly or separately analyzing data from all sites. -Data can -Analyses the three -Data can
possible
options
are available
be pooled from all sites. can be performed separately using patients drawn only from sites adjacent regional management centers. be pooled only from the sites in the three regions.
for
to
Each option has advantages and disadvantages. By performing analyses at all three levels and integrating the results, the evaluation capitalizes on the advantages of each option while minimizing the disadvantages. The main advantage of the first option-pooling all the data-is that it maximizes both the patient and facility sample sizes. maximizing the statistical power of the tests. However, it also maximizes the burden put on the analysis to control for regional differences in the patterns and costs of care. The second option, performing analyses separately within each primary area, minimizes the burden of controlling for regional differences in care patterns. However, since within-region patient sample sizes are smaller, estimates of the effect of hospice compared to conventional care are less precise. Given the smaller number of demonstration and non-demonstration hospices within each region, it is not possible to estimate the effect of hospice organizational structure on the patterns and costs of care for the terminally ill within region. The third option is a compromise between the first two. Problems of comparability will be larger than in the second option, and smaller than in the first option. Statistical power and the ability to estimate the effects of hospice organization types on outcome will be less than in the analyses of the first option (with all data pooled) and greater than in the analyses of the second option (of each primary area taken separately). Formal testing of the explicit cost hypotheses are based on the first option of pooling all data. The use of regionally standardized cost coefficients and control variables reflecting regional variations in patterns of care should be sufficient to accurately assess differences in resource use. On the other hand, tests of the payor burden hypotheses are reasonably restricted to option three (pooling only the three regions) in view of the sharp variation in the pricing factors that result in billable charges.
ANALYTIC
STRATEGY
There are three major components to the patient/family economic analyses: patient analyses, distribution of payor burden analyses and informal support analyses.
cost
National
Construction
qf andysis
Hospice Study Analysis Plan
761
zlariables
for the cost, payor burden and informal support components of the study are created from a synthesis of both primary and secondary data sources according to the following model. Patient cost. Inpatient, outpatient and home care utilization and charges are converted to a Medicare cost basis, using cost to charge ratios taken from secondary sources. Cost to charge ratios are regional averages (by type of facility, for hospitals). Hospice unit costs, which are constructed as part of the organizational and facility cost analyses (see Section VI) are specific to each individual facility. Consequently, relative to the regional averages approach, there is greater variability in service costs of hospice services. Therefore, facility specific costs are used only in comparisons of demonstration and non-demonstration hospice patients. Payor burden. Medicare payments for covered services are obtained from claims files and are interim payments (payments to facilities before year end adjustments are made). Self-payment is estimated, using the out-of-pocket expense information (log-diary) and supplementary information on non-Medicare insurance coverage for each patient. Total charges are determined from Medicare Claims Files for Medicare services and from bills and receipts for non-Medicare services. Since demonstration hospices do not charge for covered services, and since Medicare covers the entire amount of allowed charges for these services, demonstration charges are identical to Medicare payments for these services. Irzformal support. Total hours of home care is captured on the Service Records and the hours of informal support provided by families, friends and non-hospice volunteers comes from interview information. Analysis
Patient
variables
cost analyses
Medical and services costs per case include the costs of care provided to patients by hospitals, nursing homes, hospices, physicians, outpatient and at-home visits, prescription drugs and medical equipment and supplies. Both reimbursed and out-of-pocket costs are included. Several types of dependent variables are analyzed. (I) Total costs for the last week of life and for each previous bi-weekly periods, for demonstration, non-demonstration and conventional care patients; total costs include patient hospital and SNF care, outpatient and home care visits. (2) Total costs, as defined, for the entire study period (intake to death) for demonstration and non-demonstration hospice patients. (3) Total home care costs for the entire study period for demonstration and nondemonstration patients. (4) Total physician charges, for periods and patients described in categories 1 and 3 above. (5) Total drug, equipment. supply and other charges, for periods and patients described in numbers 1 and 3 above. A measure of the effects of alternative types of care on total health care costs or charges can be obtained by estimating separate regression equations for patients in demonstration and non-demonstration hospices and conventional care settings as described in Section II. If analyses of total cost show hospice care is different, there are both substantive and methodological reasons for analyzing the subcomponents of total cost. Substantively, knowing that total cost per case goes up or down in a hospice does not provide an understanding of why costs change. Analysis of the aggregate total cost obscures the various pathways through which hospice care may affect costs. We have chosen in advance to study home care costs for hospice patients because hospice programs have been designed to provide a home care alternative for the dying patient. As such, two estimates exist (i.e. home care vs total costs) of the effects of hospice (or particular types of hospice) on the cost of care for terminally ill patients.
762
DAVID S. GKEEKCI ul.
Distribution The
qf payor burden
analyses
described
above
considered
“costs”
to all
payors
(i.e.
the
amount
reimbursed by all payors). For policy purposes it is important to know the effects of hospice care (and of Federal reimbursement) on the portion of charges paid by Medicare, other third parties and patients and their families. Actual charges are used in this analysis rather than standardized costs. These charges will cover all categories of services gathered, excluding volunteer services. Total charges are defined as billed charges for all services to conventional care patients and non-demonstration patients and non-hospice services provided to demonstration patients. Hospice services provided demonstration patients must be treated differently from ordinary Medicare reimbursement because they are not liable for deductables or co-payment: the hospice submits bills directly to the HCFA Office of Direct Reimbursement using budgeted costs and an estimate of patient utilization. The hospice receives payment in amounts that reflect total expected reimbursement. Thus, demonstrationcovered hospice services are viewed as “billable” charges. Payments are defined as: (1) Interim payments by Medicare (non-pro-rated adjustment to be included for final adjustment) are facility-specific rather than patient-specific. (2) Out-of-pocket payments that are documented in the Service Record and supported by bills. “Other payor” payments will be computed as the residual, that is, the difference between total charges and total Medicare plus out-of pocket payments. The measure of payor burden used in the analysis is total billed (or billable) payment source). Multivariate analysis will be conducted for:
charges (by
-Medicare payments/total charges, for the period intake to death, for demonstration and non-demonstration hospice patients and conventional care patients. -Self-pay/total charges, for the same breakdown. Since (Medicare/total) + (self-pay/total) + (other/total) = Total charges. it will not be necessary to estimate the “other” equation once the first two equations have been estimated and total charges have been determined. Informal
support
Measures of the level of informal support received by terminally ill patients from the primary caregiver and their family members are available from interview data. Potential effects of service mode are tested by comparing the hours donated by caregivers of patients in the various samples. Although this analysis captures part of the resource intensity of hospice care, one cannot justify imputing dollar values to informal support. Thus, this analysis is treated separately from other components of the patient/family cost analysis.
A
SUPPLEMENTARY
WAIVER
HOSPICE
PATIENT
ANALYSIS
Separate analyses of the hospice cost and utilization data available from HCFA/ODR Medicare bills on the complete census of all Medicare demonstration hospice patients are being performed. The advantages of this sample are its large size (expected to include over 5000 patients), its inclusion of terminal patients without cancer and the fact that complete detailed utilization data of hospice services will be available. Analysis of this sample may provide information on the effect of alternative hospice organizational types on services provided by the hospices, and it may increase our understanding of the relationship between patient functional status) and services characteristics (e.g. diagnosis, patient demographics, received. Moreover, since the follow-up sample is limited to terminal patients with cancer, this supplementary analysis of both cancer and non-cancer patients provides the only
National
source of information disease.
Hospice
on the costs of terminal
Section V-Comparisons
Study
Analysis
Plan
763
hospice care for patients
without
malignant
of the Intervention Terminal Cancer Patients Receive
The comparative analyses of the service interventions patients are exposed test the following hypotheses:
to which hospice and non-hospice
Hypothesis 1 Hospice patients and their families will be more likely to receive psychosocial support services than non-hospice patient/family units, given the emphasis in the hospice philosophy of treating the whole person and the focus on interdisciplinary treatment. Hypothesis 2 The involvement of physicians in the care of terminal patients will be less among hospice patients relative to the involvement of other service providers. Hypothesis 3 Hospice patients will be less likely to be exposed to high technology and/or intensive diagnostic and therapeutic procedures during their last months of life than non-hospice patients. Hypothesis 4 The level of analgesic and tranquilizing medications prescribed for and consumed by hospice patients will he higher than for non-hospice patients, given the hospice emphasis on the prevention of pain and other symptoms. ISSUES
The methodological
and conceptual
(a) The validity of self-report (b) Implied value judgements. Validity
?f’ self-report
AND
RESOLUTIONS
issues relevant
to testing
these hypotheses
include:
data.
data
Patient-level data concerning exposure to various services are gathered directly from the Primary Care Person (PCP) at each scheduled follow-up visit. Rather than relying on the utilization data available for the Patient Cost Analyses, the PCP is asked whether the patient received any one of over 20 discrete types of services. Potential problems of recall are minimized by the bi-weekly follow-ups. Some differences in interpretation may occur. A syllabus of service definitions has been developed to explain the meaning of each type of service to the PCP and the instrument has been successfully pretested. Implied value judgements In testing the hypotheses presented above, no attempt to assess quality or to establish norms is implied. The hypotheses derive from the stated goals and philosophy of the hospice movement rather than value judgements. If the interventions are different and can be correlated with differences in outcome, some value judgements may be implied by the data, but neither the methodology nor the mandate of this study justifies value judgements. Conventional care is changing rapidly, at least partly as a function of the impact of the hospice movement and it is essential to determine whether the pattern of services provided to hospice patients is, indeed, different from that received by non-hospice patients. ANALYTIC
SAMPLES
The third and fourth hypotheses are tested on a subsample of the follow-up sample. The subsample consists of approximately 10% (n = 160) of the D hospice patients and 30% (n = 130) of the ND hospice and CC patients; it is a random sample of the full follow-up sample drawn proportionately from each participating study site. For this subsample, detailed prospective data on Medication Prescription and Utilization are collected.
164
DAVID S. ANALYTIC
GREEK
el ul
STRATEGY
The basic analytic strategy compares the likelihood of receiving various medical and psychosocial services in hospice and non-hospice programs at various points in the terminal phase of the patient’s disease. The service activities compared are categorized and listed below: Medical
Respiratory therapy Surgery Chemotherapy Radiation therapy Hormone therapy Thoracentesis X-Rays Blood tests Oxygen Physical therapy Intravenous therapy Bladder/catheter care Ambulance
Psychosocial
Counseling Financial/legal counseling Assistance with paperwork Arranging for services Training patient in self-care Healing/therapeutic touch Guided imagery Meditation/prayer Relaxation exercises Hypnosis
The initial comparative analysis adopts a service-by-service approach, first examining the proportions of patients in each group receiving a service within two weeks of death, within 4 weeks of death, etc. Then, the cumulative likelihood of hospice and non-hospice patients receiving a particular service at any time between study entry and death is examined. In addition to a variable-by-variable approach, service configurations are being constructed to take into consideration the possibility that services are interchangeable, or at least perceived as such. For example, financial/legal counseling may effectively be handled by assistance with paperwork (e.g. filing insurance claims, etc.). Similarly, oxygen and respiratory therapy can be seen as the same by a PCP. An “either/or” configuration caputures this substitutability. Further, receipt of service, or set of services, can be linked to the patient’s relevant symptoms during the same, or a temporally adjacent, measurement period. For example, the proportion of patients reporting shortness of breath who receive respiratory or oxygen therapy can be compared for the hospice and non-hospice samples. It must be recalled, however, that the data collection strategy makes it impossible to demonstrate a direct causal link between the emergence of a symptom and introduction of a service to ameliorate the symptom. The comparisons must remain descriptive, i.e. given similar symptom patterns, do patients in hospice and non-hospice settings receive different configurations of services? To test the hypothesis that hospice patients are more likely to receive psychosocial support services, a configuration measure is used which indicates that some level of psychosocial intervention has occurred if a patient has received one or more of an array of such services. To test the hypothesis that hospice patients will have less physician involvement, analysis will be done for various intervals or over the entire impact period (intake to death) on the basis of the number of physician visits. The prevalence of medical interventions can be addressed in the same manner; testing each medical intervention or diagnostic laboratory study separately. However, in view of the anticipated low frequency of any given service, clinically meaningful sets of services are combined. The resulting measure should provide an indication of the medical regimen to which a patient is exposed in his/her last months of life. Given the prevalence of pain and distress among terminal cancer patients and the emphasis hospice places on preventive pain control. a special analysis comparing the prescription patterns of analgesics and tranquilizers for hospice and non-hospice patients
National
Hospice
Study
Analysis
Plan
165
is being conducted. For analgesics, the diverse medications prescribed are converted to standard pharmacological analgesic dose equivalents and the analgesic dosage prescribed per kg body weight is compared for hospice and non-hospice patients. A similar approach is used with tranquilizers, merely comparing the likelihood of prescription by major type across the three groups. Since there may be changes in prescribed levels after the patient has been exposed to hospice for a week or more, principal comparisons are based upon data from the first follow-up visit. Since outpatient medications are often prescribed pm with guidelines informally provided by medical and nursing staff, the actual amount consumed in a 24-hr period is obtained during each follow-up contact. Consumption is therefore compared separately from prescription patterns. Actual consumption may vary considerably as a function of patient compliance as well as the practice of the provider. Nonetheless, it will be of interest if consistent differences in consumption between hospice and non-hospice patients with similar prescribed levels of analgesics are found.
Section VI-Organizational The organizational components:
and
facility
cost
and Facility Cost Analyses analysis
has
three
separate
but
inter-related
-Quantitative analyses of the relationship of reimbursement to changes in the organizational behavior of hospices. -Descriptive analyses of the relationship of reimbursement to the cost of hospice service and the revenue mix of hospices. -Qualitative analyses of the relationship of participation in the demonstration to changes in the organizational structure and goals of hospices. The analyses
to be conducted
address
the following
major
research
questions:
Hypothesis 1 Hospice growth and changes in the case-mix of patients served will be dSfSerent in demonstration and non-demonstration hospices, since an unrestricted retroactive cost-based reimbursement system in demonstration hospices provides an incentive for rapid growth. Hypothesis 2 Changes in the organizational structure, staff composition and the roles allocated to volunteers will difSer between demonstration and non-demonstration hospices; rapid growth may necessitate increased use of professional vs volunteer staff. Hypothesis 3 The unit cost qf hospice services will direr in demonstration and non-demonstration hospices; the overhead allocation system may encourage higher administrative costs and contracts with other agencies may be encouraged by reimbursement. Hypothesis 4 The rate of organizational change will difSer between demonstration and nondemonstration hospices.
ISSUES
In addressing
these research
AND
questions,
RESOLUTIONS
several
issues and considerations
arise:
-Evaluation of differential organizational change in a dynamic system. -Non-random selection of participating hospices and comparability of demonstration and non-demonstration hospices. -Change in demonstration hospices in anticipation of reimbursement. -Differences in hospice years. -Initiation of reimbursement prior to evaluation field efforts.
DAVIII S. GREEK et al.
766
Evaluating
d@erential
change in a dynamic
system
All hospices can be expected to proceed through a series of organizational changes. The evaluation must differentiate spontaneous change from change resulting from participation in the demonstration. Non-demonstration hospices provide an indicator of the natural history of change, i.e. the baseline to which demonstration hospice organizational change can be compared. Both the rate and magnitude of change are being assessed whenever possible. Non-random
selection
of’ participating
hospices
In selecting demonstration hospices, HCFA applied the criteria of competence and excellence, resulting in a non-random, potentially non-representative sample. In selecting the non-demonstration hospices, we applied similar criteria within the confines of our regional approach. Consequently, the organizational and facility cost analysis described in this chapter is not statistical in the commonly understood sense. We cannot generalize about behavior from statistics computed on the basis of data from these hospices, nor can we compute measures of the accuracy of our estimates. We can now view these data heuristically, however, to uncover relationships that may subsequently be explored in greater depth with a scientifically drawn sample. Change in demonstration
hospices
in anticipation
qf’ reimbursement
The 26 demonstration hospices submitted their proposals to HCFA in late summer, 1979 and were notified of the award within three months. From that point until the actual initiation of the reimbursement on October I, 1980, the hospices began preparing for the introduction of reimbursement. Conversations with hospice administrators indicate that internal procedures, record keeping, and even the organizational structure of the hospices changed markedly during this interim period*. To address this issue, the evaluation has qualitatively examined this phenomenon for the period prior to the demonstration and, where possible, prior to notification. DifSerences in the periods covered by ,fiscul years These differences exist among demonstration and non-demonstration hospices. The annual HCFA demonstration cost reports use existing fiscal years which vary from June 30 to December 3 1. This means that the first “year” cost may include 2-l 2 months of cost data. A full year of data for all hospices is available only from second year cost reports. Because of differences in the starting dates of fiscal years, the time periods covered by the second year vary as much as 9 months across the hospice. In order to control for this, the cost reports are being adjusted for area wage inflation in those hospices with a time period differential of 3 months or more. Initiation
of reimbursement
prior to evaluation jield eforts
In initiating evaluation data collection activities on August 1, 198 I, it is recognized that important changes in demonstration hospices occurred prior to this date. Conversations with hospices suggest that many had expanded their staffs and increased their patient volume. While many of the more specific hypotheses to be tested can be addressed utilizing propsective data, others must be addressed using a retrospective reconstruction of data from hospice files. Certain data which are available for the period October 1, 1980 through July 3 1, 1981 have been abstracted and analyzed. These data include the characteristics of patients served, staff time allocations and payroll data enabling time series comparisons across the full demonstration period.
_ *Despite the criteria to this period.
established
for the demonstration.
at least five hospices
were not actually
operational
prior
767
National Hospice Study Analysis Plan FACILITY
DATA
SOURCES
Facility-level data can be separated into four basic types: (a) aggregated patient data, (b) staff, (c) organizational, and (d) fiscal. The specific data sources relevant to each type are described in Appendix B. ANALYTIC The organizational
STRATEGY
and facility cost analyses
are to achieve two principal
(1) To provide facility cost data for use in the statistical analyses costs of hospice care. (2) To explore a variety of general questions about the relationship teristics to organizational behavior.
project
goals:
of the patient-level of facility
charac-
The discussion below outlines the specific approaches taken in analyzing organizational change and facility costs. There are three separate components to the analyses addressing these issues: (1) Quantitative analyses of the relationship of reimbursement to changes in the organizational behavior of hospices. (2) Descriptive analyses of the relationship of reimbursement to the cost of hospice services and the revenue mix of hospices. (3) Qualitative analyses of changes in hospice organizational structure and goals. The methods below. Analyses
and specific
of organizationai
hypotheses
to be tested
in each component
are described
change
The quantitative analysis of change in the behavior dependent variable domains:
of hospices can be grouped
into three
(a) Volume and mix of patients admitted. (b) Staffing patterns. (c) Mix of services provided patients. Impact on volume and mix of patients.
The following
directional
hypotheses
can be stated:
The number of patients served in demonstration sites will increase faster than in non -demonstration sites; The proportion of patients served for whom reimbursement is available wili increase more in demonstration than non -demonstration sites; Demonstration hospices with designated beds will have fewer patients dying at home than those without such beds. The basis for testing each of these hypotheses is an examination of differences in trends evidenced by demonstration and non-demonstration hospices. The final data analysis will involve a combination of: (1) graphic displays of trends in the data; (2) a carefully chosen structural model&presumably a time series model; and (3) a statistical test for differences in trends associated with the comparison groups. Fourteen months of aggregated patient data are available for both D and ND hospices, and an additional 10 months are available for D hospices. Plots of change in patient volume, case-mix and discharge disposition provide a clear indication of shifts over time. The statistical power of tests for differences in trends is limited. However, given the potentially large effects the reimbursement can have on organizational behavior, if these effects occur as hypothesized, they can be detected with even small samples. Analyzing changes in stafing patterns. Four issues are of interest in examining staffing patterns and utilization: -Use and role of volunteers. -Staff turnover rate and “burnout”. -Time spent on interdisciplinary clinical -Growth in the administrative function.
team activities.
768
DAVID S. GREEK
These issues will be examined
by testing
specific hypotheses.
These are:
The use of volunteers to deliver direct patient services will decrease in demonstration sites; the availability of reimbursement for direct services provides an incentive to have such services provided by paid staff. Stufl turnover rates and indicators of stress and burnout in demonstration hospices will be higher than in non-demonstration hospices; organizational growth is an additional stress. The amount qf time devoted to interdisciplinary team activities will increase in demonstrution sites; there is a separate cost allocation for interdisciplinary team functions. The proportion of totul stefl time devoted to administrative us opposed to direct service activities will increuse in demonstrution sites. The data base for testing these hypotheses is: a log completed by all paid staff in both D and ND sites monthly; volunteer records documenting the number of hours volunteers spend in direct care and administrative activities; quarterly salary and turnover records; and staff questionnaires which yield average hospice staff “burnout” scores as measured by a reliable attitude scale. The monthly percent change in the ratio of direct care to administrative hours provided by volunteers is plotted and tested as described above. The proportion of time direct care paid staff spend in interdisciplinary team meetings and for other administrative purposes is plotted both monthly and quarterly, and staff turnover can be compared across demonstration and non-demonstration hospices on a quarterly basis. Monthly data can be grouped into quarterly or bi-monthly periods to reduce fluctuations due to monthly idiosyncracies (particularly likely in small organizations), but this reduces the number of data points. Changes in staff “burnout” based on attitude scales are assessed by comparisons of average scores in the first administration (September, 1981) and the second administration (September, 1982). Analyzing change in the mix of services delivered. Based on the premise that organizations act to maximize reimbursement, the following hypotheses arise: The number of’ sociul service and bereuvement visits will increase in demonstration hospices; these are not ordinarily Medicare-covered services. The average length qf nursing visits will be longer in demonstration hospices because new standard “hospice care visit” charges are available in the demonstration. Service mix hypotheses are examined using the staff log data base. All direct care visits (in an outpatient setting) are recorded and monthly or quarterly statistical summaries of relevant dependent variables (e.g. percentage of all direct care visits coded as bereavement or social service) are available. Given differences in staff composition, prevalence of the use of outside contractors and the volume of direct care visits conducted by hospice staff themselves, particular care will be needed in making comparisons across organizations. Most of the hospices contract for various services with other agencies. This is probably more prevalent among hospitalbased (HB) and freestanding (FREE) hospices than home health agencies. Consequently, service mix statistics generated on the basis of staff log data forms completed by only hospice staff do not tell the whole story. Comparisons will be based only on organizations having similar staffing configurations.
Analyses
qf hospice costs und,finunciul
stutus
This component of the Study addresses how reimbursement status of hospices. Stated as a hypothesis, it may be anticipated that:
is related
to the financial
Unit cost qf’services will be higher in demonstration than in non-demonstration hospices. Personnel costs will be higher in demonstration than in non-demonstration hospices. Overhead costs wlill be higher in demonstration than in non-demonstration hospices.
National
Hospice
Study
Analysis
Plan
769
Unit cost of services will be higher in demonstration hospices. Unit cost of services will be analyzed for a wide range of specific services. However, problems arise in interpreting site comparisons within principal service unit costs. Therefore, aggregate costs for the total number of services provided is the principal measure of unit cost. This measure, the cost per hour of home service, reflects differences in the hospice’s production function such as the mix of professionals delivering service as well as differences in wage levels and productivity. Since hours of services is the common denominator, differences in management style or philosophy (e.g. the proportion of all home service provided by R.N.‘s) are reflected in the cost. Additionally, this approach overcomes any interpretational differences across hospices as to what each given service means. The primary analysis focuses on comparing demonstration and non-demonstration hospice service costs. Subsequently, other potentially important variables are introduced in an effort to understand the observed relationships. Although it is expected that a number of variables can affect unit costs of service, those initially anticipated to be important are: size, age of the organization, level of utilization, case-mix, use of contracts and the presence of other hospices in the area. Personnel costs will be higher in demonstration hospices. Variation in personnel costs are examined from two perspectives: average salary by job category and the proportion of dollars spent for direct care personnel. Preliminary indications suggest that salaries paid by demonstration sites may be higher than those paid by non-demonstration sites due to three factors: (a) the desire to expand quickly; (b) the lack of cost restraint or ceilings imposed by the demonstration; and (c) the substitution of paid staff for volunteer staff. Both salaries and the total dollars spent on provider staff may be higher. However, the percentage of dollars spent on direct care personnel may be lower in demonstration sites than non-demonstration sites due to expansion of administrative costs. The variables to be used to examine these issues will be average salary by job category, total direct care personnel expenditures, and the ratio of direct care salary costs to administrative salary costs. The analyses using these data will be performed along the same lines as those mentioned for cost per unit of service. Overhead costs will be higher in demonstration hospices. In addition to administrative costs, overhead includes items such as building, maintenance, and transportation. The demonstration’s liberal reimbursement procedures may encourage expenditures in these areas. Qualitative
analyses
The central organizational
of change in organizational
set of interrelated change is:
structure
issues which are the basis for the qualitative
analysis
of
-The reimbursement system creates opportunity for growth. -Reimbursement leads to hospice organization formalization. -Increased formalization leads to goal diffusion. -Reimbursement leads to increased professionalization. These issues form a causal line of reasoning, predicated on sociological, organizational and economic theory. The long term implications of behavior among reimbursed hospices are crucial for making national cost projects and policy recommendations. The quantitative organizational analyses seek to determine whether an accelerated pattern of change occurs due to the introduction of a special reimbursement system. Qualitative aspects of organizational change and expansion can also be analyzed. For example, the number of contracts that a particular hospice has may represent a diffusion of responsibility and control. Changes in patterns of communication or service protocols as seen in new procedures manuals, restructured organizational charts and the frequency of meetings, represent a more formalized organizational structure. Measures of these changes are available from agency documents such as annual reports, organizational charts, contracts and procedures manuals. Qualitative indicators of change in the organization are also obtained via interviews with hospice administrators.
770
DAVID S. GREEK er 01.
These analyses compare change by hospice organizational type and across demonstration and non-demonstration settings. Freestanding hospices may adapt to the introduction of the demonstration differently than home health agency or hospital-based hospices. Since they often have a broader volunteer base and are younger, freestanding hospices must rely upon the community for resources. The resources necessary to the freestanding hospice include labor, revenue and prestige. Without the guaranteed revenues of the demonstration, freestanding hospices devote considerable effort to attaining legitimacy in the community and to attracting resources. The introduction of a reimbursement system may cause a shift away from this effort. The implications of such a shift in terms of board composition, emphasis on community relations and the focus on recruitment and training of volunteers could be considerable. Home health agency-based (HHA) hospices have provided home care services longer than the freestanding hospices. They are less reliant on community resources. The introduction of a specialized hospice unit within the HHA could result in interorganizational conflict. Daily nurse visit quotas, a management tool in HHA’s to contain costs, may not be instituted as rigorously for hospice staff. The introduction of volunteers will, in many cases, be a novel function for HHA staff. At the same time, strategies for dealing with physician providers developed by the HHA may be transferable to the hospice unit, thus minimizing a problem freestanding agencies are likely to confront. Hospital-based (HB) hospices may have different sets of organizational issues to control and resolve, depending upon the placement of the hospice unit within the hospital’s organizational structure. The placement of the unit may impact directly upon the ability of the hospice to galvanize resources and to function as an autonomous unit. The direct line of authority for an HB hospice unit may be to a vice-president for administration. Alternately, the organizational chart may place the hospice unit at the same departmental level as Nursing. Social Services, Laboratory Services, etc. The ramifications of both models may become apparent when conflicts arise over resource allocation or the applicability of various work standards and procedures. Hospices with designated inpatient beds must resolve a series of economic. staffing and philosophical problems to maintain a viable program that continues to reflect the hospice philosophy. Pressures to keep beds filled run counter to the value placed upon home-based care. Additionally, these hospices may have to cope with the phenomenon of undesirable patients from other units being “dumped” on the hospice. Intramural strains such as these may test the viability of hospice in a hospital base and the organizational considerations may be critical to the outcome.
Section VII-National
Projections
Tests of hypotheses in the patient and facility level analyses should indicate whether hospice care and the demonstration affect terminal care costs, utilization and the share of expenses paid by various payors. If the impact on cost or quality of life is positive, it is important to project the impact to the nation as a whole. From the government’s perspective, in the current fiscal climate, cost implications probably take first priority. Thus, the major research question that could be addressed in the national projection is: Whut are the net direct costs (or swings), in total and to the Medicare program, reimbursement ,for hospice cure to ull hospice programs:~
@extending
Hospice reimbursement paid by the government
in the costs
similar to the demonstration can lead to changes for terminally ill patients in several ways, through:
-Changes in participation rates (the percent of eligible individuals who choose hospice). -Changes in patterns of utilization of hospice and conventional care patients (substitution of home care for institutionalization, for example). -Changes in facility unit costs (due to utilization level changes or organizational response to cost based reimbursement. for example).
Changes in the rate of development that exist. The national
projections
771
Hospice Study Analysis Plan
National
of hospices
and/or
the types of hospice
programs
will create:
(1) A baseline projection that forecasts hospice utilization, costs and Medicare payments based on existing patterns of utilization, participation rates, unit costs and facility characteristics. (2) A series of policy option projections, which extend the demonstration reimbursement program to the nation under different assumptions, including changes in behavior of potential hospice patients and the hospices themselves. The study will identify certain variables that are potential policy instruments for altering this behavior and test the sensitivity of our forecasts by varying policy instruments and other parameters. The discussion that follows considers several types of forecasting models and indicates which may be most helpful. The model finally chosen, the classes of variables included and the sources of data for these variables depend upon the results of the patient-level economic analysis and upon a full review of these results in the context of relevant policy parameters. DATA
SOURCES
Much of the data for these forecasts will come from the patient cost analyses (Section IV). Supplemental analyses of secondary data will provide a basis for correcting and generalizing to the nation the net cost of hospice care. These additional data bases include: -National Center for Health Statistics -Medicare History File. -The Cost of Terminal Illness Study. -Supplementary wage, health resource
(NCHS)
and demographic
ANALYTIC Forecasting
Vital Statistics.
data.
STRATEGY
models
There are numerous set of procedures: (1) Develop socioeconomic (2) Construct totals forecasted (3) Multiply
forecasting
models
available,
all of which follow the same general
forecasts for certain variables, such as population totals by demographic, and epidemiological characteristics. predictors, which are ratios of some form that describe how the population in step 1 relate to the variables targetted for forecasting. the step 1 variables by the relevant predictors to obtain forecasts.
Distinctions among techniques appear in step 2. The predictor ratios may be constructed using techniques that range from simple fixed ratios to sophisticated parameter estimates. These include: Single equation least squares regressions. The coefficients in these models calculate the total direct and indirect effects of exogenous variable changes. Feedback processes are not specified. Purameters in complex interactive models. For example, systems dynamics models and input/output models: the coefficients in these systems are applied simultaneously and measure direct and indirect effects of exogenous variable changes. Feedback processes are built into parameter estimates. Single value,fixed ratios. For example, the supply of physicians in 1990 can be predicted with an estimate of the population in 1990 and an estimate of the physician to population ratio in 1990. The single equation least squares regression technique study. Although a large interactive model may be attractive
seems most applicable to this from an analytical standpoint,
112
DAVII) S. GKEER ?i (11.
it requires a range and volume of data difficult to obtain in this study. Many of the model’s coefficients would have to be based on results of other studies, or on the informed opinion of experts. It also is very resource intensive to develop. In a model with internal feedback, this melange of coefficients would be a source of concern, because it would reflect studies over disparate populations at different points in time. In an interactive model, the stability of the entire system depends critically on coefficient values. The increase in the descriptive power of such a model does not justify the resources necessary to ensure internal consistency and produce credible results. On the other hand, single-valued fixed ratio forecasts oversimplify the situation. Their reliability usually cannot be judged because their statistical properties are often unclear. Moreover, it is impossible to determine the extent to which other variables in the system contribute to effects supposedly measured by a given ratio. For example, a simple ratio of 1000 inpatient days to 100,000 persons over 65 may imply that an increase of 100 65-t persons will increase inpatient days by one. In fact, changes may be more closely related to other variables, such as bed availability. The study will have available estimated coefficients of regression equations from the patient level economic analyses. They relate socioeconomic and demographic characteristics of patients to utilization and costs. They have two important advantages over most fixed ratio estimates: (a) They are estimated statistically, from a well-defined population, and the errors associated with these estimates can be measured. (b) In a regression context, each single coefficient isolates an effect without measured effects controlled. Thus, a regression coefficient for patients aged 65 and above predicts utilization for this age group, holding constant other factors such as sex, race, socioeconomic status and other variables not related directly to the patient, such as the health resources of the region. The reliability of the entire estimated equation can also be determined. be subject to increasing margins of error the farther one goes from known It ‘3 important to the quality of the forecast that this error be estimable.
The ,jorecasting process Figure 3 depicts a general model that forecasts hospice care. The steps are described below:
the cost to Medicare
Forecasts may sample values.
of reimbursing
Step 1: Estimate the population at risk in the ,jorecast year. Initial and target year populations by age, sex, and race are estimated for each county. Initial baseline population forecasts are developed for market areas (defined as counties) of study hospices and other hospices in existence during the study period. Target year forecasts are based on census forecasts. Step 2: Forecast cancer mortality rutes af‘patients arailuhle,for hospice during the target years. Trends of recent cancer mortality rates (if appropriate, by age, sex, and race) are used to estimate the size of the terminally ill cancer population in the initial and target years. In order to accommodate mortality rates to the analysis method described in Step 5, mortality data are converted to monthly rates. Step 3: Estimate hospice participation rutesjor terminally ill cancer patients. Since it will be impossible to rely on statistical estimates of participation rates, we shall have to depend on informed judgement to proxy these parameters. At this step, counties with hospice programs currently in place will be identified. Step 4: Compute the number oj’hospice und conventional care patients ,jor the initial and forecast years. The Joint Commission on the Accreditation of Hospitals (JCAH) surveys of hospices should provide baseline data for estimating participation, when combined with area cancer mortality statistics. Step 5: Forecast the proportions qf’hospice und conventional cure patients in discrete time interrals preceding deuth in the initial and target years. The patient level analysis uses two
I , I -
forecasts
Step 1
Population
’ I I ’ ’
I
rates of
l
I
Step 2
hospice
for
available
patients
Cancer
mortality
I I x1
l I
i=& I I 1 I I
I
I
I
3
’ ’
patients
care
' tional
’
’
‘-x&J
Sted
-4
in
before
death
’
’
in
care
patients
tional
of conven-
before
I yr:;ye
,
time
interval
each
patients
of hospice
1 Proportions
1 I 1 I 1 I
I 1
I
I
1 1 I
1 = 1 1 1 I
FIG. 3. Forecasting system
I 1 hospice I participa-1 I tion
I
f
I
I
1
I x
I
'Hospice
I , patients
Hospice
I
1 i i
I I
’ I I
'x
Hospice
intervals
patient-
care
tional
Conven-
Intervals
p,atient-
for National
=
I I
I
care
tional
I
interval
I total ’ costs I per
I
I Conven-
t
Cost Projections
x
I
I
I 1 I
1 =
I =
I :::;I I I 1 per I interval I
1 Hospice
’
’
costs
care
' tional
I
I
1 i
' Conven- 1
1
’ costs
I Hospice'
x
x
I
tional
conven-
tion of
I 1 care I paid by I I Medicare I
l
I I
, ,
1
Medicare
1 Propor-
1 I
1 paid
by
hospice
tion of
Propor-
I costs
1 l 1 1 I
I
I
costs
care
tional
I conven-
T Medicare
costs
hospice
1
' Medicare
I
I
I=
I
’
'
I
5
a
m
$
z
114
DAVID S. GKEER et ul.
methodologies for costing hospice treatment; the first is based on total costs per case and the second is based on per case costs constructed from costs for weekly and biweekly intervals preceding death. Cost projections can similarly be made on a case or time interval basis. A decision on the appropriate methodology must await completion of statistical tests in the patient level analysis. Step 6; Compute “patient intervals” for hospice and conventional care patients in the initial and target years. This computation combines total cases estimated in Step 4 and the proportions in Step 5. Step 7: Estimate total cost by case or time interval ,for the average patient in each demographic/geographic group. Costs per time interval and per case are estimated in the patient level regressions. Costs for the target year are inflated from the initial year at an assumed rate of increase based on the recent experience of (and future forecasts of) the medical care component of the Consumer Price Index. Step 8: Compute total forecasted costs of treating terminally ill cancer patients in hospice and conventional cure progrums. This computation involves multiplying patient-weeks (or total cases) (Step 6) by the appropriate costs per interval (or per case) (Step 7) and summing for hospice and conventional care patients. At this stage, “costs” are defined as Medicare defines them, since this is the basis for the patient cost analysis. Appropriate adjustments must be made for costs (charges) not measured in discrete intervals (such as physician charges). Step 9: Estimate the proportion of hospice and conventional care costs of treating terminal cancer that is reimbursed by Medicare. The baseline Medicare reimbursement assumption will be that Medicare pays all hospice costs for Medicare-eligible patients, as it is doing in the demonstration. Thus the Medicare fraction of total hospice costs depends entirely on the proportion of Medicare to total patient intervals. For conventional care, Medicare reimbursement and non-Medicare costs are estimated from patient cost and the payor mix analyses. Step 10: Compute,forecasted Medicare reimbursement for terminally ill cancer patients in hospice and conventional care programs. This computation combines total treatment costs (Step 8) with the proportion of forecasted Medicare reimbursable costs (Step 9). Step 10 totals depend on the underlying assumptions used about demographic trends, costs, and federal policy. Total Medicare program costs in this simulation include both conventional care and hospice costs under specific assumptions used about hospice participation. The net costs (or saving) of a national hospice reimbursement program can be estimated by comparing simulated national hospice coverage program costs to an estimate of costs without full hospice coverage. This methodology can also be used to compute total costs and, with modification, is applicable to other cost parameters. METHODOLOGICAL
ISSUES
There are a number of questions that must be answered before the forecasting model is complete. Statistical analysis of the patient level costs and discussion of the results with other experts will determine the resolution of these issues What are the proper
assumptions
about a baseline forecast?
The methodology discussed above projects the cost implications of a nationwide hospice program. The baseline forecast assumes that the patient level model’s predictors remain unchanged. In essence, this means that hospice participation and market penetration rates will be developed in consultation with project advisors. Other factors such as eligibility criteria under the demonstration, utilization patterns and costs are assumed to remain the same. However, certain assumptions about characteristics of hospice programs in the forecast year must be made. Should we project the rate of hospice growth that prevailed before the waiver went into effect? Should we assume that regional differences in hospice market penetration and growth are perpetuated? Do we add any assumptions about
National
Hospice
Study
Analysis
Plan
775
hospice entry into areas that now have no hospices (virtually none)? The simplest assumption is that the capacity of existing hospice programs will expand to meet demand which will grow or contract as a consequence of changes in cancer death rates. Should “charges”
or “costs”
be forecasted?
The research issue here involves costs to the government of a national waiver program. We will study Medicare’s share by estimating payments, by source, relative to total charges in the patient economic analysis. One might argue that it is logical to project charges to the target year and then apply this estimated Medicare share ratio to the appropriate charge data. However, we argued previously in the patient cost discussion that multivariate estimates of utilization patterns, weighted by standard Medicare unit costs, are likely to be more precise than estimates of charges. Since neither the theory nor the data exists to explain variations in charges among facilities and services, projections should be constructed in terms of costs; any adjustments to the projections to secure Medicare costs should be done as a final step in the process. What are the important determinants of cost.7 The patient-level cost equations will estimate coefficients that link patient and PCP characteristics, a limited number of physicican characteristics, area health and socioeconomic profiles and, for hospices, facility characteristics to patterns of utilization and cost. The regression output will include standardized coefficients that, in general terms, indicate how important an individual coefficient is in determining variations in the dependent variable. The patient demographic characteristics may contribute most to a statistical explanation of cost and utilization. If this is true, the forecast should be based on projected demographic data in detail sufficient to make full use of the estimated coefficients. On the other hand, the analysis of hospice patients may reveal that facility characteristics are more important than patient characteristics. If this is the case, the model would be less well adapted to forecasting. Facility-level detail is available for hospices but not for conventional care programs. Without a statistical basis to judge the importance of facility-level variables in determining cost variation for conventional care patients, we must rely on the literature. In order to make full use of the available hospice facility information, we should first project the characteristics of hospice facilities in the forecast year. This task is more difficult than forecasting demographic characteristics of the poulation, in part because the dynamics of population change are better understood. Forecasts of unit costs for conventional care could be grafted onto the estimates made for conventional care utilization in this study. Should facility variables be important, our current position is that they should be taken into account both for hospice patients and for conventional care patients. In order to do this, predictors of facility characteristics’ effects on costs would be developed from other studies. Assumptions would then be made about the kinds of conventional care facilities patients would use. Characteristics of these facilities would be used to forecast unit costs in the target year. What are the important parameters?
policy
parameters,
and what
are reasonable
ranges for
these
We can test the sensitivity of forecasts by varying input values (size and composition of patient groups, for example) and assumed behavioral coefficients, such as participation rates. It is particularly important to consider the effects of changes in variables that can be shaped by government policy. These include: -Timing of intake into the hospice program. -Kinds of services covered by Medicare, for institutional). -Levels of cost sharing.
specific
settings
(home,
176
DAVIII S. GREER ef d.
Changes in assumptions about the nature of Medicare reimbursement will affect both the distribution of patients in hospice programs by length of participation and the mix of services these patients consume. If, for example, Medicare sets a limit on the number of days of hospice care it will finance, this could delay the timing of the decision to participate and shift the distribution toward short stays. If costs vary over intervals, such a shift wili affect total cost whether or not numbers of patients increase or decrease. If Medicare extends reimbursement to a wide range of home care services, total costs can change because patterns of utilization by service and setting might change. From another perspective, a general increase in Medicare benefits for home care may affect utilization of hospice and conventional care patients alike. Broader home care coverage may increase hospice participation, to the extent that some patients select hospice as a less costly way of getting home care. There is no meaningful way to model the effects of policy changes on participation, average days of participation, and patterns of utilization. Rather, we shall have to develop and precisely specify assumptions about these effects. Sensitivity analyses will be conducted to determine the consequence of the various assumptions. What is the appropriate jorecast period.? Choosing a target year, or years, depends both on the value of a particular choice to policy making and the reliability of the forecasting tool. Policy relevance is determined by agency planning horizons and the Federal budget cycle. Forecast accuracy can be improved if sample data allow estimates over a sufficient number of time intervals. The observations in this study are selected over a short, i.e.. 18-month, time frame. Although we shall try to isolate patterns of change by estimating equations with three time variables (based on six month cohorts of patient observations), we shall not have enough time services points to be confident about forecast accuracy several years into the future. Thus, we shall have to make qualitative statements about accuracy. based on generalized measures of the precision of our estimates. REFERENCES I.
2. 3. 4. 5. 6.
7.
8. 9. 10.
General Accounting Office: Hospice Care-A Growing Concept in the United States. Washington, DC: U.S. General Accounting Office, HKD-79-50, March 6. 1979 Joint Commission on the Accreditation of Hosoitals: JCAH Hospice Proiect Interim Reeort. Phase 1. _ Chicago, IL: Joint Commission on the Accredit&ion of Hospitals,-1981 ” National Hospice Organization: Locator Directory of Hospices in America, 1981-1982. McLean Virginia: National Hospice Organization. 1982 Buckingham RW, Lupu D: A comparative study of hospice services in the United States. Am J Pub1 Hlth, 12: 455463, 1982 National Hospice Organization: Standards of a Hospice Program of Care 6th revision. McLean, Virginia: National Hospice Organization, 1979 National Cancer Institute: A Cost Analysis of Three Programs, Hospice: Hillhaven Hospice, KaiserPermanent Hospice, Riverside Hospice. Executive Summary. Kaiser-Permanente Medical Care Program, Southern California Program, 198 I Mor V, Sherwood S, Birnbaum H, Morris JN, Greer DS: The National Hospice Study: A Description of Participating Hospices and the Patients They Serve. Providence. RI: Brown University (unpublished manuscript), 1982 Belsley DA, Kuh E, Welsch RE: Regression Diagnostics: Identifying Influential Data and Sources of Collinearity. New York: John Wiley, 1980 Draper N, Smith H: Applied Regression Analysis, 2nd edn. New York: John Wiley, 1981 Morris JN, Gutkin CE. Sherwood CC, Sherwood S: Overview of SIMRAN, procedures. In Alternative Paths to Long Term Care. Sherwood S. Morris JN. et crl. (Eds). Chapter 3 (Appendix). Final Report to AoA Grant #90-A-1666. 1982
Appendix A-Abridged Description of the Hospice Demonstration Progress for Eligible Medicare Patients What follows is a synthesis of the Demonstration Project Provider Manual and the relevant provider letters distributed to participating hospices by the Office of Direct Reimbursement of HCFA. This is not an official interpretation and is for the use of data collectors only.
National
Hospice
Study
Analysis
Plan
777
Iniroducrion
The Medicare demonstration project alters certain provisions and regulations of the Medicare insurance aspects of existing Medicare regulations on an program. It is a general practice for HCFA to “waive” experimental, demonstration basis, simultaneously studying the effects this has on patients (beneficiaries) and costs to the program. The hospice demonstration involves a complex set of inter-related “waivers” that can be grouped into three distinct classes: First, reimbursement is provided for new services (home respite, bereavement counseling and assessment, outpatient prescription drugs and biologicals, continuous care, and institutional respite services). Second, Medicare eligibility criteria are modified, a six-month terminal prognosis replacing the “essentially home-bound” criteria for inpatient skilled nursing care. Third, certain services delivered to the family or primary care taker of the Medicare/Medicaid beneficiary are covered; these include bereavement and respite services as well as counseling and education to facilitate care of the patient. Medicare beneficiaries are eligible for these waivers if they have both Part A & B coverage, have been certified by a physician as having a life expectancy of 6 months or less and sign informed consent. Covered under the demonstration are billable outpatient, home delivered and inpatient services provided by participating agencies conforming to specific cost reporting requirements. For a service to be billable it must meet the service definitions in the Provider Manual and have a cost associated with it (i.e. provided by paid staff). No billed physician services are covered under the demonstration; however, physicians may bill under the regular Medicare program. That is. receipt of services from a demonstration hospice does not preclude the patient from receiving other Medicare covered services under the regular program (e.g. physician visits, acute hospitalization, skilled nursing facility and outpatient clinic). What follows is an enumeration of the services available under the demonstration and the current caps or conditions for reimbursement, In-home
service
(I) Nursing includes providing skilled care, teaching patient/PCP health treatments and providing counseling. limits: I5 visits or 40 hr/month unless accompanied by justified documentation. (2) Home heulrh aide includes provision of personal care and/or household cleaning. limits: 8 hr/day or 100 hrimonth unless justifying documentation. (3) Homemaker service-assistance in personal care, etc. limits: 8 hriday or 100 hr/month unless justifying documentation. (4) Continuous cure-nursing, health aides, or homemaker services around the clock. limits: 120 hrimonth unless documentation; maximum of 5-day limit regardless. (5) Physical lherupy provided by licensed therapist under MD orders. (6) Speech rhrrup) provided by licensed therapist under MD orders. (7) Occupational therupy provided by licensed therapist under MD orders. (8) Sociul sercices provided by or under supervision of an MSW. (9) Nutritiona/ seroices!‘consultation provided by dietitian either through patient visit or in consultation to the
Hospice Interdisciplinary Team. (IO) Bereucrmenf usse.wment counseling provided by “a bereavement team member trained to recognize symptoms” as determined by the Hospice Interdisciplinary Team. limits: reimbursement for only 3 visits; no group counseling or bereavement visits by volunteers are reimbursed. (I 1) Prescription drugs and biologic& are reimbursed according to Medicaid cost limits; excludes nutritional supplements and over-the-counter drugs, creams, etc. (I 2) Durable medical eyuipment includes all regularly Medicare covered DME plus certain safety and self-help devices. (I 3) Medical supplies-regular Medicare covered supplies. (14) Home respire-provision of services to patient when PCP is unable to provide normal care and supervision on a temporary basis. limits: 72 hr/episode. Inpatienl
sercices
(I) Inpatient hospice. Short term inpatient hospice care in a designated hospice unit or in a hospital section in which hospice-specific costs can be isolated. (2) Institutional respite sewice. Care provided patient to relieve PCP on a short term basis in a certified SNF, ICF, or inpatient hospice. Note: Some hospices have contracts with SNF and ICF homes to provide this care which is billed through the hospice demonstration. In addition to the specific definitions and limits for billable services, there are provisions covering the nature of allowable administrative, or overhead, costs allowable under the demonstration. These include patient expenses, pharmacy consultation, psychologist/psychiatrist consultation as well as the Hospice Interdisciplinary Team (in which the hospice physician generally participates). Demonstration hospices receive coverage of the cost of billable visits to demonstration patients. The proportion of the overhead or administrative component of the unit cost of each billable service that is reimbursed under the demonstration is related to the ratio of demonstration to non-demonstration hospice patients served. Hospices submit patient specific bills to HCFAjODR for services provided to demonstration patients. However, they are paid via period interim payments (PIP) which are based on quarterly cost reports and utilization statistics. The PIP level will change as a function of fluctuation in service volume and the proportion of all services provided to demonstration patients. The bills also serve to monitor the hospice’s compliance with specific service limits. Final reimbursement, or settlement, is determined on a retrospective basis for reasonable costs incurred based on year end cost reports which will be audited by the area Medicare fiscal intermediary.
DAVID S. GREER et ul.
778
Appendix B-National
Hospice Study Data Sources
Both primary and secondary data sources are used in the various analyses being conducted as part of the National Hospice Study. These data correspond to patient-level analyses, facility-level analyses and national projections, The various levels of data are analytically inter-related as described in relevant sections of the analysis plan. This appendix contains brief descriptions of each data source and stipulates its mode of administration if it is a primary data source. Patienl
data sourc~.~
What follows is a description of each data form relevant to the patient-level analyses of impact on quality of life and health care costs as well as the comparisons of the terminal care intervention to which hospice and non-hospice patients are exposed. The measures contained in each data form are used as either independent or dependent variables in these analyses. (See Fig 3 for a graphic display of the data gathering flow). Mediwl record ahstruct. A one-page review of medical status is used to document primary site. histological diagnosis and the presence of metastases. Also captured are past therapies, date of initial diagnosis and other medical conditions. Patirn/ inrake and discharge fbrms. These are available from existing hospice records or are completed by the data collector as a part of the initial interview battery in both hospice and conventional care settings. In addition to documenting the data of Study entry and termination (death), these records contain basic demographic data and measures describing patients’ functional status on admission. Initial patient intewiew /iwm. This is a structured guideline for a personal interview. It contains the patient quality of life dependent measures as well as some of the patient independent variables. In order to reduce the patient response burden, many of the independent variables are incorporated into the initial PCP interview. In the event that the patient cannot respond to the interview. selected items are obtained from the PCP. Initial PCP interrietv f&w. A guideline for the patient’s principal care person. It includes independent variables concerning the helping network, the existence of other obligations of the PCP and demographic characteristics of the PCP. In addition, information concerning the patient’s knowledge of his/her disease and prognosis and baseline data on family quality of life are obtained. PCP Assrs.w~enf. A paper and pencil questionnaire completed at the initial and each subsequent visit. In it the PCP assesses the patient’s quality of life, the use of medical and psychosocial services. patient symptoms. the level of informal support provided and the amount of time the PCP lost from work. Patient ,fb//o+v-up intervie+t.. This interview is repeated at each follow-up session until the patient’s death. It includes the dependent variables encompassed in the initial patient interview. PCP fi&n-up interview. This brief interview is conducted at the time of the second patient follow-up visit. It contains the principal dependent measures for the family quality of life analysis. Medication prrscriptmn and ufilizarion /arm. In addition to prescribed dosage, the actual amount of medication consumed in the previous 24-hr period is dctermincd. The data collector checks the containers of all medications and ascertains utilizations of those medications of interest in the Study. PCP hrrearement interview. This interview takes place 9@lOO days after the patient’s death. It contains the same set of dependent variables as the PCP follow-up interview, in addition to sets of questions concerning the grief experience. Patient
cost. paJwent,
and i~f&mal
support
datu
The principal source of patient cost and utilization information are weekly service records and checked against bills and records for completeness by the data collector.
maintained
by PCP’s
(I) A Service Record is maintained by each PCP. This instrument records inpatient hospital and nursing home days, physician visits, outpatient visits, home care visits (and hours for certain providers), visits from volunteer agencies. expenditures on drugs and supplies and total out-of-pocket treatment expenditures for the week. (2) After the patient‘s death. the data collector transfers Service Record information to summary forms after verifying it with bills, receipts. vouchers and, where pertinent, hospice records. Summary Inpa/ienr
forms,
constructed
charge
from Service
Record
information,
include:
summtrries.
(One for each hospital or inpatient nursing home stay), includes utilization reimbursed services and utilization/charge information for non-Medicare services. Outpatienr, physician, home care summaries. These allocate all utilization to the last week of the patient’s life and preceding bi-weekly periods. Our-q/-pocket c~pmse, drug, und supply summaries. The record expenses by week and for the Study period. Vo/un/eer .summay. This records visits and hours from community volunteers.
information
for Medicare
(a) Additional information on informal support, insurance coverage and utilization the PCP Initial Interriett, and the Patient Intake Forms. (b) These primary data are supplemented by Medicare infbrmufion on Medicare
MEDICARE Demonstration
CLAIMS
DATA
FOR
MEDICARE
prior to intake comes from reimbursed
services.
PATIENTS
c1rtim.s
Data on claims for services provided under the demonstration are obtained from Office of Direct Reimbursement (ODR) bill files. These contain information on utilization of services and charges for equipment, supplies and drugs.
National Regulur
Medicare
Hospice
Study
Analysis
Plan
179
claims
Data on (regular) Medicare services are obtained from two sources. Inpatient stay and home health service information is drawn from the Bill History file for the follow-up sample and a supplemental sample of conventional care patients. Copies of Provider Claims for Medical and Other Health Services (SSA-1483) and for Services by Physicians (SSA- 1554) are made as claims of follow-up sample patients are processed by the Office of Research, Demonstration and Statistics. Subsequently, they are sent on magnetic tape to the project for inclusion into the overall data base. The physician suraey. A short telephone interview is conducted with a sample of the physicians indicated in the record as primarily responsible for the patient’s medical care. It solicits attitudinal information regarding narcotic use and treatment for the terminally ill and demographic data on the physicians themselves.
FACILITY Facility-level organizational, Aggregated
data can be separated and (d) hscal.
patient
into
DATA four
basic
SOURCE types:
(I)
aggregated
patient
data,
(b) staff,
(c)
duiu
to both demonstration and non-demonstration hospices, a standard Intake and is completed and incorporated into the data base system. These records describe the overall hospice patient population in terms of basic demographics, income and functional status. At the facility level, they are aggregated to describe the monthly (quarterly) admission cohort of each hospice. For all patients
Discharge
Summarv
admitted Form
Hospice SlqfJ‘ Atfitude QuestionnaireA questionnaire is completed by staff (salaried and volunteer) at both demonstration and non-demonstration hospices at the beginning and end of the evaluation period. Provider Log. The Provider Log is a time sheet for hospice employees. It is completed monthly by all paid staff. The form provides a record of: (1) services rendered and tasks performed for outpatient cases; (2) total time devoted to inpatient cases; (3) time devoted to patient-related administrative activities; and (4) general administrative activities. Hospice Volunteer Statistics. In both demonstration and non-demonstration sites. evaluation staff gather information each month on volunteer staff use. The data include: the number of active volunteers, the number of patient visits made by volunteers. hours of patient care and hours of non-patient care provided by volunteers. St@ Salary und Turnover Records. This form is completed quarterly for demonstration and non-demonstration hospices. It records the average salary for five different categories of paid staff, the number of new staff hired. and staff resignations by category for each period. Organixtionul Hospice
datu
Charactrri.rtic.s
Form. This form summarizes certain data describing the structural characteristics of the hospice organization. e.g. ownership, hospice type, prior patient census data, community population served. services and programs provided. staff service mix, eligibility and discharge criteria, referral information, and contractual agreements. &.xecufive Director Interview. This instrument is a guide for the interviewer (Regional Manager) in obtaining qualitative information from the executive directors of both demonstration and non-demonstration hospices. It supplements quantitative information and information available in hospice documents (e.g. organizational charts, by-laws and procedures manuals, copies of incorporation papers, etc.). It addresses the history and background of the hospice, community involvement. etc. Three such qualitatively-oriented discussions occur and serve to place the quantitative information in context.
Fiscul data Hospice Demonstrution Stutement of Reimbursable Costs. The Hospice Demonstration Statement of Reimbursable Costs is a requirement of the demonstration and is completed by all demonstration hospices. It has all the detail of standard Medicare Cost Reports including: total cost, overhead costs, contract costs and unit cost for each service offered by the hospice. Data acquired from non-demonstration hospices are comparable. The Hospice Statement of Reimbursable Costs is simulated on the basis of summary service statistics maintained by the hospice or compiled from staff time sheets collected by on-site evaluation staff. serve as a means of documenting the non-demonstration Worksheets entitled “Composition of Expenses” hospice costs based upon existing records such as budgets or Medicare Cost Reports. The data on these forms are examined and reclassified by evaluation staff accountants into the appropriate categories based on the Medicare Hospice Demonstration requirements such that the cost data of demonstration and non-demonstration sites are comparable. The basis for the classification of services and costs are: Hospice Srutisrics. Data coordinators in non-demonstration sites assemble records on service utilization by service category. The source of these data are weekly time sheets completed by hospice staff either specifically for the evaluation or the existing record system. Stu/ement of Reoenue and Expenses. This statement of all sources of income and total expenditures of both demonstration and non-demonstration hospices is based upon generally accepted accounting procedures. In demonstration sites, cost data are completed automatically as part of the hospices’ participation in the demonstration.
780
DAVID S. GREEK et al.
To minimize the burden of data collection in non-demonstration simulated cost report. Non-demonstration sites assemble the budgetary the worksheets.
SECONDARY
DATA
hospices, evaluation staff and financial data needed
prepare the to complete
SOURCES
Much of the data for these forecasts will come from the previously discussed IV). Supplemental analyses of secondary data will provide a basis for correcting the net cost of hospice care. These additional data bases include:
patient cost analyses (Section and generalizing to the nation
-National Center for Health Statistics (NCHS) Vital Statistics. -Medicare History File. -The Cost of Terminal Illness Study. -Supplementary wage, health resource, and demographic data. NCHS
Vital StaMics
The National Center for Health Statistics Division of Vital Statistics regularly causes of death (four digit ICDA code) by geographic region and demographic be the main vehicle for projecting the number of terminal cancer patients to the mortality will be examined to develop, as necessary, adjustments to historical Medicare
History
prepares mortality tables of the characteristics. These data will nation. Recent trends in cancer data for future projections.
File
The Medicare History File, maintained by HCFA, contains a combined record of all Medicare activity for a 5”/, sample of Medicare patients. The Medicare History File is used to develop regional indices of costs and utilization for Medicare services. Cosr of Terminal
Illness Stu&
This data base, available through the Blue Cross and Blue Shield Associations, presents the health care costs incurred by terminal patients under age 65 during their last 6 months of life. It includes claims files from three areas-Michigan, Indiana and Atlanta, Georgia-and captures all institutional and physician services billed for subscribers between 1 January 1978 and 31 December 1979. Together with the supplemental study of the cost of terminal cancer covering Rhode Island deaths in 1980 and 1981. these data constitute a unique validation resource. The JCAH
National
Surt~e~ sf Hospices
The Joint Commission on Accreditation of Hospitals (JCAH) is conducting a survey of some 1000 organizations during 1982 regarding their hospice activities, staff, patient mix and volume. These data will be used to extrapolate the facility-level analyses and to ascertain the patient participation rate.
OTHER The U.S. Census routinely publishes population available. The Area Resource File provides data health status characteristics.
DATA
SOURCES
data forecasts. Those based upon the 1980 census should be on area socioeconomic, demographic, health resource. and
II.
pp. 737-780.
1983
0021.9681183 S3.oO+O.W
Printed in Great Britain. All rights reserved
NATIONAL
Copyright
HOSPICE
STUDY
ANALYSIS
c’ 1983 Pergamon Press Ltd
PLAN*
DAVID S. GREER’, VINCENT MoR’, SYLVIA SHERWOOD~,JOHN N. MORRIS~ and HOWARD
BIRNBAUM’
‘Principal Investigator, National Hospice Study; Dean of Medicine, Professor of Community Health, Brown University, *Assistant Professor, Section of Community Health, Brown University and Project Director of the National Hospice Study, 3Director, Department of Social Gerontological Research, Hebrew Rehabilitation Center for Aged, Boston; Clinical Professor (Research), Brown University, 4Associate Director, Department of Social Gerontological Research, Hebrew Rehabilitation Center for Aged, Boston and ‘Associate Director, Division of Health Studies Section, Abt Associates, Inc., Cambridge, MA; Clinical Assistant Professor (Research), Brown University, Providence, RI 02912, U.S.A. 10 October 1982)
(Receioed
Contents Section
I
David S. Greer, Vincent Mor, Sylvia Sherwood and Howard Birnbaum Se&on
of hospice
752
Methodology for determining the impact on patient/family quality of life
of hospice
758
Determining costs
763
Comparisons of the patients receive
765
Organizational
770
National
projections
the impact
of hospice
on health
care
intervention
terminal
cancer
VI
Vincent Mor, Bruce R. Foulke and Howard Birnbaum Section
for determining the impact and their families
V
Vincent Mor and David S. Greer Section
Methodology on patients
IV
Howard Birnbaum and David Kidder Section
747
and Overview
III
John N. Morris and Sylvia Sherwood Section
Introduction
II
Vincent Mor, Howard Birnbaum, John N. Morris, David S. Greer, and Sylvia Sherwood Section
738
and
facility
cost analyses
VII
Howard Birnbaum David Kidder
and
Appendix
A
776
Abridged program
description for eligible
Appendix
B
778
National
Hospice
*Supported in part by the National Hospice Study grants from the Robert Wood Johnson Foundation
of the hospice demonstration Medicare patients
Study
data
sources
funded by DHHS/HCFA Grant No. 99-P-97793/1-0 and the John A. Hartford Foundation. 737
and
DAVID S. GKEERet ul
738
Abstract-Since the founding of the first hospice in the United States in 1974, the number of health care organizations providing hospice services has grown rapidly. In 1978, the U.S. General Accounting Office identitied 59 operational hospices [l]. A survey undertaken by the National Hospice Organization (NHO) in 1980 found 235 operational programs and many more actively planning to deliver services. By the summer of 1981. the Joint Commission on the Accreditation of Hospitals (JCAH), in studying the feasibility of a voluntary hospice accreditation program, had 650 responses to a national survey [2]. Finally, the 1981 NH0 directory identifies 464 operational “provider programs” as well as 33 functioning state-level hospice organizations with an additional 353 programs in various stages of establishing hospice programs of care [3]. The growth of the movement and the public recognition it has received have catalyzed advocacy of Federal support for hospice services. In 1979, the Congress responded by mandating a study to delineate the implications of inclusion of hospice services in the Medicare program. The Health Care Financing Administration (HCFA) then selected 26 hospices (from an applicant pool of 233) to participate in a two-year expertmental program. These demonstration sites receive reimbursement for services provided Medicare beneficiaries not otherwise avatlable under current regulations. The special reimbursement provisions went into effect on October 1, 1980. (See Appendix A: Description of the Hospice Reimbursement Program.) In the spring of 1980, the Robert Wood Johnson Foundation and the John A. Hartford Foundation Joined with the Health Care Financing Administration (HCFA) to solicit proposals for a national evaluation of hospice care as a basis for future Federal fiscal policy and legislation. Brown University was selected as the evaluation center by competitive process and the grant was awarded on September 30. 1980. The evaluation employs a quasi-experrmental design in whtch the impact of hospice care (with and without reimbursement) on yuulir,, of I!fr and cos1.5 are compared to non-hospice (conventional) terminal care. Eight hundred patients and families in 24 comparison sites located in three regional areas (Southern New England, Northern Midwest and Southern California) are expected to participate. Primary data collection began on August I. 1981. Analyses of differential outcome are performed using standard linear multiple regression and logistic multiple regression with separate models for each comparison group. Effects are tested by separately estimating the specific response variable for the prototype (average) hospice patient for each model.
Section I-Introduction
and Overview
HOSPICE can be conceived of as a repertoire of services based on a humanistic philosophy of care for terminally ill patients and their families. The implementation of the hospice concept is highly diverse [ 1,471. This diversity is expressed in the institutional affiliations hospice programs have, the range of services provided directly or under contract and in the eligibility criteria utilized [7,4]. Despite this diversity, there are commonalities among the organizations that call themselves hospices. In this section, we briefly describe the hospice philosophy, its programmatic elements, and their conceptual relationship to the outcomes examined in this study. The National Hospice Organization’s 1979 “Standards of a Hospice Program of Care” [5] states the hospice philosophy:
“Hospice affirms life. Hospice exists to provide support and care for persons in the last phases of incurable disease so that they might live as fully and comfortably as possible. Hospice recognizes dytng as a normal process whether or not resulting from disease. Hosptce neither hastens nor postpones death. Hospice exists in the hope and belief that. through appropriate care and the premonition of a caring community sensitive to their needs, patients and families may be free to attain a degree of mental and spiritual preparation for death that is satisfactory to them.”
The hospice
philosophy
includes
the following:
(1) Patient and family know of the terminal condition. (2) Further medical treatment and intervention are indicated only on a supportive basis. (3) Pain control should be available to patients as needed to prevent rather than ameliorate pain. (4) Interdisciplinary teamwork is essential in caring for patient and family. (5) Family members and friends should be active in providing support during the death and bereavement process. (6) Trained volunteers should provide additional support as needed.
National
The following
provisions
Hospice
Study
are characteristic
Analysis
739
Plan
of hospice
programs:
(a) Health care and services are provided to terminally ill. (b) The patient,,famil_y, and other persons essential to the patient’s care comprise the unit of care. The “hospice patient ‘s,family ” refers to the patient’s immediate relatives; individuals with signt$cant personal ties may be designated as the patient’s “family” by mutual agreement among the patient, the individual, and the hospice organization. (c) Inpatient and home care services are closely integrated to ensure continuity and coordination of care. (d) Care is available 7 days a week, 24 hours a day. (e) Care is planned and provided by a medically supervised interdisciplinary team composed of several individuals with appropriate skills. The team members work together to plan and provide services that will secure the physical, emotional and spiritual welfare of the patient and his/her family. (f) Palliative and supportive cure is directed at allaying the physical and emotional discomfort associated with terminal illness. (g) Bereavement services are provided which may include follow-up visits and supports of the family after the patient dies. (h) An education program is available which has two components: (i) Educating dying. (ii) Teaching (i) Volunteers
the patient, the family
family
and inter-disciplinary
to care for the patient
play an important
team concerning
death
and
in the home.
role in the provision
of care (NHO,
1979).
Implementation of this philosophy by hospices should result in a substantial alteration in the pattern of health care provided to the terminally ill and their families. Changes in the pattern of care which should emerge as a function of the hospice program may be categorized as follows: Locus of cure: in the patient’s home and/or designated hospice beds rather than in hospital and/or nursing homes. Providers of Care: family and/or volunteers rather than health care professionals. Orientation of cure: palliative, preventive, supportive and less resource-intensive than conventional care. These changes in process should improve outcome in both patients if hospice care is superior to conventional care. Postulated changes quality of care are depicted in Fig. 1. The major research questions derived from this conceptual framework. CHANGES
CHANGES
IN PROCESS
and their families in both costs and of this Study are
IN OUTCOME
OF CARE
cost
Quality
LOCUS
of care
4
,.I", K rlu~~~r-basedcare
Providers
HOSPICE PROGRAM
of care
Substitutes home care for hospital-
I I I
__)1
More "informal", volunteer help and support
1 1 ,
\
I
ization
Substitutes nonpaid family and friends for professional and hospital personnel
I ’ 1 I I ( 1
Patient remains in familiar atmosphere with family with social contact and less anxiety and fear
more
Patients cared for by family with more intimacy will be more satisfied with care
’
t Orientation
of care
-
More preventive, palliative, non-curative care
FIG. I. Causal
model
of Hospice
1
Substitutes
less
costly palliative for more costly aggressive care
Intervention
System
’ I ,
With
preventive and palliative patients' pain and other symptoms will be better controlled
care,
I
and its effect on patient
outcome.
DAVID S. GREER rt ul
740
RESEARCH
The major
research
questions
QUESTIONS
pertaining
to the Study
are:
(1) What is the differential impact of hospice, demonstration or non-demonstration, on the quality of life of terminal patients and their families, as compared to “conventional” or “customary” care? (2) What are the differential costs of caring for comparable terminally ill patients in demonstration hospices, non-demonstration hospices and customary care settings? (3) What are the differences in the services which hospice and non-hospice patients receive? (4) What is the likely impact of Medicare reimbursement on the organizational structure, staffing pattern and costs of hospices? (5) What are the likely national cost implications of reimbursed hospice care? OVERVIEW
OF
THE
STUDY
COMPONENTS
The Study consists of several separate but related analyses corresponding to the five major research questions. The specific research questions being examined in each Study component are described below. IMPACT
These analyses
ON
address
PATIENT/FAMILY
the following
QUALITY
OF
LIFE
questions:
(1) What is the impact of hospice, under reimbursed and non-reimbursed conditions, on the quality of life of patients and their satisfaction with the care they receive? (2) What is the impact of hospice, under reimbursed and non-reimbursed conditions, on the satisfaction with care of patients’ families and the prevalence of family problems and grief before and after the patient’s death? (3) What is the impact of hospice organizational structure on the outcomes experienced by patients and families served? Quality of life is a multi-dimensional construct which is conceptualized as a positive mood state, the absence of physical and psychological distress, and positive interpersonal relations. Based on these concepts, a series of measurable domains of patient quality of life pertinent to terminal cancer patients has been identified. These are: -Pain and other symptoms. -Functional status and mobility. -Quality of social interactions. -Satisfaction with life. -Sense of isolation and burden on others. -Satisfaction with care received. With respect to the family, hospice can mitigate grief reaction and decrease social and physical morbidity through the provision of training, education and counseling while the patient is alive and subsequently through bereavement, assessment, and counseling. If families have been educated and supported, the psychological trauma associated with death may be reduced. From this perspective, the outcome areas being assessed are: -Indicators of family secondary morbidity (psycho-social functional symptoms). -Family satisfaction with care received. -Subjectively reported grief reaction (see Section III). IMPACT
These analyses
ON
FAMILY/PATIENT
address
(1) What is the impact non-reimbursed conditions
the following
COSTS
research
OF
distress,
TERMINAL
role loss, and
dys-
ILLNESS
questions:
of the hospice service and care model under reimbursed on the cost of caring for terminally ill patients?
and
National
Hospice
Study
Analysis
Plan
741
(2) What is the impact of the hospice service and care model under reimbursed and non-reimbursed conditions on the sources of payment for services used by patients during the terminal phase of their illness? (3) What is the impact of the hospice service and care model under reimbursed and non-reimbursed conditions on the level of informal support provided terminally ill patients? The patient/family economic analyses address costs, or resource commitments, for treating hospice and non-hospice cancer patients separately from examining the burden of paying for care as shared among payors. The cost analysis
includes:
“Costs” of those services for which standard techniques of computing cost exist are compared for hospice and non-hospice patients. These techniques will be applied to inpatient hospital stays, outpatient visits, nursing home stays, and home care visits. Charges for services for which standard costing techniques are not available are compared separately. These include physicians’ services, drugs, supplies and other expenses. Hours of informal support provided hospice and non-hospice patients are compared without imputing monetary costs to such donated services. The payor burden analysis is based upon billed or billable charges. The percentage of billed and “billable” charges paid by the patient, by Medicare, and by other third-party payors is compared for demonstration and non-demonstration hospice patients as well as conventional care patients (see Section IV).
DOCUMENTING
THE INTERVENTION PATIENTS RECEIVE
WHICH
TERMINAL
This component of the patient/family level study examines differences in the service interventions to which hospice and non-hospice patients are exposed during their final months of life. The analysis addresses the following questions: (1) What is the impact of hospice on the mix of health-related and psycho-social services received by terminally ill patients? (2) What is the impact of hospice on the level of analgesics and tranquilizing prescribed for and consumed by terminally ill patients?
support agents
The likelihood of receiving an array of psycho-social support services, medical treatments and diagnostic procedures is compared across hospice and non-hospice patients. Given the saliency of pain control to the hospice concept, the level of prescribed and consumed analgesic and tranquilizer medications in the last weeks of life is specifically compared in the two groups (see Section V). ORGANIZATIONAL
AND
FACILITY
COST
ANALYSIS
The impact of reimbursement on hospices as organizations is examined by comparing demonstration and non-demonstration hospices on such variables as staff mix, volume of patients served, length of stay, the unit cost of services provided, allocation of staff time, and administrative procedures (see Section VI). The analyses address the following research questions: (1) What is the impact of reimbursing hospices on the unit cost of hospice services? (2) What is the impact of reimbursing hospices on the staffing pattern and service mix of hospices? (3) What is the impact of reimbursing hospices on the mix of patients served and their length of stay? (4) What changes in hospice organizational structure and service goals are associated with reimbursement?
142
DAVID S. GREER et
National
al.
cost estimates
National estimates of the net financial cost or savings associated with hospice care will be developed; i.e. the cost of hospice care minus the cost of the alternative conventional care which would be provided in lieu of hospice care. Two types of national estimates are anticipated: (1) baseline national estimates; and (2) policy alternative national estimates. The baseline national estimates involve extrapolation of the net cost of hospice care from the sites under study to the nation. The policy alternative estimates could be developed for the nation under a range of reimbursement policies for which the evaluation has empirical information. -Medicare coverage of hospice care (relatively complete coverage as under the demonstration vs existing coverage under current Medicare programs); -Different organizational modes of hospice care receiving third-party reimbursement (e.g. hospital-based, home health agency and freestanding); -Various types and amounts of services receiving third-party reimbursement; and -Variable allowable enrollment time for hospice care; i.e. how long a patient is expected to live. Both the baseline and policy alternative estimates could address the current time period since future patient and provider behavior and market-place patterns are likely to change. In developing these estimates, the Study could consider: (1) net total national health care costs; (2) net Medicare programmatic costs; and (3) the net cost to other third parties, including both out-of-pocket, patient/family costs, and costs to private third-party payors (see Section VII). Study sites Hospices can be classified into three types: (a) Hospital-based; (b) Home health agency-based; (c) Freestanding. Hospital-based hospices have inpatient facilities by definition; these may be sequestered and/or specifically designated or may merely be available within the hospital as needed. Freestanding hospices may or may not have an inpatient facility. Home health agencybased hospices are affiliated with existing home care agencies. Demonstration
hospices
In selecting the 26 demonstration HCFA used the following criteria: (a) (b) (c) (d) (e)
sites from
among
the 233 applicant
organizations,
Comprehensiveness of the hospice intervention. Soundness and thoroughness of the service plan in the proposal. Operational at time of review. Sufficient distribution of major hospice types. Representation in each of the DHHS Federal regions.
Proposals were submitted in September of 1979 and successful applicants were notified of award within three months. The hospices are located in 16 different states. Eleven are hospital-based; 7 are home health agency-based and 8 are freestanding. Two of the freestanding hospices have inpatient facilities. Non -demonstration
hospices
The non-demonstration used for selection were:
hospices
were selected by the project
(a) Representative of major hospice types. (b) Reasonable proximity to the project’s regional
investigators.
management
centers.
The criteria
Hospice
National
(c) Similarity (d) Adequate
to demonstration hospices. admissions rate and patient
Eight of the non-demonstration agency-based and 4 are freestanding, noted that 11 of the 26 demonstration “Customary”
Study
Analysis Plan
743
census.
hospices are hospital-based; 2 are home health none of which has inpatient facilities. It should be hospices are located in the same regions.
cure
“Customary” or “conventional” of provider as follows:
care can be classified
(a) University medical center care, supervised (b) Community-based oncological care.
by site of delivery
by academic
oncologists;
and/or
type
and
care usually involves multiple programs and sites and, often, several “Customary” physicians. In most areas of the country, terminal cancer care is directed by oncologists, either as attending physicians or consultants. Customary care sites were selected using the following criteria: (i) Appropriate representation of major categories (above). (ii) Ease of access to patients (e.g. cancer registry or center). (iii) Conditions conducive to follow-up (e.g. integrated records). (iv) Willingness of key providers to participate. (v) Proximity to regional management centers. Patient
samples
There are three distinct, for use in the Study:
but overlapping,
patient
samples
for which data are gathered
-The census of all patients admitted to demonstration (D) or non-demonstration (ND) hospices during the months of ongoing data collection. -All Medicare patients served in D sites during the months of ongoing data collection. -Patient/family units from the D, ND and conventional care (CC) sites who consent to be part of an intensive data collection effort entailing regularfoffow-up visits by field staff and the tracking of medical care costs and utilization. This group is drawn from those patients with a biopsy-confirmed diagnosis of cancer. Table type and Table the two
1 summarizes the number of demonstration and non-demonstration hospices by the estimated number of patients in the census and detailed follow-up samples. 2 summarizes the number of patients in the follow-up sample to be drawn from classes of conventional care settings.
PATIENT Three patients
SAMPLE
strategies are employed to ensure that conventional are similar to patients sampled in hospices:
-Controlled patient selection procedures. -Ex post ,facto exclusion of non-comparable -Statistical control procedures. The first of these is discussed Patient
SELECTION
below.
patient
The others
care
follow-up
sample
types.
are described
in Section
II.
selection procedures
All patients
in the Study
must
have documented
(1) Cancer confirmed by tissue diagnosis. (2) Remote or extensive metastases, except suffices. CD3h:lI ”
evidence
for lung cancer
of:
where regional
metastasis
DAVID S. GREEK et
144
al.
TABLE I. ESTIMATEDSAMPLESIZESBY HOSPICETYPE
Demonstration
Hospice type Free standing
Hospitalbased
Home health agency
Bed status
Facilities (N)
hospices
Non-demonstration
Estimated no. of census
Patients in follow-up sample (N)
Facilities (N)
hospices
Estimated no. of census
Patients in follow-up sample (N)
None designated Designated beds
6
I500
550
4
220
50
2
700
150
0
0
0
Designated beds None designated
9
1000
400
6
800
I50
2
200
75
2
130
50
None designated
7
I800
500
2
415
50
26
5200
1675
I4
1565
300
Total
TABLE 2. CONVENTIONALCAKE SITES
(N)
Patients in follow-up sample (N)
4 8 I2
I50 250 400
Facilities University Medical Center Community-Based Oncological
Care Total
(3) Karnofsky functional/medical status score of 50 or less; i.e. in need of some personal care assistance (applies to conventional care patients only). (4) A principal care person (PCP). (All patients permanently residing in a long-term care facility are excluded.) (5) Age more than 2 1. An admission criterion for patients in most hospices is a physician’s determination that the patient is likely to live less than 6 months. However, the median length of stay is between 30 and 40 days and a fairly high proportion (some 40%) of hospice patients die within 3 weeks of admission. The criteria for selecting conventional care patients are based on the characteristics of hospice patients. A review of hospice patients’ functional status indicated that most patients have mobility limitiations or need for personal care assistance upon admission. The Karnofsky scale maximum of 50 for potential conventional care patients restricts that sample to patients who are at least as impaired as hospice patients and similarly at risk of “imminent death.” The presence of a principal care person (PCP) is a requirement of most hospices in the U.S.A. and a specific criterion for the HCFA demonstration. Persons under 21 are excluded from the follow-up sample. Age over or under 65 is a stratification variable which serves as a proxy for Medicare eligibility. Patient
sampling procedures
In demonstration and non-demonstration hospices, on-site data collectors independently trained and supervised by evaluation staff determine the eligibility of each patient admitted. Eligible patients and their PCP’s are asked to give written consent to participate in the Study by the data collector. If the number of eligible patients admitted exceeds the data collector’s case load capacity at any given time (approx. 10 patient/PCP units), the data collector uses a table of random numbers to select among cases and approaches those randomly selected.
National
Hospice
Study
Analysis
745
Plan
In conventional care sites, data collectors review lists of patients under the care of participating physicians or admitted to the oncology unit of a participating hospital with a designated on-site contact person (generally an oncology nurse clinician). Permission to contact Study-eligible patients is obtained from the physician, and then the patient and his/her PCP are approached, and written consent to participate in the Study is solicited. PATIENT/FAMILY
DATA SAMPLE
CONTACTS MEMBERS
FOR
FOLLOW-UP
Table 3 below lists the interviews and data forms used for the follow-up sample, grouped by type of information. Each of these is described in greater detail in Appendix B. At all sites, a trained field data collector has responsibility for contacting potential sample members and for gathering the requisite data both through personal interview and by abstracting information from available records. Figure 2 depicts the flow of a patient/family unit through the data process. The first follow-up contact occurs seven days after the initial interview and subsequently at 16day intervals. The number of contacts the data collector has with a patient/family unit varies with the length of life of the patient. At a minimum, the initial interview set and the final bereavement interview are obtained. Given a median length of life of 35 days, the median number of follow-up interviews is two. Most PCP’s have a follow-up interview while the patient is living as well as the final bereavement interview. The interview response burden per contact is limited: l/2 hr for the patient and up to 1 hr with the PCP during the initial contact, 15 min per patient follow-up, and 15 min with the PCP at each patient follow-up. At the bereavement interview, the data collector reconciles the service records gathered while the patient was living with bills received from providers to document health service utilization charges and to document out-of-pocket expenses. SUPPLEMENTAL
STUDIES AND DATA SOURCES
SECONDARY
The National Hospice Study compares the quality of life, health care utilization and cost experience of hospice patients and their families with those of similar patients and families not served by hospice. For valid comparison, similar individuals in the hospice and non-hospice groups must be sampled in the hospice and conventional care systems. A broader population-based approach is also desirable to complement the patient comparisons and to ascertain whether patients served by hospices are different from the larger population of terminal cancer patients. To address these issues and to place the findings TABLE 3.PATIENT-LEVEL DATA SOURCESUMMARY Content
Data
Demographic/background
Patient/family
quality
Cost and utilization
source
Patient intake form Medical record abstract of life
(form
name)
form
Initial principal care person (PCP) interview Follow-up PCP interview Bereavement interview Initial patient interview PCP assessment of patient Medication prescription and utilization record Patient follow-up interview Physician telephone interview Health insurance assessment Weekly service record Cost summary abstracts Hospital Outpatient clinic Nursing home Inpatient hospice Home health agency Physician Medicare bill history file
form
Activity
Time
Activity
Time
Activity
Time
Activity
Time
w
r
/\
FO1lOw-uP IntervIew
Patlent
obtain
v
referral to rJro.1ect
FIG. 2. Diagram
B
PCP Assessment -3f Patient ~-
14 days
1
consent
No.
of a patient/family
PCP Follow-up Tnterview
later
Day
Within 3 days wirtten informed
Day No. 0
unit‘s flow through
the data
90
3
Intake
later
PCP Assessment ofPatient_m Medlcatlon Utlllzatlon
7 days
gathering
- 100 days
system.
after
patlent
dies
Review of ierv~ce Record _____
Conduct telephone interview with primary physician
Variable time period
Repeated every 14 days until patlent dies
NW patients
Patient
days
Wlthin
National
Hospice
Study
Analysis
Plan
741
of the components of the National Hospice Study in context, a number activities are being undertaken. Each of these is described briefly. THE
COST
OF
TERMINAL
CANCER
IN
RHODE
of supplemental
ISLAND
The State of Rhode Island offers an ideal opportunity for a population-based comparison of the medical care costs incurred by hospices and non-hospice patients with terminal cancer. In this study, computerized death certificates from the Department of Health are matched with the bill history files of Blue Cross/Blue Shield of Rhode Island-the Medicare fiscal intermediary and health insurer of most of the remaining pobulation-for all deaths in 1980 and 1981 where cancer was a primary or related cause of death. All individuals served by the State’s only hospice during that period have been identified enabling a comparison of the health care costs of the two groups. Census tract designation facilitates comparisons of hospice and non-hospice groups on basic demographic, economic and health care access characteristics of the neighborhoods in which the individuals resided. These data will contribute to our understanding of differences in the characteristics of hospice and non-hospice patients as well as the patterns and costs of health care services they utilized in the last 6 months of their lives. A COMMUNITY
STUDY
OF
CANCER
CARE
Understanding the pattern of health care provided to a population of patients with terminal cancer under fairly “typical” community conditions is an important part of interpreting National Hospice Study results and of assessing the larger implications of policies reimbursing hospice services. A small, southeastern New England city served by two community hospitals and a small hospice organization was selected to undertake such an effort. The death certificates of all persons dying between August 1, 1981 and September 30, 1982 with a diagnosis of cancer are being matched with the cancer registries in both hospitals to characterize hospital service use in the last three months of life. Utilization of surgery, chemotherapy, radiation therapy, etc. in this period is compared for patients known to have been served by the local hospice and those who were not. Additionally, the demographic and family characteristics of the two groups will be compared, as will their prior cancer treatment as documented in the cancer registry. The remainder of this monograph presents the details of the five components of the National Hospice Study. Before describing these, however, Section II describes the analytic methodology used to test the major patient/family level cost and quality of life hypotheses including a specification of statistical power. Section III describes the quality of life analyses including the measures used. Section IV presents the methodology for measuring and comparing health care costs. Section V describes the methods used in comparing the service interventions received by hospice and non-hospice patients. Section VI describes the analytic strategy for comparing changes in demonstration and non-demonstration hospices. Finally, Section VII presents the framework for projecting Study findings to the nation based upon alternate policy options.
Section II-Methodology for Determining the Impact of Hospice on Patients and their Families The non-random selection of Study sites in conjunction with the structure of the Medicare demonstration project made using a classical clinical trial research design impossible. However, the rapidly growing and evolving hospice movement meant that a random sample of hospices drawn only two years ago would have been unrepresentative today. The patient selection procedures and analytic strategy for addressing the major research questions have been designed to adjust for possible pre-existing differences in the samples of hospice and non-hospice patient/family units whose outcomes are being compared.
748
DAVII) S. GKEEKet al.
The principal concern is that hospice and non-hospice patients are not drawn from the same population, by virtue of their choice to select one intervention. Nonetheless, it is anticipated that, in view of the Study eligibility criteria applied, there is considerable overlap in the groups being compared. The purpose of this section is to briefly describe the models and statistical methods used to compare the effects of alternative interventions on the outcomes experienced by terminal cancer patients. The models and procedures are stipulated in advance of our examination of the final data and are aimed at compensating, to the extent possible, for threats to the validity of the findings. These procedures are designed to adjust for differences in the comparison samples. Our further challenge concerns comparisons across Study sites and interventions. The number of hospices, both D and ND, and non-hospice Study sites is small, and they were selected purposively. They cannot, therefore, be viewed as representative of the different interventions. Rather, each facility can be seen as an instance, or “design point”, in the array of points that constitute the particular intervention type. To understand aspects of the interventions that influence its effect as observed on patient outcomes, meaningful characteristics of the Study sites can be introduced into the analytic model.
STRATEGIES
TO
ADJUST
FOR
SAMPLE
DIFFERENCES
Two techniques will be used, either independently or jointly, to adjust for possible differences in the characteristics of the samples exposed to the three interventions. One is based upon standard multiple regression techniques to specify and fit mathematical models that relate patient outcomes to patient and facility characteristics. Another employs multivariate procedures to identify and exclude sample numbers in order to ex post facto construct comparison samples comparably distributed on key patient characteristics. Each of these is described below followed by examples of the hypothesis-testing procedures and the resulting statistical power associated with these tests. Multiple
regression
The four main
steps of the analytical
strategy
are:
(1) the specification of mathematical models relating response variables to patient and facility characteristics; (2) fitting the specified models to the observed data and validating the models; (3) the performance of hypothesis tests, specified in advance of inspection of the data and the evaluation of confidence interval estimates to assess the differences in effects between alternative interventions; and (4) systematic use of fitted models to learn which differences in characteristics of patients or facilities are associated with differences in observed effects. The mathematical models are based upon multiple linear regression techniques in which independent variables (IV’s) describe characteristics of patients at Study intake, properties of the service pattern, and case mix of the Study site and the duration of patients’ exposure to the intervention. The models assume interactions between the type of intervention and the IV’s in the regression equations in terms of how they affect the response variable. Modeling a response variable Y that assesses cost of care or quality of life, the equations will be of the general form:
The subscripted X’s denote patient-level independent variables and the subscripted F’s denote facility-level independent variables. Two such equations will be used: one for all hospice patients, and one for all conventional care patients. Separate equations are required because we anticipate interactions between the intervention and other patient-level independent variables, and
National
because settings.
different
facility-level
Hospice
variables
Study
749
Plan
(the F’s) are pertinent
Hospice Y = B, + B, X, + B2XZ +
Analysis
and available
for the two
equation
. . + BpXp + C, H, + C2H2 +
Customary
+ Cq,,
+ eps.
care equation
Y = D, + D, X, + D,X, + . . + DpXp + E, G, + E2G2 + . . . + Erc, + eps. In these models, “eps” is the random “error” term. We assume that E (eps) = 0, that the variance of eps does not vary as a function of the IV’s in the separate equations (though the variance of eps in the hospice equation need not be the same as the variance of eps in the customary care equation) and that the error terms associated with separate patients in the samples are stochastically independent random variables. Some hypothesis tests and estimators used are predicated on the assumption that eps is normally distributed. The models are designed with these assumptions in mind. The IV’s are selected so that these assumptions will be legitimate and their validity will be tested when the models are fitted to the data. A different mathematical model complete with IV’s is used for each outcome measure. Based upon the expert judgement of professionals intimately familiar with the care of terminal cancer patients, independent variables that are conceptually related to the outcome measure are identified. The array of independent variables from which those included in the models will be chosen is large and range from standard demographic data to attitudinal information presumed to be related to choice of hospice. Listed below are the domains of independent variables and examples of specific measures. Patient
demographics
Age, sex, race, religion, Patient
marital
status.
medical and health status
Cancer Family
education,
type, co-morbid
medical
conditions,
functional
status,
nursing
care needs.
situation
Family size, patient relationship to patient, insurance coverage.
and PCP living family income,
arrangements, other support
PCP employment status, PCP obligations of PCP, patient’s
Prior service utilization Type of prior cancer therapy, with physician’s orders. Patientifamily
prior hospital
or institutional
service use, prior compliance
attitudes
Knowledge of diagnosis and prognosis, importance of religion, afterlife, characterization of the aggressiveness of patient’s treatment. Extrinsic
patient’s
belief
in
factors
These include characteristics of the adjacent catchment area (e.g. prevalence of hospital beds, home health services, skilled nursing homes), characteristics of the Study site, hospice or conventional care. Hospice facility IV’s are of two types: (a) those measuring an attribute of the hospice per se; and (b) those combining an attribute of the facility with a component that measures the patient’s exposure to the facility attribute. These latter IV’s are designed to measure the “dose” of the intervention received by the patient where dose is defined as time exposed to a given facility attribute. We assume a linear relationship between a patient outcome variable and the logarithm of the “dose” measure. Thus, the longer a patient is in hospice, the less the marginal effect upon the outcome measure of an additional day.
750
DAVID S. GKEER et u/.
An example outcome is: Volunteer
relating
exposure
a hospice’s
pattern
and volume
of volunteer
use to relevant
= log ([days the patient spent in home care x service hours provided at home per home care patient spent in the hospice inpatient unit x service hours provided inpatients per patient
patient
no. of volunteer day] + [days the no. of volunteer day]}
These variables assume that the intensity of the volunteer component of a hospice’s service intervention is related to the outcomes patients experience. Criteria for including these IV’s into the model are the same as for the patient-level IV’s, To the extent that relationships to patient outcome are observed, it is reasonable to interpolate findings to similar hospices not specifically included in the study. Validation of the model will rely upon graphical methods and objective computational tests. The graphical methods identify striking violations of model assumptions, and computational tests assess the significance of observed departures from the assumptions. Each graphical method (normal probability plots of residuals, residual plots against IV’s not in the model, and partial regression leverage plots to identify outlier observations) has a counterpart in an objective test [S]. In addition, standard goodness-of-fit tests for the models will be carried out provided the assumption of normality is supported [9]. Once these procedures have been applied and the linear models are accepted, hypotheses about the effects of the alternate interventions can be tested. If the linear models are not accepted, the diagnostic methods will guide our redesign of the models or selection of appropriate non-parametric methods Random
sample simulation
(SIMRAN
’ ) [lo]
An alternate approach to adjust for pre-existing differences among demonstration, non-demonstration and conventional care patients is to identify specific patients or groups of patients who are outliers by reviewing key independent and stratification variables. This is done by using a random sample simulation procedure which identifies the types of patients present in each Study sample and equalizes the proportions of these types across the samples. The procedure to be employed considers the comparison groups as pools of potential sample members. Briefly described, it selects the final comparison samples from the pools of demonstration, non-demonstration and conventional care follow-up patients. The first step in the process considers the total pool of subjects to be the sample universe. In 100 separate trials, the computer algorithm randomly allocates patients into comparison groups. For each set of random comparisons, baseline indices of the number of significant differences found between the different groups are computed on some 100 independent and dependent variables. Additionally, the average ‘I’ of each variable is calculated. The generation of modelled random samples and computation of significant differences and average q’ statistics is repeated until 100 simulated comparison samples are drawn and computations for at least 100 variables are completed. At that point, a frequency distribution of the number of significant differences and the average y ’ for each sample is computed. Percentile scores, ranking the simulated random samples from least to most comparable, form the criterion against which subsequent adjustments to the actual samples are compared. Starting with the patients in the conventional care pool, the computer algorithm selects comparison samples that pass the criterion established (i.e. being no “different” than one of the “better” random samples). Using random procedures, a series of iterations then attempts to select a sample from the larger pool of demonstration subjects which is comparable to the subjects in the smaller, conventional care pool. At each iteration, the number of significant differences between the groups and the size of the average ye’ on the criterion measures is calculated. A randomly selected demonstration sample will be considered acceptable if it is better than average of the simulated random samples. i.e. the comparison samples have fewer significant differences and a smaller average q’ than the
National
Hospice
Study
Analysis
751
Plan
50th percentile established by the previous frequency distributions of “true” random draws. However, even if an acceptable demonstration sample is drawn, the algorithm continues to search (without reducing the sample sizes) until the “best” sample is identified (having the fewest differences and the smallest average q2). If no acceptable frequency-matched sample has been found, the third step is initiated. Demonstration hospice patients considered to be outliers are dropped. Later, subjects from either the non-demonstration or the conventional care groups who are extreme outliers are dropped. Following each adjustment, the procedure again tests the resulting samples against the criterion. Experience has shown that even with very dissimilar pools of potential subjects, comparable samples can be identified for impact evaluation purposes without unduly sacrificing the sample sizes. Given the procedures for selecting the subjects in this Study, it can be assumed that the overall pools will not be extremely dissimilar. In summary, the procedure identifies and selects impact comparison groups having similar distributions on a large array of patient characteristics at comparable points in their “death trajectory”. Based on several a priori criteria, the procedure tests each sample for equivalence along an array of relevant independent measures and selected dependent variables. Only when sample comparability has been demonstrated at the criterion level are the patient outcome hypotheses tested. STATISTICAL
POWER
OF
THE
HYPOTHESIS
TESTS
The major Study hypotheses concerning quality of life and costs will be tested separately for the overall sample and for patients over and under 65 yr of age (Medicare eligibility). In the case of the multiple regression approach, an approximate 9.5% confidence interval estimate for the expected value of the difference between the average response of hospice and non-hospice patients is given by: EY,
- EY,(f)2
x D,
where D = {Z;i(W;W,)-‘Z,MSEu Here,
“t” denotes
EY,
transpose
= B, + B,X, +
+ Z;(W;W,)-‘Z,MSE,}‘~2 and
+ BJ,
+ C,H, + . . . C,H,
EY,=D,,+D,X,+...+D,X,+E,G,+...E,G, Z:,=(l,X
,,...,
Xr,H ,,...,
H4)
Z:=[l,X
,I...,
X,,G
G,)
,,...,
W, = independent
variable
W, = independent
variable
MSE,
design
matrix
design matrix
for the hospice for the customary
= residual
mean
square
error
for hospice
MSE, = residual
mean
square
error
for customary
equation
equation
regression;
care equation
regression;
regression;
and care regression.
Using the SIMRAN’ approach, unadjusted one- or two-way analysis of variance techniques will be used to test Study hypotheses for the relevant response variables on the assumption that the samples are comparable. With either approach, the introduction of facility-level variables into the analyses will be limited to a small number. The statistical power of the hypothesis tests is a function of the variance in the outcome measure, the sample size, and a priori assumptions concerning the size of the differences between the groups which will be accepted as “true”. Preliminary examinations of the major patient-level cost and quality of life variables have made it possible to realistically specify the power of the hypothesis tests associated with these two outcomes.
752
S.
DAVID
TABLE 4. TEST
POWER
THE
TABLE
QUALITY
CONFIDENCE
et ul.
COK SAMPLE
OF
LEVEL
GKEEK
LIFE
(N
SIZE
NECESSAKY
HYPOTHESIS
= SMALLER
OF
AT
THE
To
95”,,
COMPARISON
SAMPLES)
Differences in samples expressed as a percentage of the mean ,I 0
Level of statistical (1 -ill
IO IS 20 30 40 SO
power
0.5
0.6
0.7
0.8
0.9
253 II2 63 28 16 IO
322 I43 X0 36 20 I3
404 I80 101 45 25 I6
512 228 128 57 32 21
683 304 I71 16 43 21
Table 4 presents the sample size necessary at various levels of statistical power (1 - /I) given varying accepted levels of true differences across samples for the principal quality of life outcome measure, the modified Spitzer Quality of Life Index. Estimates of the mean and standard deviation of the measure are based on preliminary examinations of the data. Sample sizes are predicated upon a 95% confidence limit, or at cz = 0.05. The differences between samples are expressed as percentages of the mean on the QLI scale which ranges from 0 to 10. A difference of at least 157; on this scale will be accepted as a true difference, A sample size of 304 conventional care patients will be required to assure that SOo/, of the time we will be correct in assuming a true difference actually exists. Table 5 presents comparable information for the principal patient cost measure--sum of inpatient and home care reimbursable service utilization multiplied by constant cost coefficients. In this case, a coefficient of variation (x,SD] of one (1) is assumed and levels of differences are expressed as percentage from the mean. Upon consideration of the different patterns of service utilization both hospice and non-hospice patients receive, a minimum of a 207< difference in the terminal care health costs associated with the two samples will be accepted as a true difference. At a desired power level of 0.8, a sample size of 404 patients in the conventional care group will be required. Based upon most recent sample size projections, the number of hospice and non-hospice patients necessary to reliably test the major Study hypotheses will be reached.
Section III-Methodology for Determining the Impact of Hospice on Patient/Family Quality of Life The analyses of the impact following hypotheses:
of hospice
on the lives of patients
and their families
test the
Hypothesis 1 The quality oj’patients’ lives in hospices \ilill he better than that experienced by comparable non-hospice patients. Patients will experience fewer discomforting symptoms, less severe pain, more positive mood states, and greater satisfaction with care received. Hypothesis 2 The.fkmi1ie.s of hospice patients
M’ille.uperience ,f&ter physical
ISSUES
In developing -Selection -Timing -Validity
an analysis
AND
problems.
RESOLUTIONS
plan to test these hypotheses,
of outcome areas. of data collection. of patient reports.
and psychosocial
three major
issues arise:
National
Hospice
Study
Analysis
Plan
753
TABLE 5. POWER TABLE FOR SAMPLE SIZES NECESSARYTO TEST
THE
PATIENT
CONFIDENCE
LEVEL
COST (N
HYPOTHESIS = SMALLER
AT OF
95%
THE
COMPARISON
SAMPLES)
Differences in samples expressed as a percentage of the mean
Level of statistical (l-8)
-~
power
%
0.5
0.6
0.7
0.8
0.9
IO 20 30 40 50
800 200 89 50 32
1016 254 113 63 41
1276 319 142 80 51
1616 404 179 101 65
2156 539 239 135 86
Selection
of outcome
Quality state, the relations. quality of
of life is a multi-dimensional construct which is conceptualized as positive mood absence of physical and psychological distress, and satisfactory interpersonal In this study, we have identified a series of measurable dimensions of patient life:
-Severity of pain -Functional status -Quality of social -Satisfaction with -Sense of isolation -Satisfaction with
areas
and other symptoms. and mobility. interactions. life. and burden on others. care received.
Table 6 (segments A through H) lists the scales and measures used to generate the dependent variables which represent the dimensions of patient quality of life. With respect to thefamily, hospice claims to be effective in mitigating grief reaction and decreasing psychosocial and physical morbidity through the provision of training, education and counseling while the patient is alive and, subsequently, through bereavement and counseling. Hospice can also benefit the family indirectly. The family may feel more secure in the knowledge that they have done all they could; death may not be viewed as a failure on their part. Additionally, because the family will have been educated as to what they should expect in the final stages, the psychological trauma associated with death may be reduced. From this perspective, the outcome areas being assessed are: -Indicators of family secondary morbidity dysfunctional symptoms). -Family satisfaction with care received. -Subjectively reported grief reaction.
(psychosocial
The scales and measures to be used to capture 6 (Segments I through L).
distress,
each outcome
role
change,
and
area are listed in Table
Timing of data collection In determining the frequency of follow-up contacts, a number of factors were considered. First, the initial follow-up had to be timed to include the large number of patients who die within two weeks’ time of admission to hospice. Second, for ethical reasons and to maximize the participation rate, the response burden on both patients and families had to be minimized. Finally, we sought a schedule of contacts which would enable the data collector and the patient/family unit to set aside a constant time period on a given day of the week for all visits. The unpredictability of duration of life for terminally ill patients makes it impossible to systematically schedule visits so that one will coincide with the final few days of life, but the schedule assures a last follow-up contact generally no more than two weeks prior to death.
NPJIUNAL
questions
Impact on patient satisfaction with medical care
G
H. Impact on PCP satisfaction with professional care c l”romlal support
Impact on overall quality of life of pallanl
F.
on
the feeling a burden
ImpaLA
E.
of being
“load
RPS’SEAKCH QUESTIONS
diw
support
CBTL‘
of life
professional
3 days
on
Satisfaction with profewonal care of patient (including
Inr
purienr
with
Satisfaction
While
of last
a burden
Character
HRCA QL-Index Uniscale Karnofsky
Sense uthws
Dysphol-ic
of pain
or visiting
Self esteem
Chatting
Impact on patient perceived social Interactlo”\
C.
patient’s of being
STIJDY:
&verily of common symptoms other than pain: Nausea or vomiting Dry mouth Constipation Dizziness bever or chills Shortness of breath Overall assessment
Description
Impact on patient‘s physical symptoms
research
HOWKF
B. Impact on patient report of pain
A.
6.
0utc0mc area
TABLE
assessment
PCP self report
Patient self report
PCP assessment PCP assessment Interviewer ludgement PCP bereavement
Patient self report
Patient self report Patlent self report
Patlent self report
Pallenl self report PCP assessment
PCP
or
OUTCOME
Source data
Patient self report
ON PATI~NT/~AMILY
AREAS
5
IO
I3
5
2
IO
6
4
2
6
Items
AND
Number
A fXTlNC
I
I
2
h
I
1
I
I
2
and
Rand,
Wolf
HR(‘A
e/ (Il., and HRCA
Wolf et al., Rand, and IIRCA
Kastenbaum
HRCA, Spitzcr Spitzer Karnofsky
HRCA
HRCA
Moditied from Li”n’\ Modification of POMS
Rosenberg
HRCA
I
Spitrer Melzack Spitzcr
I
source*
I” gcncral “SC
Item
MEASURbS
1
I
2
I
Outcome measures
of:
OF ASSOCIATEU
Impact on secondary morbidity/grief experienced by family members
Bereavement Physical symptoms Depression Overwhelmed Anxiety Loss of faith Unsettled Anger
PCP self report 5 6 I2 3 3 5 5
8
While patient dice rmd ut hereaoement Symptoms
3
I
I
5
PCP self report
PCP assessment
PCP self report
While putient alive Mood state
Residence change Job related
B.Cr~U~emeflt Social involvement/family interaction
Job related
Ability to meet other needs
While patient alive Social Financial
I
1
I I I I I
1
Sanders Sanders Sanders Sanders Sanders Sanders Sanders
HRCA
Rand
HRCA HRCA
& HRCA
& Rand
Rand and Sanders
HRCA
HRCA
HRCA HRCA
*Linn MW, Linn BS, Harris R: Humanistic Oncology: The Potential in the Omega Experience. Miami, Florida: VA Medical Center. 1980 Melzack R: The McGill pain questionnaire: major properties and scoring methods. Pain 1: 277, 1975 Rand Corporation: Instrumentation for Hospice Study, 1980 Rosenberg M: In Measures of Social Psychological Attitudes. Robinson JP, Shaver PR (Eds). Ann Arbor, Michigan: Institute of Social Research, University of Michigan, 1973 Saunders C, Mauger P, Strong P: A Manual for the Grief Experience Inventory. Loss and Bereavement Resource Center, University of Southern Florida, 1979 Spitzcr WO, Dobson AJ, Hall J, Chester-man E, Levi J, Shepherd R, Catchlove BR: Measuring the Quality of Life of Cancer patients: A Concise QL Index for Use by Physicians. The Royal North Shore Hospital of Sydney, The Commonwealth Institute of Health of Australia at Sydney University, The University of Newcastle and the McGill Cancer Centre Wolf MH, Putname SM, James SA, Stiles WB: The Medical Interview Satisfaction Scale: Development of a scale to measure patient perceptions of physician behavior. J. Behav Med I: 391, 1978
J.
1. Impact on social roles of family members
DAVID S. GREEKet ul.
756
Validity
of patient
reports
During the terminal stages of cancer, some patients are not lucid or able to communicate. The likelihood of this occurring increases as the patient approaches death. Ability to acquire valid data from the patient under these circumstances is diminished. To compensate for this, two strategies have been adopted. First, a PCP Assessment of the patient is completed at each follow-up, even if no interview with the patient is possible. This assessment provides for continuity of measurement for all patients. Secondly, at both the initial and follow-up patient interviews, non-attitudinal measures concerning the patient are obtained by proxy from the PCP if the patient is unable to provide this information.
ANALYTIC
Forms
qf the
dependent
STRATEGY
variables to be tested
Table 6 lists the outcome areas, the associated scales or measures, their sources and the method of obtaining the data. Repeated measurements will make it possible to approach the analysis of each dependent measure in several ways. These can be categorized as: (1) Simple comparisons of a variable at different follow-up interviews (e.g. last, next to last); (2) Summary measures of patient status on a given variable across various intervals (e.g. between the last and an earlier period); (3) Change scores calculated on the basis of the direction and magnitude of change on a given variable between two temporally adjacent follow-up interviews; (4) More complex interactive measures relying on information from both the patient and the principal care person. The simplest form of the dependent measure is an established summated scale as outlined in Table 6. Patient scores on such measures can be compared for each discrete follow-up period. This approach addresses such questions as “What is the impact of hospice (e.g. on patients’ symptom patterns) in the last weeks of life?” This least complex form of each dependent measure construct is the basis for the explicit hypothesis testing. The dependent measures may also take the form of a summated score over the impact period. Each patient’s raw scores at different interviews for a particular outcome measure can be summed with the goal of creating a total index for the variable of interest. Included within the dependent variable array for the patients are a number of previously established scales that can be used in this type of summated format. By summing the scales over time and creating average scores, patients’ status during exposure to hospice (or conventional care) can be characterized. These scales are known to be sensitive to shifts in the status of patients. For example, the Melzack Perceivable Pain Inventory scores the degree of pain-from none to excruciating-based on the patient’s response. A change score measuring the difference in the degree of pain experienced by the patient between any two points in time is constructed by subtracting the pain score recorded at one interview from that of the preceding contact. A final approach relies on comparable information obtained from both the patient and the principal care person to construct a measure of discrepancy of perception. For example, one dependent variable uses both patient and family information regarding the patient’s last three days of life. During the initial interview, the patient is asked: “If the last three days of your life could be exactly they be like?”
the way you want them, what would
The interviewer classifies the response to this open-ended question based on whether particular issues were mentioned. Examples of common response classes are: freedom from pain, at peace with God and in the presence of loved ones. At the bereavement interview,
National
Hospice
Study
Analysis
757
Plan
the PCP is asked to characterize the patient’s final days of life on the same set of issues. On the basis of these two data sources, difference scores are calculated. It is possible to determine whether the last three days live up to the expectations of patients and whether hospice patients are more or less likely to have spent their last days as they wished.
Number
qf dependent uariuhles
The multiplicity of quality of life outcome areas and the variety of forms specific variables can take result in a proliferation of outcome measures. Valid arguments can be made for the relevance of each. However, this multiplicity of variables makes it difficult to integrate and interpret even statistically significant results. Therefore, for the purpose of hypothesis testing, the analyses are reduced to single summary indicators of patient and family outcome within each of the domains listed earlier. However, in order to capitalize on the richness of the data, established statistical techniques, involving a widening of confidence intervals and narrowing of critical regions to compensate for the loss of significance associated with multiple tests, can be used (e.g. the methods of Bonferroni, Tukey and Scheffe).
Examining
diSferences in longetliiy
The procedures for selecting conventional care patients described in Section I seek to ensure that, on average, conventional care patients enter the Study at the same point in their terminal trajectory as do hospice patients. (For hospice patients, Study entry is admission into the hospice.) In the absence of random assignment, the evaluation can only simulate this comparability by monitoring longevity differences between the groups and adjusting the conventional care selection procedures prospectively in the event that differences are observed. If differences in the length of life distributions of hospice and non-hospice study patients are found at the end of the data collection period, there are two possible explanations. (a) Selection hius. That is, the selection criteria were not sufficiently sensitive to ensure that hospice and non-hospice patients entered the Study equidistant from death. (b) An ~fict on morfalify. That is, hospice or conventional care patients having entered the Study at comparable points in the terminal phase live longer: presumably due to the specific nature of the interventions they received. Should a difference in the length of life distributions be observed, the initial interpretation will be that it is a function of selection bias. To test this assumption, differences in length of life will be statistically controlled. Using both multiple regression and sample adjustment procedures, patient longevity will be examined to identify predisposing factors conceptually relevant to “explaining” length of life. These will include: -rate of disease progression-time between initial -cancer diagnosis; -metastatic sites on Study entry; -functional status on Study entry; -prior treatment (surgery, chemotherapy, radiation -cancer type (e.g. lung, breast, etc.); -age; -presence of non-cancer-related medical conditions.
diagnosis
and date of Study
entry;
and combinations);
The predicted longevity of hospice and non-hospice patients will be compared. If greater than one week, additional analyses will be undertaken to isolate other potentially contributing factors. Observed longevity differences will, however, have no bearing on comparative analyses of quality of life or patient cost outcomes since all analyses will be performed retrospectively from time of death.
758
DAVID S. GREER el rtl
Section IV-Determining The patient/family Hypothesis Hospice
economic
the Impact of Hospice on Health Care Costs analyses
test the following
hypotheses:
1 patients
have lower terminul
because less expensive care. Hypothesis 2
home/hospice
The cost qf curing for demonstration ,for comparable
non-demo~srratjon
likely to induce demonstration paid staff for volunteers*. Hypothesis 3
care costs than comparable
care is substituted
non-hospice
for more expensive
patients,
institutional
hospice patients will be higher than the cost of caring
hospice
patients,
hospices to increase
Hospice patients served by hospital-bused higher terminal care costs than comparable
because Medicare reimbursement is the volume of services and/or substitute
hospices or hospices with inpatient beds will have hospice patients served in other settings, because
hospices with inpatient beds will provide more institutional care and less home care than hospices without inpatient beds, and presumably institutional care is more expensive than home care. Hypothesis 4 Medicare hospices,
wjill pay ,fbr relatively
compared
because federal Hypothesis 5
more qf the cost of‘ care ,for patients
to patients in non-demonstration
reimbursement
in demonstration
hospices and conventional
will affect the type and quantity
of services
care settings,
rendered.
Hospice cure will a$Gect the level of informal home care provided to terminal patients (but the direction of the effect is unclear). Family involvement along with greater time spent by the patient at home may lead to an increase in the amount of informal care provided by families; alternatively, the expected increase in forma1 care provided by the hospice may substitute for informal care and lead to a reduction in the amount of informal care provided by families and volunteers. ISSUES
In developing
an analysis
AND
plan to test these hypotheses,
-measuring costs; -timing of the measurement of dependent -pooling observations across sites. Measuring
RESOLUTIONS
variables;
three major
issues arise:
and
costs
Overview. The patient cost analysis uses standard accounting definitions of unit costs for the services used by hospice and conventional care patients. The accounting standards used by Medicare are applied to both Medicare and non-Medicare reimbursable services because they are consistent and widely used. Since the price to payors of specific health care services is rarely equivalent to the cost of producing it?, economic analyses must treat charges for services separately from costs. In a non-profit operation, the total monetary costs of a service should equal total charges, when charges include all direct, indirect and imputed payments. In fact, it is impossible to identify all payments and it is equally impossible to measure all costs. Costs are
*If demonstration hospice care is more expensive than non-demonstration hospice care but less expensive than conventional care, then the effect of hospice reimbursement on system health care costs hinges on the extent to which the waiver system induces people who would have been using conventional care into the hospice system vs the extent to which the waiver simply substitutes reimbursed for non-reimbursed hospice care. tThird party reimbursement procedures and provider billing practices typically involve various types of adjustments. discounts, and cross-subsidies.
National
Hospice
Study
Analysis
159
Plan
absorbed by the system, accepted as uncollectable bad debt and/or shifted onto other payors. For these reasons, the patient/family economic analyses examine costs, derived from resource commitments, separately from charges or how the burden @paying for care is shared among payors. Cost construction. Regional average Medicare unit costs are used to compare hospice and conventional care. These unit costs are applied to Medicare and non-Medicare patients, regardless of whether they are served by hospices or by non-hospice programs. Cost construction depends upon the kind of service provided. In some cases, regional average Medicare costs-per unit of service are multiplied by patient utilization levels (e.g. nursing visits). In others, total charges per patient for services are multiplied by patient utilization levels (e.g. physician visits). In others, total charges per patient for services are multiplied by regional average Medicare cost to charge ratios (e.g. ancillary services). Medicare data for costing are derived from Medicare Cost Reports available from secondary sources. In comparing demonstration and non-demonstration hospice patients, unit of service cost/charge coefficients are developed for each participating hospice for use in the patient level cost analysis (see Section VI). In hospice/conventional care comparisons, these regional averages substitute for the specific hospice cost coefficients to determine the costs of services hospice patients use. In the event that comparable hospice services “cost” substantially more per unit than regional Medicare averages (based on the facility level analyses), the intensity of services (e.g. number of hours of care per visit) can be used to differentially weight hospice patients’ utilization. Thus, the form for defining costs will differ somewhat in performing hospice/non-hospice and demonstration/non-demonstration comparisons. -The hospice/conventional care analyses will compare relative resource utilization using unit cost weights that are constant across facilities (but not across regions), but that vary among patients due to differences in service intensity. -The demonstration/non-demonstration analyses will compare patient costs, within which both levels of utilization and unit costs can vary among patients and facilities. All of the following services, whether or not they are Medicare adjusted to cost bases for the hospice/conventional care analyses:
reimbursed,
will be
Inpatient hospitalization: routine and ancillary costs, adjusted by region and facility (bed size, teaching status); Outpatient visits: costs per visit adjusted by region and facility type; Skilled nursing facility days: costs per day; Home health visits: costs per visit.
type
Analysis of charges. Some services cannot be readily subsumed under this methodology. Physician fees can be related to Medicare standards for “reasonable and customary” charges. This standard may not reflect the costs of a physician’s services. Moreover, there are separate standards for hundreds of different procedures performed by physicians which determine the charge. Drugs, equipment, medical supplies and other expenses are similar. No single regional standard can be developed to translate a drug charge into a measure of cost. The variety of types, brands and sources of drugs makes such a procedure impractical. The same can be said for supplies, medical equipment and other expenditures. For these reasons, we plan to separately analyze variations in charges between hospice and conventional care patients, and between demonstration and non-demonstration hospices for physicians’ visits (not billed through the facility) and for drugs supplies and other treatment related expenses. Much of the variation in these measures reflects billing practices and the relative market “power” of individual physicians. Timing
qf the measurement
All analyses (‘D36’11<
are stratified
of dependent by length
variables
of life. First,
all patients
who live at least a week
760
DA\III) S. GREEK et d
after they entered the sample are analyzed to ascertain the effect of hospice care on total costs in the last week of life. The same analysis is then performed for those living at least 3, 5, 7, etc. weeks. This procedure for analyzing total costs at different lengths of time before death makes it possible to deal with the problem of varying time periods of observation. It also provides a method for approximating a non-linear time relationship of costs to treatment period. Suppose that hospice care reduces hospitalizations predominantly in the last weeks of life and increases home care over the entire time that a patient is in a hospice. As the length of stay in hospice increases, the cost advantages of hospice would decrease. The proposed procedure provides a test of this expectation; it will demonstrate whether length of hospice stay does, in fact, affect the cost savings due to a hospice. The total hospice “effect” for a patient with a given length of participation will be the sum of conventional care minus hospice costs, over a certain number of weekly or bi-weekly periods. Thus, the total cost differential due to hospice is the sum of these individual effects for all sample hospice patients in a specified number of intervals. Pooling
ohseraations
across sites
In testing the patient level cost hypotheses, three jointly or separately analyzing data from all sites. -Data can -Analyses the three -Data can
possible
options
are available
be pooled from all sites. can be performed separately using patients drawn only from sites adjacent regional management centers. be pooled only from the sites in the three regions.
for
to
Each option has advantages and disadvantages. By performing analyses at all three levels and integrating the results, the evaluation capitalizes on the advantages of each option while minimizing the disadvantages. The main advantage of the first option-pooling all the data-is that it maximizes both the patient and facility sample sizes. maximizing the statistical power of the tests. However, it also maximizes the burden put on the analysis to control for regional differences in the patterns and costs of care. The second option, performing analyses separately within each primary area, minimizes the burden of controlling for regional differences in care patterns. However, since within-region patient sample sizes are smaller, estimates of the effect of hospice compared to conventional care are less precise. Given the smaller number of demonstration and non-demonstration hospices within each region, it is not possible to estimate the effect of hospice organizational structure on the patterns and costs of care for the terminally ill within region. The third option is a compromise between the first two. Problems of comparability will be larger than in the second option, and smaller than in the first option. Statistical power and the ability to estimate the effects of hospice organization types on outcome will be less than in the analyses of the first option (with all data pooled) and greater than in the analyses of the second option (of each primary area taken separately). Formal testing of the explicit cost hypotheses are based on the first option of pooling all data. The use of regionally standardized cost coefficients and control variables reflecting regional variations in patterns of care should be sufficient to accurately assess differences in resource use. On the other hand, tests of the payor burden hypotheses are reasonably restricted to option three (pooling only the three regions) in view of the sharp variation in the pricing factors that result in billable charges.
ANALYTIC
STRATEGY
There are three major components to the patient/family economic analyses: patient analyses, distribution of payor burden analyses and informal support analyses.
cost
National
Construction
qf andysis
Hospice Study Analysis Plan
761
zlariables
for the cost, payor burden and informal support components of the study are created from a synthesis of both primary and secondary data sources according to the following model. Patient cost. Inpatient, outpatient and home care utilization and charges are converted to a Medicare cost basis, using cost to charge ratios taken from secondary sources. Cost to charge ratios are regional averages (by type of facility, for hospitals). Hospice unit costs, which are constructed as part of the organizational and facility cost analyses (see Section VI) are specific to each individual facility. Consequently, relative to the regional averages approach, there is greater variability in service costs of hospice services. Therefore, facility specific costs are used only in comparisons of demonstration and non-demonstration hospice patients. Payor burden. Medicare payments for covered services are obtained from claims files and are interim payments (payments to facilities before year end adjustments are made). Self-payment is estimated, using the out-of-pocket expense information (log-diary) and supplementary information on non-Medicare insurance coverage for each patient. Total charges are determined from Medicare Claims Files for Medicare services and from bills and receipts for non-Medicare services. Since demonstration hospices do not charge for covered services, and since Medicare covers the entire amount of allowed charges for these services, demonstration charges are identical to Medicare payments for these services. Irzformal support. Total hours of home care is captured on the Service Records and the hours of informal support provided by families, friends and non-hospice volunteers comes from interview information. Analysis
Patient
variables
cost analyses
Medical and services costs per case include the costs of care provided to patients by hospitals, nursing homes, hospices, physicians, outpatient and at-home visits, prescription drugs and medical equipment and supplies. Both reimbursed and out-of-pocket costs are included. Several types of dependent variables are analyzed. (I) Total costs for the last week of life and for each previous bi-weekly periods, for demonstration, non-demonstration and conventional care patients; total costs include patient hospital and SNF care, outpatient and home care visits. (2) Total costs, as defined, for the entire study period (intake to death) for demonstration and non-demonstration hospice patients. (3) Total home care costs for the entire study period for demonstration and nondemonstration patients. (4) Total physician charges, for periods and patients described in categories 1 and 3 above. (5) Total drug, equipment. supply and other charges, for periods and patients described in numbers 1 and 3 above. A measure of the effects of alternative types of care on total health care costs or charges can be obtained by estimating separate regression equations for patients in demonstration and non-demonstration hospices and conventional care settings as described in Section II. If analyses of total cost show hospice care is different, there are both substantive and methodological reasons for analyzing the subcomponents of total cost. Substantively, knowing that total cost per case goes up or down in a hospice does not provide an understanding of why costs change. Analysis of the aggregate total cost obscures the various pathways through which hospice care may affect costs. We have chosen in advance to study home care costs for hospice patients because hospice programs have been designed to provide a home care alternative for the dying patient. As such, two estimates exist (i.e. home care vs total costs) of the effects of hospice (or particular types of hospice) on the cost of care for terminally ill patients.
762
DAVID S. GKEEKCI ul.
Distribution The
qf payor burden
analyses
described
above
considered
“costs”
to all
payors
(i.e.
the
amount
reimbursed by all payors). For policy purposes it is important to know the effects of hospice care (and of Federal reimbursement) on the portion of charges paid by Medicare, other third parties and patients and their families. Actual charges are used in this analysis rather than standardized costs. These charges will cover all categories of services gathered, excluding volunteer services. Total charges are defined as billed charges for all services to conventional care patients and non-demonstration patients and non-hospice services provided to demonstration patients. Hospice services provided demonstration patients must be treated differently from ordinary Medicare reimbursement because they are not liable for deductables or co-payment: the hospice submits bills directly to the HCFA Office of Direct Reimbursement using budgeted costs and an estimate of patient utilization. The hospice receives payment in amounts that reflect total expected reimbursement. Thus, demonstrationcovered hospice services are viewed as “billable” charges. Payments are defined as: (1) Interim payments by Medicare (non-pro-rated adjustment to be included for final adjustment) are facility-specific rather than patient-specific. (2) Out-of-pocket payments that are documented in the Service Record and supported by bills. “Other payor” payments will be computed as the residual, that is, the difference between total charges and total Medicare plus out-of pocket payments. The measure of payor burden used in the analysis is total billed (or billable) payment source). Multivariate analysis will be conducted for:
charges (by
-Medicare payments/total charges, for the period intake to death, for demonstration and non-demonstration hospice patients and conventional care patients. -Self-pay/total charges, for the same breakdown. Since (Medicare/total) + (self-pay/total) + (other/total) = Total charges. it will not be necessary to estimate the “other” equation once the first two equations have been estimated and total charges have been determined. Informal
support
Measures of the level of informal support received by terminally ill patients from the primary caregiver and their family members are available from interview data. Potential effects of service mode are tested by comparing the hours donated by caregivers of patients in the various samples. Although this analysis captures part of the resource intensity of hospice care, one cannot justify imputing dollar values to informal support. Thus, this analysis is treated separately from other components of the patient/family cost analysis.
A
SUPPLEMENTARY
WAIVER
HOSPICE
PATIENT
ANALYSIS
Separate analyses of the hospice cost and utilization data available from HCFA/ODR Medicare bills on the complete census of all Medicare demonstration hospice patients are being performed. The advantages of this sample are its large size (expected to include over 5000 patients), its inclusion of terminal patients without cancer and the fact that complete detailed utilization data of hospice services will be available. Analysis of this sample may provide information on the effect of alternative hospice organizational types on services provided by the hospices, and it may increase our understanding of the relationship between patient functional status) and services characteristics (e.g. diagnosis, patient demographics, received. Moreover, since the follow-up sample is limited to terminal patients with cancer, this supplementary analysis of both cancer and non-cancer patients provides the only
National
source of information disease.
Hospice
on the costs of terminal
Section V-Comparisons
Study
Analysis
Plan
763
hospice care for patients
without
malignant
of the Intervention Terminal Cancer Patients Receive
The comparative analyses of the service interventions patients are exposed test the following hypotheses:
to which hospice and non-hospice
Hypothesis 1 Hospice patients and their families will be more likely to receive psychosocial support services than non-hospice patient/family units, given the emphasis in the hospice philosophy of treating the whole person and the focus on interdisciplinary treatment. Hypothesis 2 The involvement of physicians in the care of terminal patients will be less among hospice patients relative to the involvement of other service providers. Hypothesis 3 Hospice patients will be less likely to be exposed to high technology and/or intensive diagnostic and therapeutic procedures during their last months of life than non-hospice patients. Hypothesis 4 The level of analgesic and tranquilizing medications prescribed for and consumed by hospice patients will he higher than for non-hospice patients, given the hospice emphasis on the prevention of pain and other symptoms. ISSUES
The methodological
and conceptual
(a) The validity of self-report (b) Implied value judgements. Validity
?f’ self-report
AND
RESOLUTIONS
issues relevant
to testing
these hypotheses
include:
data.
data
Patient-level data concerning exposure to various services are gathered directly from the Primary Care Person (PCP) at each scheduled follow-up visit. Rather than relying on the utilization data available for the Patient Cost Analyses, the PCP is asked whether the patient received any one of over 20 discrete types of services. Potential problems of recall are minimized by the bi-weekly follow-ups. Some differences in interpretation may occur. A syllabus of service definitions has been developed to explain the meaning of each type of service to the PCP and the instrument has been successfully pretested. Implied value judgements In testing the hypotheses presented above, no attempt to assess quality or to establish norms is implied. The hypotheses derive from the stated goals and philosophy of the hospice movement rather than value judgements. If the interventions are different and can be correlated with differences in outcome, some value judgements may be implied by the data, but neither the methodology nor the mandate of this study justifies value judgements. Conventional care is changing rapidly, at least partly as a function of the impact of the hospice movement and it is essential to determine whether the pattern of services provided to hospice patients is, indeed, different from that received by non-hospice patients. ANALYTIC
SAMPLES
The third and fourth hypotheses are tested on a subsample of the follow-up sample. The subsample consists of approximately 10% (n = 160) of the D hospice patients and 30% (n = 130) of the ND hospice and CC patients; it is a random sample of the full follow-up sample drawn proportionately from each participating study site. For this subsample, detailed prospective data on Medication Prescription and Utilization are collected.
164
DAVID S. ANALYTIC
GREEK
el ul
STRATEGY
The basic analytic strategy compares the likelihood of receiving various medical and psychosocial services in hospice and non-hospice programs at various points in the terminal phase of the patient’s disease. The service activities compared are categorized and listed below: Medical
Respiratory therapy Surgery Chemotherapy Radiation therapy Hormone therapy Thoracentesis X-Rays Blood tests Oxygen Physical therapy Intravenous therapy Bladder/catheter care Ambulance
Psychosocial
Counseling Financial/legal counseling Assistance with paperwork Arranging for services Training patient in self-care Healing/therapeutic touch Guided imagery Meditation/prayer Relaxation exercises Hypnosis
The initial comparative analysis adopts a service-by-service approach, first examining the proportions of patients in each group receiving a service within two weeks of death, within 4 weeks of death, etc. Then, the cumulative likelihood of hospice and non-hospice patients receiving a particular service at any time between study entry and death is examined. In addition to a variable-by-variable approach, service configurations are being constructed to take into consideration the possibility that services are interchangeable, or at least perceived as such. For example, financial/legal counseling may effectively be handled by assistance with paperwork (e.g. filing insurance claims, etc.). Similarly, oxygen and respiratory therapy can be seen as the same by a PCP. An “either/or” configuration caputures this substitutability. Further, receipt of service, or set of services, can be linked to the patient’s relevant symptoms during the same, or a temporally adjacent, measurement period. For example, the proportion of patients reporting shortness of breath who receive respiratory or oxygen therapy can be compared for the hospice and non-hospice samples. It must be recalled, however, that the data collection strategy makes it impossible to demonstrate a direct causal link between the emergence of a symptom and introduction of a service to ameliorate the symptom. The comparisons must remain descriptive, i.e. given similar symptom patterns, do patients in hospice and non-hospice settings receive different configurations of services? To test the hypothesis that hospice patients are more likely to receive psychosocial support services, a configuration measure is used which indicates that some level of psychosocial intervention has occurred if a patient has received one or more of an array of such services. To test the hypothesis that hospice patients will have less physician involvement, analysis will be done for various intervals or over the entire impact period (intake to death) on the basis of the number of physician visits. The prevalence of medical interventions can be addressed in the same manner; testing each medical intervention or diagnostic laboratory study separately. However, in view of the anticipated low frequency of any given service, clinically meaningful sets of services are combined. The resulting measure should provide an indication of the medical regimen to which a patient is exposed in his/her last months of life. Given the prevalence of pain and distress among terminal cancer patients and the emphasis hospice places on preventive pain control. a special analysis comparing the prescription patterns of analgesics and tranquilizers for hospice and non-hospice patients
National
Hospice
Study
Analysis
Plan
165
is being conducted. For analgesics, the diverse medications prescribed are converted to standard pharmacological analgesic dose equivalents and the analgesic dosage prescribed per kg body weight is compared for hospice and non-hospice patients. A similar approach is used with tranquilizers, merely comparing the likelihood of prescription by major type across the three groups. Since there may be changes in prescribed levels after the patient has been exposed to hospice for a week or more, principal comparisons are based upon data from the first follow-up visit. Since outpatient medications are often prescribed pm with guidelines informally provided by medical and nursing staff, the actual amount consumed in a 24-hr period is obtained during each follow-up contact. Consumption is therefore compared separately from prescription patterns. Actual consumption may vary considerably as a function of patient compliance as well as the practice of the provider. Nonetheless, it will be of interest if consistent differences in consumption between hospice and non-hospice patients with similar prescribed levels of analgesics are found.
Section VI-Organizational The organizational components:
and
facility
cost
and Facility Cost Analyses analysis
has
three
separate
but
inter-related
-Quantitative analyses of the relationship of reimbursement to changes in the organizational behavior of hospices. -Descriptive analyses of the relationship of reimbursement to the cost of hospice service and the revenue mix of hospices. -Qualitative analyses of the relationship of participation in the demonstration to changes in the organizational structure and goals of hospices. The analyses
to be conducted
address
the following
major
research
questions:
Hypothesis 1 Hospice growth and changes in the case-mix of patients served will be dSfSerent in demonstration and non-demonstration hospices, since an unrestricted retroactive cost-based reimbursement system in demonstration hospices provides an incentive for rapid growth. Hypothesis 2 Changes in the organizational structure, staff composition and the roles allocated to volunteers will difSer between demonstration and non-demonstration hospices; rapid growth may necessitate increased use of professional vs volunteer staff. Hypothesis 3 The unit cost qf hospice services will direr in demonstration and non-demonstration hospices; the overhead allocation system may encourage higher administrative costs and contracts with other agencies may be encouraged by reimbursement. Hypothesis 4 The rate of organizational change will difSer between demonstration and nondemonstration hospices.
ISSUES
In addressing
these research
AND
questions,
RESOLUTIONS
several
issues and considerations
arise:
-Evaluation of differential organizational change in a dynamic system. -Non-random selection of participating hospices and comparability of demonstration and non-demonstration hospices. -Change in demonstration hospices in anticipation of reimbursement. -Differences in hospice years. -Initiation of reimbursement prior to evaluation field efforts.
DAVIII S. GREEK et al.
766
Evaluating
d@erential
change in a dynamic
system
All hospices can be expected to proceed through a series of organizational changes. The evaluation must differentiate spontaneous change from change resulting from participation in the demonstration. Non-demonstration hospices provide an indicator of the natural history of change, i.e. the baseline to which demonstration hospice organizational change can be compared. Both the rate and magnitude of change are being assessed whenever possible. Non-random
selection
of’ participating
hospices
In selecting demonstration hospices, HCFA applied the criteria of competence and excellence, resulting in a non-random, potentially non-representative sample. In selecting the non-demonstration hospices, we applied similar criteria within the confines of our regional approach. Consequently, the organizational and facility cost analysis described in this chapter is not statistical in the commonly understood sense. We cannot generalize about behavior from statistics computed on the basis of data from these hospices, nor can we compute measures of the accuracy of our estimates. We can now view these data heuristically, however, to uncover relationships that may subsequently be explored in greater depth with a scientifically drawn sample. Change in demonstration
hospices
in anticipation
qf’ reimbursement
The 26 demonstration hospices submitted their proposals to HCFA in late summer, 1979 and were notified of the award within three months. From that point until the actual initiation of the reimbursement on October I, 1980, the hospices began preparing for the introduction of reimbursement. Conversations with hospice administrators indicate that internal procedures, record keeping, and even the organizational structure of the hospices changed markedly during this interim period*. To address this issue, the evaluation has qualitatively examined this phenomenon for the period prior to the demonstration and, where possible, prior to notification. DifSerences in the periods covered by ,fiscul years These differences exist among demonstration and non-demonstration hospices. The annual HCFA demonstration cost reports use existing fiscal years which vary from June 30 to December 3 1. This means that the first “year” cost may include 2-l 2 months of cost data. A full year of data for all hospices is available only from second year cost reports. Because of differences in the starting dates of fiscal years, the time periods covered by the second year vary as much as 9 months across the hospice. In order to control for this, the cost reports are being adjusted for area wage inflation in those hospices with a time period differential of 3 months or more. Initiation
of reimbursement
prior to evaluation jield eforts
In initiating evaluation data collection activities on August 1, 198 I, it is recognized that important changes in demonstration hospices occurred prior to this date. Conversations with hospices suggest that many had expanded their staffs and increased their patient volume. While many of the more specific hypotheses to be tested can be addressed utilizing propsective data, others must be addressed using a retrospective reconstruction of data from hospice files. Certain data which are available for the period October 1, 1980 through July 3 1, 1981 have been abstracted and analyzed. These data include the characteristics of patients served, staff time allocations and payroll data enabling time series comparisons across the full demonstration period.
_ *Despite the criteria to this period.
established
for the demonstration.
at least five hospices
were not actually
operational
prior
767
National Hospice Study Analysis Plan FACILITY
DATA
SOURCES
Facility-level data can be separated into four basic types: (a) aggregated patient data, (b) staff, (c) organizational, and (d) fiscal. The specific data sources relevant to each type are described in Appendix B. ANALYTIC The organizational
STRATEGY
and facility cost analyses
are to achieve two principal
(1) To provide facility cost data for use in the statistical analyses costs of hospice care. (2) To explore a variety of general questions about the relationship teristics to organizational behavior.
project
goals:
of the patient-level of facility
charac-
The discussion below outlines the specific approaches taken in analyzing organizational change and facility costs. There are three separate components to the analyses addressing these issues: (1) Quantitative analyses of the relationship of reimbursement to changes in the organizational behavior of hospices. (2) Descriptive analyses of the relationship of reimbursement to the cost of hospice services and the revenue mix of hospices. (3) Qualitative analyses of changes in hospice organizational structure and goals. The methods below. Analyses
and specific
of organizationai
hypotheses
to be tested
in each component
are described
change
The quantitative analysis of change in the behavior dependent variable domains:
of hospices can be grouped
into three
(a) Volume and mix of patients admitted. (b) Staffing patterns. (c) Mix of services provided patients. Impact on volume and mix of patients.
The following
directional
hypotheses
can be stated:
The number of patients served in demonstration sites will increase faster than in non -demonstration sites; The proportion of patients served for whom reimbursement is available wili increase more in demonstration than non -demonstration sites; Demonstration hospices with designated beds will have fewer patients dying at home than those without such beds. The basis for testing each of these hypotheses is an examination of differences in trends evidenced by demonstration and non-demonstration hospices. The final data analysis will involve a combination of: (1) graphic displays of trends in the data; (2) a carefully chosen structural model&presumably a time series model; and (3) a statistical test for differences in trends associated with the comparison groups. Fourteen months of aggregated patient data are available for both D and ND hospices, and an additional 10 months are available for D hospices. Plots of change in patient volume, case-mix and discharge disposition provide a clear indication of shifts over time. The statistical power of tests for differences in trends is limited. However, given the potentially large effects the reimbursement can have on organizational behavior, if these effects occur as hypothesized, they can be detected with even small samples. Analyzing changes in stafing patterns. Four issues are of interest in examining staffing patterns and utilization: -Use and role of volunteers. -Staff turnover rate and “burnout”. -Time spent on interdisciplinary clinical -Growth in the administrative function.
team activities.
768
DAVID S. GREEK
These issues will be examined
by testing
specific hypotheses.
These are:
The use of volunteers to deliver direct patient services will decrease in demonstration sites; the availability of reimbursement for direct services provides an incentive to have such services provided by paid staff. Stufl turnover rates and indicators of stress and burnout in demonstration hospices will be higher than in non-demonstration hospices; organizational growth is an additional stress. The amount qf time devoted to interdisciplinary team activities will increase in demonstrution sites; there is a separate cost allocation for interdisciplinary team functions. The proportion of totul stefl time devoted to administrative us opposed to direct service activities will increuse in demonstrution sites. The data base for testing these hypotheses is: a log completed by all paid staff in both D and ND sites monthly; volunteer records documenting the number of hours volunteers spend in direct care and administrative activities; quarterly salary and turnover records; and staff questionnaires which yield average hospice staff “burnout” scores as measured by a reliable attitude scale. The monthly percent change in the ratio of direct care to administrative hours provided by volunteers is plotted and tested as described above. The proportion of time direct care paid staff spend in interdisciplinary team meetings and for other administrative purposes is plotted both monthly and quarterly, and staff turnover can be compared across demonstration and non-demonstration hospices on a quarterly basis. Monthly data can be grouped into quarterly or bi-monthly periods to reduce fluctuations due to monthly idiosyncracies (particularly likely in small organizations), but this reduces the number of data points. Changes in staff “burnout” based on attitude scales are assessed by comparisons of average scores in the first administration (September, 1981) and the second administration (September, 1982). Analyzing change in the mix of services delivered. Based on the premise that organizations act to maximize reimbursement, the following hypotheses arise: The number of’ sociul service and bereuvement visits will increase in demonstration hospices; these are not ordinarily Medicare-covered services. The average length qf nursing visits will be longer in demonstration hospices because new standard “hospice care visit” charges are available in the demonstration. Service mix hypotheses are examined using the staff log data base. All direct care visits (in an outpatient setting) are recorded and monthly or quarterly statistical summaries of relevant dependent variables (e.g. percentage of all direct care visits coded as bereavement or social service) are available. Given differences in staff composition, prevalence of the use of outside contractors and the volume of direct care visits conducted by hospice staff themselves, particular care will be needed in making comparisons across organizations. Most of the hospices contract for various services with other agencies. This is probably more prevalent among hospitalbased (HB) and freestanding (FREE) hospices than home health agencies. Consequently, service mix statistics generated on the basis of staff log data forms completed by only hospice staff do not tell the whole story. Comparisons will be based only on organizations having similar staffing configurations.
Analyses
qf hospice costs und,finunciul
stutus
This component of the Study addresses how reimbursement status of hospices. Stated as a hypothesis, it may be anticipated that:
is related
to the financial
Unit cost qf’services will be higher in demonstration than in non-demonstration hospices. Personnel costs will be higher in demonstration than in non-demonstration hospices. Overhead costs wlill be higher in demonstration than in non-demonstration hospices.
National
Hospice
Study
Analysis
Plan
769
Unit cost of services will be higher in demonstration hospices. Unit cost of services will be analyzed for a wide range of specific services. However, problems arise in interpreting site comparisons within principal service unit costs. Therefore, aggregate costs for the total number of services provided is the principal measure of unit cost. This measure, the cost per hour of home service, reflects differences in the hospice’s production function such as the mix of professionals delivering service as well as differences in wage levels and productivity. Since hours of services is the common denominator, differences in management style or philosophy (e.g. the proportion of all home service provided by R.N.‘s) are reflected in the cost. Additionally, this approach overcomes any interpretational differences across hospices as to what each given service means. The primary analysis focuses on comparing demonstration and non-demonstration hospice service costs. Subsequently, other potentially important variables are introduced in an effort to understand the observed relationships. Although it is expected that a number of variables can affect unit costs of service, those initially anticipated to be important are: size, age of the organization, level of utilization, case-mix, use of contracts and the presence of other hospices in the area. Personnel costs will be higher in demonstration hospices. Variation in personnel costs are examined from two perspectives: average salary by job category and the proportion of dollars spent for direct care personnel. Preliminary indications suggest that salaries paid by demonstration sites may be higher than those paid by non-demonstration sites due to three factors: (a) the desire to expand quickly; (b) the lack of cost restraint or ceilings imposed by the demonstration; and (c) the substitution of paid staff for volunteer staff. Both salaries and the total dollars spent on provider staff may be higher. However, the percentage of dollars spent on direct care personnel may be lower in demonstration sites than non-demonstration sites due to expansion of administrative costs. The variables to be used to examine these issues will be average salary by job category, total direct care personnel expenditures, and the ratio of direct care salary costs to administrative salary costs. The analyses using these data will be performed along the same lines as those mentioned for cost per unit of service. Overhead costs will be higher in demonstration hospices. In addition to administrative costs, overhead includes items such as building, maintenance, and transportation. The demonstration’s liberal reimbursement procedures may encourage expenditures in these areas. Qualitative
analyses
The central organizational
of change in organizational
set of interrelated change is:
structure
issues which are the basis for the qualitative
analysis
of
-The reimbursement system creates opportunity for growth. -Reimbursement leads to hospice organization formalization. -Increased formalization leads to goal diffusion. -Reimbursement leads to increased professionalization. These issues form a causal line of reasoning, predicated on sociological, organizational and economic theory. The long term implications of behavior among reimbursed hospices are crucial for making national cost projects and policy recommendations. The quantitative organizational analyses seek to determine whether an accelerated pattern of change occurs due to the introduction of a special reimbursement system. Qualitative aspects of organizational change and expansion can also be analyzed. For example, the number of contracts that a particular hospice has may represent a diffusion of responsibility and control. Changes in patterns of communication or service protocols as seen in new procedures manuals, restructured organizational charts and the frequency of meetings, represent a more formalized organizational structure. Measures of these changes are available from agency documents such as annual reports, organizational charts, contracts and procedures manuals. Qualitative indicators of change in the organization are also obtained via interviews with hospice administrators.
770
DAVID S. GREEK er 01.
These analyses compare change by hospice organizational type and across demonstration and non-demonstration settings. Freestanding hospices may adapt to the introduction of the demonstration differently than home health agency or hospital-based hospices. Since they often have a broader volunteer base and are younger, freestanding hospices must rely upon the community for resources. The resources necessary to the freestanding hospice include labor, revenue and prestige. Without the guaranteed revenues of the demonstration, freestanding hospices devote considerable effort to attaining legitimacy in the community and to attracting resources. The introduction of a reimbursement system may cause a shift away from this effort. The implications of such a shift in terms of board composition, emphasis on community relations and the focus on recruitment and training of volunteers could be considerable. Home health agency-based (HHA) hospices have provided home care services longer than the freestanding hospices. They are less reliant on community resources. The introduction of a specialized hospice unit within the HHA could result in interorganizational conflict. Daily nurse visit quotas, a management tool in HHA’s to contain costs, may not be instituted as rigorously for hospice staff. The introduction of volunteers will, in many cases, be a novel function for HHA staff. At the same time, strategies for dealing with physician providers developed by the HHA may be transferable to the hospice unit, thus minimizing a problem freestanding agencies are likely to confront. Hospital-based (HB) hospices may have different sets of organizational issues to control and resolve, depending upon the placement of the hospice unit within the hospital’s organizational structure. The placement of the unit may impact directly upon the ability of the hospice to galvanize resources and to function as an autonomous unit. The direct line of authority for an HB hospice unit may be to a vice-president for administration. Alternately, the organizational chart may place the hospice unit at the same departmental level as Nursing. Social Services, Laboratory Services, etc. The ramifications of both models may become apparent when conflicts arise over resource allocation or the applicability of various work standards and procedures. Hospices with designated inpatient beds must resolve a series of economic. staffing and philosophical problems to maintain a viable program that continues to reflect the hospice philosophy. Pressures to keep beds filled run counter to the value placed upon home-based care. Additionally, these hospices may have to cope with the phenomenon of undesirable patients from other units being “dumped” on the hospice. Intramural strains such as these may test the viability of hospice in a hospital base and the organizational considerations may be critical to the outcome.
Section VII-National
Projections
Tests of hypotheses in the patient and facility level analyses should indicate whether hospice care and the demonstration affect terminal care costs, utilization and the share of expenses paid by various payors. If the impact on cost or quality of life is positive, it is important to project the impact to the nation as a whole. From the government’s perspective, in the current fiscal climate, cost implications probably take first priority. Thus, the major research question that could be addressed in the national projection is: Whut are the net direct costs (or swings), in total and to the Medicare program, reimbursement ,for hospice cure to ull hospice programs:~
@extending
Hospice reimbursement paid by the government
in the costs
similar to the demonstration can lead to changes for terminally ill patients in several ways, through:
-Changes in participation rates (the percent of eligible individuals who choose hospice). -Changes in patterns of utilization of hospice and conventional care patients (substitution of home care for institutionalization, for example). -Changes in facility unit costs (due to utilization level changes or organizational response to cost based reimbursement. for example).
Changes in the rate of development that exist. The national
projections
771
Hospice Study Analysis Plan
National
of hospices
and/or
the types of hospice
programs
will create:
(1) A baseline projection that forecasts hospice utilization, costs and Medicare payments based on existing patterns of utilization, participation rates, unit costs and facility characteristics. (2) A series of policy option projections, which extend the demonstration reimbursement program to the nation under different assumptions, including changes in behavior of potential hospice patients and the hospices themselves. The study will identify certain variables that are potential policy instruments for altering this behavior and test the sensitivity of our forecasts by varying policy instruments and other parameters. The discussion that follows considers several types of forecasting models and indicates which may be most helpful. The model finally chosen, the classes of variables included and the sources of data for these variables depend upon the results of the patient-level economic analysis and upon a full review of these results in the context of relevant policy parameters. DATA
SOURCES
Much of the data for these forecasts will come from the patient cost analyses (Section IV). Supplemental analyses of secondary data will provide a basis for correcting and generalizing to the nation the net cost of hospice care. These additional data bases include: -National Center for Health Statistics -Medicare History File. -The Cost of Terminal Illness Study. -Supplementary wage, health resource
(NCHS)
and demographic
ANALYTIC Forecasting
Vital Statistics.
data.
STRATEGY
models
There are numerous set of procedures: (1) Develop socioeconomic (2) Construct totals forecasted (3) Multiply
forecasting
models
available,
all of which follow the same general
forecasts for certain variables, such as population totals by demographic, and epidemiological characteristics. predictors, which are ratios of some form that describe how the population in step 1 relate to the variables targetted for forecasting. the step 1 variables by the relevant predictors to obtain forecasts.
Distinctions among techniques appear in step 2. The predictor ratios may be constructed using techniques that range from simple fixed ratios to sophisticated parameter estimates. These include: Single equation least squares regressions. The coefficients in these models calculate the total direct and indirect effects of exogenous variable changes. Feedback processes are not specified. Purameters in complex interactive models. For example, systems dynamics models and input/output models: the coefficients in these systems are applied simultaneously and measure direct and indirect effects of exogenous variable changes. Feedback processes are built into parameter estimates. Single value,fixed ratios. For example, the supply of physicians in 1990 can be predicted with an estimate of the population in 1990 and an estimate of the physician to population ratio in 1990. The single equation least squares regression technique study. Although a large interactive model may be attractive
seems most applicable to this from an analytical standpoint,
112
DAVII) S. GKEER ?i (11.
it requires a range and volume of data difficult to obtain in this study. Many of the model’s coefficients would have to be based on results of other studies, or on the informed opinion of experts. It also is very resource intensive to develop. In a model with internal feedback, this melange of coefficients would be a source of concern, because it would reflect studies over disparate populations at different points in time. In an interactive model, the stability of the entire system depends critically on coefficient values. The increase in the descriptive power of such a model does not justify the resources necessary to ensure internal consistency and produce credible results. On the other hand, single-valued fixed ratio forecasts oversimplify the situation. Their reliability usually cannot be judged because their statistical properties are often unclear. Moreover, it is impossible to determine the extent to which other variables in the system contribute to effects supposedly measured by a given ratio. For example, a simple ratio of 1000 inpatient days to 100,000 persons over 65 may imply that an increase of 100 65-t persons will increase inpatient days by one. In fact, changes may be more closely related to other variables, such as bed availability. The study will have available estimated coefficients of regression equations from the patient level economic analyses. They relate socioeconomic and demographic characteristics of patients to utilization and costs. They have two important advantages over most fixed ratio estimates: (a) They are estimated statistically, from a well-defined population, and the errors associated with these estimates can be measured. (b) In a regression context, each single coefficient isolates an effect without measured effects controlled. Thus, a regression coefficient for patients aged 65 and above predicts utilization for this age group, holding constant other factors such as sex, race, socioeconomic status and other variables not related directly to the patient, such as the health resources of the region. The reliability of the entire estimated equation can also be determined. be subject to increasing margins of error the farther one goes from known It ‘3 important to the quality of the forecast that this error be estimable.
The ,jorecasting process Figure 3 depicts a general model that forecasts hospice care. The steps are described below:
the cost to Medicare
Forecasts may sample values.
of reimbursing
Step 1: Estimate the population at risk in the ,jorecast year. Initial and target year populations by age, sex, and race are estimated for each county. Initial baseline population forecasts are developed for market areas (defined as counties) of study hospices and other hospices in existence during the study period. Target year forecasts are based on census forecasts. Step 2: Forecast cancer mortality rutes af‘patients arailuhle,for hospice during the target years. Trends of recent cancer mortality rates (if appropriate, by age, sex, and race) are used to estimate the size of the terminally ill cancer population in the initial and target years. In order to accommodate mortality rates to the analysis method described in Step 5, mortality data are converted to monthly rates. Step 3: Estimate hospice participation rutesjor terminally ill cancer patients. Since it will be impossible to rely on statistical estimates of participation rates, we shall have to depend on informed judgement to proxy these parameters. At this step, counties with hospice programs currently in place will be identified. Step 4: Compute the number oj’hospice und conventional care patients ,jor the initial and forecast years. The Joint Commission on the Accreditation of Hospitals (JCAH) surveys of hospices should provide baseline data for estimating participation, when combined with area cancer mortality statistics. Step 5: Forecast the proportions qf’hospice und conventional cure patients in discrete time interrals preceding deuth in the initial and target years. The patient level analysis uses two
I , I -
forecasts
Step 1
Population
’ I I ’ ’
I
rates of
l
I
Step 2
hospice
for
available
patients
Cancer
mortality
I I x1
l I
i=& I I 1 I I
I
I
I
3
’ ’
patients
care
' tional
’
’
‘-x&J
Sted
-4
in
before
death
’
’
in
care
patients
tional
of conven-
before
I yr:;ye
,
time
interval
each
patients
of hospice
1 Proportions
1 I 1 I 1 I
I 1
I
I
1 1 I
1 = 1 1 1 I
FIG. 3. Forecasting system
I 1 hospice I participa-1 I tion
I
f
I
I
1
I x
I
'Hospice
I , patients
Hospice
I
1 i i
I I
’ I I
'x
Hospice
intervals
patient-
care
tional
Conven-
Intervals
p,atient-
for National
=
I I
I
care
tional
I
interval
I total ’ costs I per
I
I Conven-
t
Cost Projections
x
I
I
I 1 I
1 =
I =
I :::;I I I 1 per I interval I
1 Hospice
’
’
costs
care
' tional
I
I
1 i
' Conven- 1
1
’ costs
I Hospice'
x
x
I
tional
conven-
tion of
I 1 care I paid by I I Medicare I
l
I I
, ,
1
Medicare
1 Propor-
1 I
1 paid
by
hospice
tion of
Propor-
I costs
1 l 1 1 I
I
I
costs
care
tional
I conven-
T Medicare
costs
hospice
1
' Medicare
I
I
I=
I
’
'
I
5
a
m
$
z
114
DAVID S. GKEER et ul.
methodologies for costing hospice treatment; the first is based on total costs per case and the second is based on per case costs constructed from costs for weekly and biweekly intervals preceding death. Cost projections can similarly be made on a case or time interval basis. A decision on the appropriate methodology must await completion of statistical tests in the patient level analysis. Step 6; Compute “patient intervals” for hospice and conventional care patients in the initial and target years. This computation combines total cases estimated in Step 4 and the proportions in Step 5. Step 7: Estimate total cost by case or time interval ,for the average patient in each demographic/geographic group. Costs per time interval and per case are estimated in the patient level regressions. Costs for the target year are inflated from the initial year at an assumed rate of increase based on the recent experience of (and future forecasts of) the medical care component of the Consumer Price Index. Step 8: Compute total forecasted costs of treating terminally ill cancer patients in hospice and conventional cure progrums. This computation involves multiplying patient-weeks (or total cases) (Step 6) by the appropriate costs per interval (or per case) (Step 7) and summing for hospice and conventional care patients. At this stage, “costs” are defined as Medicare defines them, since this is the basis for the patient cost analysis. Appropriate adjustments must be made for costs (charges) not measured in discrete intervals (such as physician charges). Step 9: Estimate the proportion of hospice and conventional care costs of treating terminal cancer that is reimbursed by Medicare. The baseline Medicare reimbursement assumption will be that Medicare pays all hospice costs for Medicare-eligible patients, as it is doing in the demonstration. Thus the Medicare fraction of total hospice costs depends entirely on the proportion of Medicare to total patient intervals. For conventional care, Medicare reimbursement and non-Medicare costs are estimated from patient cost and the payor mix analyses. Step 10: Compute,forecasted Medicare reimbursement for terminally ill cancer patients in hospice and conventional care programs. This computation combines total treatment costs (Step 8) with the proportion of forecasted Medicare reimbursable costs (Step 9). Step 10 totals depend on the underlying assumptions used about demographic trends, costs, and federal policy. Total Medicare program costs in this simulation include both conventional care and hospice costs under specific assumptions used about hospice participation. The net costs (or saving) of a national hospice reimbursement program can be estimated by comparing simulated national hospice coverage program costs to an estimate of costs without full hospice coverage. This methodology can also be used to compute total costs and, with modification, is applicable to other cost parameters. METHODOLOGICAL
ISSUES
There are a number of questions that must be answered before the forecasting model is complete. Statistical analysis of the patient level costs and discussion of the results with other experts will determine the resolution of these issues What are the proper
assumptions
about a baseline forecast?
The methodology discussed above projects the cost implications of a nationwide hospice program. The baseline forecast assumes that the patient level model’s predictors remain unchanged. In essence, this means that hospice participation and market penetration rates will be developed in consultation with project advisors. Other factors such as eligibility criteria under the demonstration, utilization patterns and costs are assumed to remain the same. However, certain assumptions about characteristics of hospice programs in the forecast year must be made. Should we project the rate of hospice growth that prevailed before the waiver went into effect? Should we assume that regional differences in hospice market penetration and growth are perpetuated? Do we add any assumptions about
National
Hospice
Study
Analysis
Plan
775
hospice entry into areas that now have no hospices (virtually none)? The simplest assumption is that the capacity of existing hospice programs will expand to meet demand which will grow or contract as a consequence of changes in cancer death rates. Should “charges”
or “costs”
be forecasted?
The research issue here involves costs to the government of a national waiver program. We will study Medicare’s share by estimating payments, by source, relative to total charges in the patient economic analysis. One might argue that it is logical to project charges to the target year and then apply this estimated Medicare share ratio to the appropriate charge data. However, we argued previously in the patient cost discussion that multivariate estimates of utilization patterns, weighted by standard Medicare unit costs, are likely to be more precise than estimates of charges. Since neither the theory nor the data exists to explain variations in charges among facilities and services, projections should be constructed in terms of costs; any adjustments to the projections to secure Medicare costs should be done as a final step in the process. What are the important determinants of cost.7 The patient-level cost equations will estimate coefficients that link patient and PCP characteristics, a limited number of physicican characteristics, area health and socioeconomic profiles and, for hospices, facility characteristics to patterns of utilization and cost. The regression output will include standardized coefficients that, in general terms, indicate how important an individual coefficient is in determining variations in the dependent variable. The patient demographic characteristics may contribute most to a statistical explanation of cost and utilization. If this is true, the forecast should be based on projected demographic data in detail sufficient to make full use of the estimated coefficients. On the other hand, the analysis of hospice patients may reveal that facility characteristics are more important than patient characteristics. If this is the case, the model would be less well adapted to forecasting. Facility-level detail is available for hospices but not for conventional care programs. Without a statistical basis to judge the importance of facility-level variables in determining cost variation for conventional care patients, we must rely on the literature. In order to make full use of the available hospice facility information, we should first project the characteristics of hospice facilities in the forecast year. This task is more difficult than forecasting demographic characteristics of the poulation, in part because the dynamics of population change are better understood. Forecasts of unit costs for conventional care could be grafted onto the estimates made for conventional care utilization in this study. Should facility variables be important, our current position is that they should be taken into account both for hospice patients and for conventional care patients. In order to do this, predictors of facility characteristics’ effects on costs would be developed from other studies. Assumptions would then be made about the kinds of conventional care facilities patients would use. Characteristics of these facilities would be used to forecast unit costs in the target year. What are the important parameters?
policy
parameters,
and what
are reasonable
ranges for
these
We can test the sensitivity of forecasts by varying input values (size and composition of patient groups, for example) and assumed behavioral coefficients, such as participation rates. It is particularly important to consider the effects of changes in variables that can be shaped by government policy. These include: -Timing of intake into the hospice program. -Kinds of services covered by Medicare, for institutional). -Levels of cost sharing.
specific
settings
(home,
176
DAVIII S. GREER ef d.
Changes in assumptions about the nature of Medicare reimbursement will affect both the distribution of patients in hospice programs by length of participation and the mix of services these patients consume. If, for example, Medicare sets a limit on the number of days of hospice care it will finance, this could delay the timing of the decision to participate and shift the distribution toward short stays. If costs vary over intervals, such a shift wili affect total cost whether or not numbers of patients increase or decrease. If Medicare extends reimbursement to a wide range of home care services, total costs can change because patterns of utilization by service and setting might change. From another perspective, a general increase in Medicare benefits for home care may affect utilization of hospice and conventional care patients alike. Broader home care coverage may increase hospice participation, to the extent that some patients select hospice as a less costly way of getting home care. There is no meaningful way to model the effects of policy changes on participation, average days of participation, and patterns of utilization. Rather, we shall have to develop and precisely specify assumptions about these effects. Sensitivity analyses will be conducted to determine the consequence of the various assumptions. What is the appropriate jorecast period.? Choosing a target year, or years, depends both on the value of a particular choice to policy making and the reliability of the forecasting tool. Policy relevance is determined by agency planning horizons and the Federal budget cycle. Forecast accuracy can be improved if sample data allow estimates over a sufficient number of time intervals. The observations in this study are selected over a short, i.e.. 18-month, time frame. Although we shall try to isolate patterns of change by estimating equations with three time variables (based on six month cohorts of patient observations), we shall not have enough time services points to be confident about forecast accuracy several years into the future. Thus, we shall have to make qualitative statements about accuracy. based on generalized measures of the precision of our estimates. REFERENCES I.
2. 3. 4. 5. 6.
7.
8. 9. 10.
General Accounting Office: Hospice Care-A Growing Concept in the United States. Washington, DC: U.S. General Accounting Office, HKD-79-50, March 6. 1979 Joint Commission on the Accreditation of Hosoitals: JCAH Hospice Proiect Interim Reeort. Phase 1. _ Chicago, IL: Joint Commission on the Accredit&ion of Hospitals,-1981 ” National Hospice Organization: Locator Directory of Hospices in America, 1981-1982. McLean Virginia: National Hospice Organization. 1982 Buckingham RW, Lupu D: A comparative study of hospice services in the United States. Am J Pub1 Hlth, 12: 455463, 1982 National Hospice Organization: Standards of a Hospice Program of Care 6th revision. McLean, Virginia: National Hospice Organization, 1979 National Cancer Institute: A Cost Analysis of Three Programs, Hospice: Hillhaven Hospice, KaiserPermanent Hospice, Riverside Hospice. Executive Summary. Kaiser-Permanente Medical Care Program, Southern California Program, 198 I Mor V, Sherwood S, Birnbaum H, Morris JN, Greer DS: The National Hospice Study: A Description of Participating Hospices and the Patients They Serve. Providence. RI: Brown University (unpublished manuscript), 1982 Belsley DA, Kuh E, Welsch RE: Regression Diagnostics: Identifying Influential Data and Sources of Collinearity. New York: John Wiley, 1980 Draper N, Smith H: Applied Regression Analysis, 2nd edn. New York: John Wiley, 1981 Morris JN, Gutkin CE. Sherwood CC, Sherwood S: Overview of SIMRAN, procedures. In Alternative Paths to Long Term Care. Sherwood S. Morris JN. et crl. (Eds). Chapter 3 (Appendix). Final Report to AoA Grant #90-A-1666. 1982
Appendix A-Abridged Description of the Hospice Demonstration Progress for Eligible Medicare Patients What follows is a synthesis of the Demonstration Project Provider Manual and the relevant provider letters distributed to participating hospices by the Office of Direct Reimbursement of HCFA. This is not an official interpretation and is for the use of data collectors only.
National
Hospice
Study
Analysis
Plan
777
Iniroducrion
The Medicare demonstration project alters certain provisions and regulations of the Medicare insurance aspects of existing Medicare regulations on an program. It is a general practice for HCFA to “waive” experimental, demonstration basis, simultaneously studying the effects this has on patients (beneficiaries) and costs to the program. The hospice demonstration involves a complex set of inter-related “waivers” that can be grouped into three distinct classes: First, reimbursement is provided for new services (home respite, bereavement counseling and assessment, outpatient prescription drugs and biologicals, continuous care, and institutional respite services). Second, Medicare eligibility criteria are modified, a six-month terminal prognosis replacing the “essentially home-bound” criteria for inpatient skilled nursing care. Third, certain services delivered to the family or primary care taker of the Medicare/Medicaid beneficiary are covered; these include bereavement and respite services as well as counseling and education to facilitate care of the patient. Medicare beneficiaries are eligible for these waivers if they have both Part A & B coverage, have been certified by a physician as having a life expectancy of 6 months or less and sign informed consent. Covered under the demonstration are billable outpatient, home delivered and inpatient services provided by participating agencies conforming to specific cost reporting requirements. For a service to be billable it must meet the service definitions in the Provider Manual and have a cost associated with it (i.e. provided by paid staff). No billed physician services are covered under the demonstration; however, physicians may bill under the regular Medicare program. That is. receipt of services from a demonstration hospice does not preclude the patient from receiving other Medicare covered services under the regular program (e.g. physician visits, acute hospitalization, skilled nursing facility and outpatient clinic). What follows is an enumeration of the services available under the demonstration and the current caps or conditions for reimbursement, In-home
service
(I) Nursing includes providing skilled care, teaching patient/PCP health treatments and providing counseling. limits: I5 visits or 40 hr/month unless accompanied by justified documentation. (2) Home heulrh aide includes provision of personal care and/or household cleaning. limits: 8 hr/day or 100 hrimonth unless justifying documentation. (3) Homemaker service-assistance in personal care, etc. limits: 8 hriday or 100 hr/month unless justifying documentation. (4) Continuous cure-nursing, health aides, or homemaker services around the clock. limits: 120 hrimonth unless documentation; maximum of 5-day limit regardless. (5) Physical lherupy provided by licensed therapist under MD orders. (6) Speech rhrrup) provided by licensed therapist under MD orders. (7) Occupational therupy provided by licensed therapist under MD orders. (8) Sociul sercices provided by or under supervision of an MSW. (9) Nutritiona/ seroices!‘consultation provided by dietitian either through patient visit or in consultation to the
Hospice Interdisciplinary Team. (IO) Bereucrmenf usse.wment counseling provided by “a bereavement team member trained to recognize symptoms” as determined by the Hospice Interdisciplinary Team. limits: reimbursement for only 3 visits; no group counseling or bereavement visits by volunteers are reimbursed. (I 1) Prescription drugs and biologic& are reimbursed according to Medicaid cost limits; excludes nutritional supplements and over-the-counter drugs, creams, etc. (I 2) Durable medical eyuipment includes all regularly Medicare covered DME plus certain safety and self-help devices. (I 3) Medical supplies-regular Medicare covered supplies. (14) Home respire-provision of services to patient when PCP is unable to provide normal care and supervision on a temporary basis. limits: 72 hr/episode. Inpatienl
sercices
(I) Inpatient hospice. Short term inpatient hospice care in a designated hospice unit or in a hospital section in which hospice-specific costs can be isolated. (2) Institutional respite sewice. Care provided patient to relieve PCP on a short term basis in a certified SNF, ICF, or inpatient hospice. Note: Some hospices have contracts with SNF and ICF homes to provide this care which is billed through the hospice demonstration. In addition to the specific definitions and limits for billable services, there are provisions covering the nature of allowable administrative, or overhead, costs allowable under the demonstration. These include patient expenses, pharmacy consultation, psychologist/psychiatrist consultation as well as the Hospice Interdisciplinary Team (in which the hospice physician generally participates). Demonstration hospices receive coverage of the cost of billable visits to demonstration patients. The proportion of the overhead or administrative component of the unit cost of each billable service that is reimbursed under the demonstration is related to the ratio of demonstration to non-demonstration hospice patients served. Hospices submit patient specific bills to HCFAjODR for services provided to demonstration patients. However, they are paid via period interim payments (PIP) which are based on quarterly cost reports and utilization statistics. The PIP level will change as a function of fluctuation in service volume and the proportion of all services provided to demonstration patients. The bills also serve to monitor the hospice’s compliance with specific service limits. Final reimbursement, or settlement, is determined on a retrospective basis for reasonable costs incurred based on year end cost reports which will be audited by the area Medicare fiscal intermediary.
DAVID S. GREER et ul.
778
Appendix B-National
Hospice Study Data Sources
Both primary and secondary data sources are used in the various analyses being conducted as part of the National Hospice Study. These data correspond to patient-level analyses, facility-level analyses and national projections, The various levels of data are analytically inter-related as described in relevant sections of the analysis plan. This appendix contains brief descriptions of each data source and stipulates its mode of administration if it is a primary data source. Patienl
data sourc~.~
What follows is a description of each data form relevant to the patient-level analyses of impact on quality of life and health care costs as well as the comparisons of the terminal care intervention to which hospice and non-hospice patients are exposed. The measures contained in each data form are used as either independent or dependent variables in these analyses. (See Fig 3 for a graphic display of the data gathering flow). Mediwl record ahstruct. A one-page review of medical status is used to document primary site. histological diagnosis and the presence of metastases. Also captured are past therapies, date of initial diagnosis and other medical conditions. Patirn/ inrake and discharge fbrms. These are available from existing hospice records or are completed by the data collector as a part of the initial interview battery in both hospice and conventional care settings. In addition to documenting the data of Study entry and termination (death), these records contain basic demographic data and measures describing patients’ functional status on admission. Initial patient intewiew /iwm. This is a structured guideline for a personal interview. It contains the patient quality of life dependent measures as well as some of the patient independent variables. In order to reduce the patient response burden, many of the independent variables are incorporated into the initial PCP interview. In the event that the patient cannot respond to the interview. selected items are obtained from the PCP. Initial PCP interrietv f&w. A guideline for the patient’s principal care person. It includes independent variables concerning the helping network, the existence of other obligations of the PCP and demographic characteristics of the PCP. In addition, information concerning the patient’s knowledge of his/her disease and prognosis and baseline data on family quality of life are obtained. PCP Assrs.w~enf. A paper and pencil questionnaire completed at the initial and each subsequent visit. In it the PCP assesses the patient’s quality of life, the use of medical and psychosocial services. patient symptoms. the level of informal support provided and the amount of time the PCP lost from work. Patient ,fb//o+v-up intervie+t.. This interview is repeated at each follow-up session until the patient’s death. It includes the dependent variables encompassed in the initial patient interview. PCP fi&n-up interview. This brief interview is conducted at the time of the second patient follow-up visit. It contains the principal dependent measures for the family quality of life analysis. Medication prrscriptmn and ufilizarion /arm. In addition to prescribed dosage, the actual amount of medication consumed in the previous 24-hr period is dctermincd. The data collector checks the containers of all medications and ascertains utilizations of those medications of interest in the Study. PCP hrrearement interview. This interview takes place 9@lOO days after the patient’s death. It contains the same set of dependent variables as the PCP follow-up interview, in addition to sets of questions concerning the grief experience. Patient
cost. paJwent,
and i~f&mal
support
datu
The principal source of patient cost and utilization information are weekly service records and checked against bills and records for completeness by the data collector.
maintained
by PCP’s
(I) A Service Record is maintained by each PCP. This instrument records inpatient hospital and nursing home days, physician visits, outpatient visits, home care visits (and hours for certain providers), visits from volunteer agencies. expenditures on drugs and supplies and total out-of-pocket treatment expenditures for the week. (2) After the patient‘s death. the data collector transfers Service Record information to summary forms after verifying it with bills, receipts. vouchers and, where pertinent, hospice records. Summary Inpa/ienr
forms,
constructed
charge
from Service
Record
information,
include:
summtrries.
(One for each hospital or inpatient nursing home stay), includes utilization reimbursed services and utilization/charge information for non-Medicare services. Outpatienr, physician, home care summaries. These allocate all utilization to the last week of the patient’s life and preceding bi-weekly periods. Our-q/-pocket c~pmse, drug, und supply summaries. The record expenses by week and for the Study period. Vo/un/eer .summay. This records visits and hours from community volunteers.
information
for Medicare
(a) Additional information on informal support, insurance coverage and utilization the PCP Initial Interriett, and the Patient Intake Forms. (b) These primary data are supplemented by Medicare infbrmufion on Medicare
MEDICARE Demonstration
CLAIMS
DATA
FOR
MEDICARE
prior to intake comes from reimbursed
services.
PATIENTS
c1rtim.s
Data on claims for services provided under the demonstration are obtained from Office of Direct Reimbursement (ODR) bill files. These contain information on utilization of services and charges for equipment, supplies and drugs.
National Regulur
Medicare
Hospice
Study
Analysis
Plan
179
claims
Data on (regular) Medicare services are obtained from two sources. Inpatient stay and home health service information is drawn from the Bill History file for the follow-up sample and a supplemental sample of conventional care patients. Copies of Provider Claims for Medical and Other Health Services (SSA-1483) and for Services by Physicians (SSA- 1554) are made as claims of follow-up sample patients are processed by the Office of Research, Demonstration and Statistics. Subsequently, they are sent on magnetic tape to the project for inclusion into the overall data base. The physician suraey. A short telephone interview is conducted with a sample of the physicians indicated in the record as primarily responsible for the patient’s medical care. It solicits attitudinal information regarding narcotic use and treatment for the terminally ill and demographic data on the physicians themselves.
FACILITY Facility-level organizational, Aggregated
data can be separated and (d) hscal.
patient
into
DATA four
basic
SOURCE types:
(I)
aggregated
patient
data,
(b) staff,
(c)
duiu
to both demonstration and non-demonstration hospices, a standard Intake and is completed and incorporated into the data base system. These records describe the overall hospice patient population in terms of basic demographics, income and functional status. At the facility level, they are aggregated to describe the monthly (quarterly) admission cohort of each hospice. For all patients
Discharge
Summarv
admitted Form
Hospice SlqfJ‘ Atfitude QuestionnaireA questionnaire is completed by staff (salaried and volunteer) at both demonstration and non-demonstration hospices at the beginning and end of the evaluation period. Provider Log. The Provider Log is a time sheet for hospice employees. It is completed monthly by all paid staff. The form provides a record of: (1) services rendered and tasks performed for outpatient cases; (2) total time devoted to inpatient cases; (3) time devoted to patient-related administrative activities; and (4) general administrative activities. Hospice Volunteer Statistics. In both demonstration and non-demonstration sites. evaluation staff gather information each month on volunteer staff use. The data include: the number of active volunteers, the number of patient visits made by volunteers. hours of patient care and hours of non-patient care provided by volunteers. St@ Salary und Turnover Records. This form is completed quarterly for demonstration and non-demonstration hospices. It records the average salary for five different categories of paid staff, the number of new staff hired. and staff resignations by category for each period. Organixtionul Hospice
datu
Charactrri.rtic.s
Form. This form summarizes certain data describing the structural characteristics of the hospice organization. e.g. ownership, hospice type, prior patient census data, community population served. services and programs provided. staff service mix, eligibility and discharge criteria, referral information, and contractual agreements. &.xecufive Director Interview. This instrument is a guide for the interviewer (Regional Manager) in obtaining qualitative information from the executive directors of both demonstration and non-demonstration hospices. It supplements quantitative information and information available in hospice documents (e.g. organizational charts, by-laws and procedures manuals, copies of incorporation papers, etc.). It addresses the history and background of the hospice, community involvement. etc. Three such qualitatively-oriented discussions occur and serve to place the quantitative information in context.
Fiscul data Hospice Demonstrution Stutement of Reimbursable Costs. The Hospice Demonstration Statement of Reimbursable Costs is a requirement of the demonstration and is completed by all demonstration hospices. It has all the detail of standard Medicare Cost Reports including: total cost, overhead costs, contract costs and unit cost for each service offered by the hospice. Data acquired from non-demonstration hospices are comparable. The Hospice Statement of Reimbursable Costs is simulated on the basis of summary service statistics maintained by the hospice or compiled from staff time sheets collected by on-site evaluation staff. serve as a means of documenting the non-demonstration Worksheets entitled “Composition of Expenses” hospice costs based upon existing records such as budgets or Medicare Cost Reports. The data on these forms are examined and reclassified by evaluation staff accountants into the appropriate categories based on the Medicare Hospice Demonstration requirements such that the cost data of demonstration and non-demonstration sites are comparable. The basis for the classification of services and costs are: Hospice Srutisrics. Data coordinators in non-demonstration sites assemble records on service utilization by service category. The source of these data are weekly time sheets completed by hospice staff either specifically for the evaluation or the existing record system. Stu/ement of Reoenue and Expenses. This statement of all sources of income and total expenditures of both demonstration and non-demonstration hospices is based upon generally accepted accounting procedures. In demonstration sites, cost data are completed automatically as part of the hospices’ participation in the demonstration.
780
DAVID S. GREEK et al.
To minimize the burden of data collection in non-demonstration simulated cost report. Non-demonstration sites assemble the budgetary the worksheets.
SECONDARY
DATA
hospices, evaluation staff and financial data needed
prepare the to complete
SOURCES
Much of the data for these forecasts will come from the previously discussed IV). Supplemental analyses of secondary data will provide a basis for correcting the net cost of hospice care. These additional data bases include:
patient cost analyses (Section and generalizing to the nation
-National Center for Health Statistics (NCHS) Vital Statistics. -Medicare History File. -The Cost of Terminal Illness Study. -Supplementary wage, health resource, and demographic data. NCHS
Vital StaMics
The National Center for Health Statistics Division of Vital Statistics regularly causes of death (four digit ICDA code) by geographic region and demographic be the main vehicle for projecting the number of terminal cancer patients to the mortality will be examined to develop, as necessary, adjustments to historical Medicare
History
prepares mortality tables of the characteristics. These data will nation. Recent trends in cancer data for future projections.
File
The Medicare History File, maintained by HCFA, contains a combined record of all Medicare activity for a 5”/, sample of Medicare patients. The Medicare History File is used to develop regional indices of costs and utilization for Medicare services. Cosr of Terminal
Illness Stu&
This data base, available through the Blue Cross and Blue Shield Associations, presents the health care costs incurred by terminal patients under age 65 during their last 6 months of life. It includes claims files from three areas-Michigan, Indiana and Atlanta, Georgia-and captures all institutional and physician services billed for subscribers between 1 January 1978 and 31 December 1979. Together with the supplemental study of the cost of terminal cancer covering Rhode Island deaths in 1980 and 1981. these data constitute a unique validation resource. The JCAH
National
Surt~e~ sf Hospices
The Joint Commission on Accreditation of Hospitals (JCAH) is conducting a survey of some 1000 organizations during 1982 regarding their hospice activities, staff, patient mix and volume. These data will be used to extrapolate the facility-level analyses and to ascertain the patient participation rate.
OTHER The U.S. Census routinely publishes population available. The Area Resource File provides data health status characteristics.
DATA
SOURCES
data forecasts. Those based upon the 1980 census should be on area socioeconomic, demographic, health resource. and