Hospital Readmissions and Repeat Emergency Department Visits Among Children With Medical Complexity: An Integrative Review

Journal of Pediatric Nursing (2013) 28, 316–339

Hospital Readmissions and Repeat Emergency Department Visits Among Children With Medical Complexity: An Integrative Review Shannon M. Hudson RN, BSN, CCRN, PhD(c) ⁎ Medical University of South Carolina, Charleston, SC

Key words: Patient readmission; Emergency service, hospital; Chronic disease

Children with medical complexity (CMC) have chronic conditions, intense healthcare needs, and high healthcare utilization. Proposed changes in the healthcare environment initiated by the Affordable Care Act have led to efforts toward preventing hospital readmissions. The purpose of this integrative review is to explore the current empirical literature and examine how hospital readmissions and repeat emergency department visits have been studied among CMC. A computer database search and ancestry search were conducted, resulting in a sample of 26 studies. The results of the integrative review are presented along with gaps in the literature and implications for nursing practice and research. © 2013 Elsevier Inc. All rights reserved.

CHILDREN WITH MEDICAL complexity (CMC) are a population of chronically ill children with extensive health care needs, high levels of health care utilization, and substantial costs of care. As a subpopulation of children with special health care needs (CSHCN), CMC have been described using a number of terms including medically fragile children, children with complex chronic conditions, and medically complex children. Whereas CSHCN have or are at risk for chronic health conditions and have health care needs greater than children in general (McPherson et al., 1998), CMC have even higher, more intensive health care needs. Among these needs are high levels of health care utilization which include services from specialists and other providers, multiple or frequent surgical interventions, or frequent use of tertiary care services (Cohen et al., 2011). CMC have elevated emergency department (ED) visit rates and utilize more hospital resources, especially pediatric inpatient hospital resources (Beck, Khambalia, Parkin, Raina, & Macarthur, 2006; Bramlett, Read, Bethell, & Blumberg, 2009; Reynolds, Desguin, Uyeda, & Davis, 1996; Simon et al., 2010). ⁎ Corresponding author: Shannon M. Hudson, RN, BSN, CCRN, PhD(c). E-mail address: [email protected]. 0882-5963/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.pedn.2012.08.009

Because of this increased use of resources, care expenditures for CMC are greater than for children as a whole, with the greatest proportion of costs attributed to inpatient hospitalizations (Ireys, Anderson, Shaffer, & Neff, 1997). According to Buescher et al. (2006), Medicaid payments for technology-dependent CMC have been as high as $69,906 per child per year compared to well-child annual Medicaid payments of $3181 per child per year. These cost burdens of care for persons with chronic conditions may have long term implications as the population of CMC ages. For example, some adults with chronic childhood illnesses such as cystic fibrosis and cerebral palsy continue to seek care at children's hospitals and may collectively incur over $500 million dollars per year in pediatrician-provided hospital care (Goodman, Mendez, Throop, & Ogata, 2002). In studies examining health care utilization among CMC and other populations, one research focus has been identifying population characteristics and other factors associated with hospital readmissions and ED visits. Variables such as age, diagnosis, length of hospital stay, insurance status, and race/ ethnicity have been investigated as predictors of unavoidable and potentially avoidable hospital readmissions in children and adults; presence of one or more chronic conditions has been consistently related to increased hospital readmission rates

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(Beck et al., 2006; García, Yee, Chan, & Romano, 2003; Lagoe, Noetscher, & Murphy, 2001; McKay, Rowe, & Bernt, 1997; Oster & Bindman, 2003). Despite this growing interest in researching the link between population characteristics and hospital readmission rates, a comprehensive literature review examining hospital readmissions and repeat ED visits among CMC is needed. This integrative review explores the current empirical literature, investigating how hospital readmissions and repeat ED visits have been studied in CMC, identifying gaps in the literature, and outlining implications for nursing practice and potential avenues for future research. The integrative review was guided by the following research questions: Among studies of hospital readmissions and repeat ED visits in CMC, what were the characteristics of the populations, in which settings or contexts were the investigations conducted, and how were hospital readmissions and repeat ED visits as measures and outcome measures investigated?

Design

Theoretical Frameworks

A comprehensive search of the literature was conducted in May 2011 beginning with an iterative search of Ovid/ MEDLINE, PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and PsychINFO databases. No date limits were set. The following Medical Subject Headings (MeSH) terms, CINAHL headings, thesaurus terms, and keywords were used: patient readmission; readmission; hospital readmission; chronic illness; chronic disease; emergency service, hospital; rehospitalization; and emergency department visit*. The search yield was 900 articles, excluding cross-citations. The abstract of each article was reviewed for inclusion in the sample; the full article was obtained and reviewed when no abstract was available or in situations when inclusion could not be determined by abstract review. Inclusion criteria were as follows: published reports of studies investigating hospital readmissions and repeat ED visits in populations that included CMC ages 0 to 21 years, and publication in English. Exclusion criteria were as follows: unpublished abstracts, dissertations, manuscripts, or conference proceedings; theoretical, expert opinion, editorial, or any other articles that did not report empirical study findings; sample included participants greater than 21 years of age not independently reported and analyzed from younger participants. Twentytwo articles were included in the sample. Ancestry searching was also performed and resulted in the inclusion of four additional articles. Thus, the final sample included 26 articles reporting studies of hospital readmissions and repeat ED visits in CMC.

The Expanded Chronic Care Model (ECCM) and social ecological theory (SET) served as the theoretical frameworks for this study, providing the lens through which the review sample was evaluated and organized. The multi-level approach exhibited by both models has been successful in addressing health care and health behavior problems in chronic illnesses (Barr et al., 2003; Sallis, Owen, & Fisher, 2008). Use of SET as a theoretical framework offered a broad, multi-level perspective during the literature review, while use of ECCM provided greater structure and detail. A central tenet of SET that guided the review is that behavior can be explained by the interactions among multiple levels of influence including the intrapersonal, interpersonal, community, societal, political, and environmental (Sallis et al., 2008). According to Bronfenbrenner (1994), interactive relationships occur within the individual as well as within and among the levels surrounding the individual which include family and peer groups, school and work, and culture and society. SET has been proposed for use in health promotion in that the multiple circumstances found at the personal, cultural, societal, and environmental levels influence health outcomes such as well being (Stokols, 1996). The ECCM was developed by Barr et al. (2003) as an elaboration of the Chronic Care Model (Wagner, Davis, Sachaefer, Von Korff, & Austin, 1999) that places greater emphasis on prevention, health promotion, community, and population health. According to the ECCM, connections between the health care system and the community are pivotal. Additionally, the ECCM is conducive to consideration of the influence of the social determinants of health and health inequities on health problems. SET framed the current review as the multiple levels of influence and the interaction among levels were considered at each step of the review process. The studies reviewed were compared to the components and outcomes of the ECCM.

The design for this study followed Whittemore and Knafl's (2005) modified framework for integrative reviews. The purpose of the review, the problem of interest, and the related variables were identified, and a theoretical perspective through which the problem could be viewed was chosen. The literature search was performed using more than one search technique, and data evaluation was conducted. Data analysis, data extraction, and comparison of data were performed. After verification with the original data, conclusions regarding the patterns or themes in data were presented.

Methods Search Criteria

Sample Published study reports included in the sample are listed in Table 1. Of the 26 sample articles, 23 were quantitative studies, 2 were qualitative studies, and 1 was a mixed methods study. Two study reports were independent analyses of the same study population (Liese et al., 2003;

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Table 1

Sample of study reports included in the integrative review. Purpose

Setting

Design

Procedure

Results/findings specific to hospital readmissions or repeat ED visits

Berry et al. (2009)

To identify and describe health outcomes, hospital utilization, comorbid conditions, and other characteristics of children after tracheostomy

Pediatric Health Information System (PHIS): large database of 36 freestanding children's hospitals across the US

Retrospective cohort

– Children and comorbid conditions identified from ICD-9 tracheostomy codes and followed across admissions using identification code – Outcome measures assessed for each hospitalization during the 5year follow-up period

Berry et al. (2011)

To describe hospital utilization, clinical characteristics, and demographic characteristics of children with repeat hospitalizations and to evaluate the reasons for readmission

PHIS: large database of 37 freestanding children's hospitals across the US

Retrospective cohort

– Children followed through multiple admissions to the same institution using identification code – Children with at least one admission in 2003 followed through 2008, identifying readmissions – Sample characteristics and outcome measures obtained via database

– Mean number hospitalizations 3.8/child – Mean total days in hospital 32.3 – 45% with hospital readmission within 30 days – $529 million in charges for hospitalizations – 74.4% nonelective admissions – 46.1% of admissions for respiratory problem – Children with neurological impairment longer LOS (pb0.0001) and hospital days (p=0.003) – Children with ventilators fewer readmissions within 30 days (pb0.001) – Children discharged to rehab facility fewer readmissions within 30 days (pb0.001) – Children ≤1 year old more readmissions within 30 days compared with older children (pb0.001) – No difference found in hospital resource use by insurance type – 9237 children with 4 or more readmissions – Median 37 days between admissions – Children with 4 or more admissions represented 2.9% of the cohort, 18.8% of admissions, 23.4% of bed-days, 23.2% total charges – Age 13–18 years (pb0.001), public insurance (pb0.001), non-Hispanic black (pb0.001) associated with greater readmissions – Significant increase (pb0.001) in number of complex chronic conditions (CCC) with increased admissions – Significant increase in percentage of patients with more than 1 CCC with increased readmissions (pb0.001) – Percentage of technology assistance increased with increased readmissions (pb0.001) – Percentage of patients with both CCC and technology increased with increased readmissions (pb0.001)

S.M. Hudson

Citation

To explore the perceptions of coping among schoolaged children with chronic illness frequently admitted to the hospital

A tertiary care children's hospital with gastroenterology, neurosurgery, and nephrology services located in Ontario, Canada

Qualitative grounded theory

– Children with chronic conditions and more than 3 hospital admissions (with the most recent within 3 years) identified – Demographic information collected – Data collected using participants' verbal description of art work, semistructured interviews, and participants' daily journal entries

Burke et al. (1991)

To understand the stress process experienced by parents of children with chronic conditions who are repeatedly hospitalized

Homes of mothers who volunteer at the Easter Seal Society, weekend retreat for parents, or a hospital in Ontario, Canada

Qualitative grounded theory

– 30 mothers of children with and 30 without disabilities identified and interviewed twice – Responses of mothers compared and contrasted – 100 parents of children with disability or chronic illness and 6 community-based nurses recruited – Results from the interviews with the first two groups presented to second two groups and perceptions obtained – 25 mothers of children with disabilities from first sample and 26 mothers of children without disability from second sample reinterviewed – Interview and participant observation conducted with sample of 9 mothers of children with chronic conditions to test theory

Categories identified: – Perceived stressors of hospitalization, including IVs, invasive procedures, isolation, death – Perceived coping strategies, including distraction, seeking social support, emotional and verbal expression, avoidance – What others do to promote coping, including familiarity with healthcare professionals, staff attitudes, presence of family and friends, awareness of hospital environment – Categories, themes, and basic psychosocial process (BPP) emerged – BPP: hazardous secrets (for children) and reluctantly taking charge (for parents) Themes of hazardous secrets: – Information of a negative nature, including diagnoses, medications, treatments – Variations, gaps, and/or omissions, describing issues in child care management – The learning health care worker, describing the inexperienced and unsupervised care provider Themes of reluctantly taking charge: – Vigilance, describing the need to keep watch over the child – Taking over, describing the need to assume care the health care system neglects – Negotiating the rules – Calling a halt – Tenaciously seeking information

Hospital Readmissions and Repeat Emergency

Boyd & Hunsberger (1998)

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Table 1 (continued) Purpose

Setting

Design

CarbonellEstrany et al. (2000)

To examine risk factors for readmission among premature infants with and without chronic lung disease (CLD)

14 neonatal ICUs in Spain

Prospective cohort

Chang et al. (1998)

To determine infants for whom home oxygen therapy is applicable and the outcomes for this population

NICU at Mackay Memorial Hospital, Taipei, Taiwan

Retrospective case-series

Chien et al. (2002)

To determine rates of hospital readmission for ELBW infants in the first 2 years, factors associated with readmissions, and the benefit of home oxygen therapy for this group

NICU at National Taiwan University Hospital, Taipei, Taiwan

Retrospective cohort

Cook et al. (1986)

To analyze the influence of previously identified factors on health care utilization in children who are chronically ill, ruraldwelling, and Medicaideligible

Low-income, rural areas in 24 counties of Northern Florida

Retrospective cohort

Procedure applicability to other illnesses – Initial assessment of clinical characteristics and demographic data – 6 monthly assessments via outpatient visit or telephone call to obtain outcomes data

– Charts of VLBW infants admitted to NICU over a 1-year period reviewed to determine presence of CLD – Data collection occurred at followup visit at 6, 9, and 12 months corrected age – Chart review conducted of ELBW infants at a NICU in Taiwan from 1993 through 1998 – Cases of CLD identified – Clinical characteristics obtained from chart review – Infants were followed at 6, 12, 18, and 24 months – Information regarding hospitalization obtained at follow up visits – Hospital records reviewed for details – Stratified random sampling used to obtain equal proportions of children from each of 24 counties – Questionnaires administered at homes to obtain demographic information and health care use for previous 12-month period – Data on hospitalization obtained

Results/findings specific to hospital readmissions or repeat ED visits – Rate of readmission for RSV 26/1000 children with a history of prematurity per month – Median LOS 7 days – Lower risk for RSV-readmission associated with increased gestational age [odds ratio 0.85 (0.72–0.99), pb0.047] – Higher risk of RSV-readmission for infants with CLD [odds ratio 3.1 (1.22–7.91), pb0.016] – Higher risk of RSV-readmission with living with school-attending siblings [odds ratio 1.86 (1.01–3.4), pb0.048] – 20 infants (91%) required 71 readmissions for medical illness or surgical intervention during the 1-year post-discharge period – Respiratory illness most common cause for readmission

– 72% of infants required readmission in the 2 year follow up period – Infants with CLD significantly higher readmissions (p=0.045) – Infants with CLD significantly longer readmission LOS (p=0.034) – Respiratory tract problems most frequent readmission cause – 83% of infants with home oxygen required readmission

– 35.4% of children visited the ED during the previous year – Mean number of ED visits 2.4 – Children with hematologic or perinatal disorders had the highest mean number of ED visits – Respiratory illness, limitations in activity, higher number of hospital days associated with

S.M. Hudson

Citation

To examine associations between severe CLD, growth outcomes, duration of hospitalization, and readmissions in the first year

2 level-III nurseries in Winston-Salem, NC serving a 17- county region of North Carolina

Case-control

Feudtner et al. (2009)

To develop and validate a population-level prediction model for future hospitalizations in children with CCC

PHIS: large database of 38 freestanding children's hospitals across the US

Retrospective cohort

Fosarelli et al. (1987)

To determine characteristics associated with use of hospital services and whether use patterns are created in the first year of life

Harriet Lane Primary Care Clinic at John's Hopkins University in Baltimore, MD

Longitudinal cohort

increased likelihood of ED visit – Number of infants readmitted twice or more in 1-year period significantly higher for those with CLD than without (pb0.005) – Infants with severe CLD significantly increased odds of readmission over infants with no CLD [odds ratio 8.2 (2.6–36.9)] or mild CLD [odds ratio 3.9 (1.5–11.6)]

– Greatest association of readmission with primary payer, number of prior admissions, CCC diagnosis, increased LOS during index admission – Final prediction model of greater likelihood of readmission: female, older age, non-Hispanic black, public insurance, CCC diagnosis, previous admissions

Hospital Readmissions and Repeat Emergency

deRegnier et al. (1997)

from Medicaid records and from medical record review – VLBW infants identified from database – Infants classified as no CLD, mild CLD, or severe CLD – Infants in smallest group matched with infants in other groups for birth weight, race/ethnicity, and gender – Chart reviews conducted on all infants for clinical characteristics, 1year follow up data, readmission data – Data on children in from 2003 to 2005 were obtained from an administrative database – Children with an initial hospitalization and discharge in 2004 were included – Data collected- patient characteristics, previous hospitalization within 1 year, readmission data within 1 year following discharge – All infants with an initial visit between July 1, 1979 and June 30, 1980 included – Demographic data obtained at the time of the first visit – Demographic info, medical info, ED visit data, and clinic visit data obtained 12 months after the first visit, and at the end of the second and third years post initial visit

– Frequency of ED use (low or high) in the first year associated with frequency of use (low or high) in the second and third years (pb0.001) – Frequency of clinic use (low or high) associated with frequency of ED use (low or high) within the same year (pb0.001) – First year high ED use was associated with presence of a chronic condition (pb0.001) – Second year high ED use was associated with newly diagnosed chronic conditions (pb0.001) (continued on next page)

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Table 1 (continued) Citation

Purpose

Setting

Design

Procedure

Results/findings specific to hospital readmissions or repeat ED visits

Frei-Jones et al. (2009)

To evaluate an intervention designed to reduce the 30day readmission rate in children with sickle cell disease (SCD)

Children's Hospital in St. Louis, MO

Evaluation study using before-andafter design

– Significantly lower 30-day readmission rate for children admitted during the intervention period compared with the control period (pb0.002) – 50% of readmissions occurred within 14 days of previous admission

Furman et al. (1996)

To examine characteristics of hospitalization and readmission in the first year of life among infants with CLD

NICU at Rainbow Babies and Children's Hospital in Cleveland, OH

Retrospective cohort

– Prospective review of hospital admissions for SCD pain in 6-month period in 2007 and children meeting inclusion criteria identified during which educational component of intervention conducted – Control cohort identified using same inclusion/exclusion criteria in 6-month period in 2006 – Admissions for SCD pain meeting inclusion/exclusion criteria during 6-month period in 2008 followed to identify readmissions – Retrospective chart review conducted of patients in intervention cohort and control cohort – VLBW infants with CLD identified and demographic data obtained – Data on readmissions recorded at clinic visits at 40 weeks, 4, 8, and 20 months corrected age – Hospitalization details obtained via hospital and long-term facility chart review

Graf et al. (2008)

To describe indications for tracheostomy, discharge disposition and hospital utilization characteristics in children with tracheostomy

Large, urban pediatric hospital (Texas Children's Hospital) in Houston, TX

Retrospective case series

S.M. Hudson

– Chart review conducted of all children receiving tracheostomy during 2002 or 2003 – Demographics and other data collected via chart review – Pediatric Risk of Mortality II score calculated – Indication and surgical timing determined – Charges calculated using hospital records – Patients followed for 6 months to determine readmissions

– 50% readmitted within 1 year; mean readmissions 1.7 – 37% readmitted in second year; mean readmissions 1.9 – 65% of readmissions in first year from RAD, pneumonia or RSV – 81% of readmissions in second year from RAD, pneumonia, or RSV – Readmission LOS significantly associated with lower gestational age, mother unmarried, duration of oxygen dependence – 50% of patients readmitted within 3 months – 63% of patients readmitted within 6 months – 37% of patients readmitted 0 times within 6 months – 63% readmitted 1 time within 6 months – 36% readmitted 2 times within 6 months – 20% readmitted 3 times within 6 months – 11% readmitted 4 times within 6 months

To examine whether measures of oxygen saturation can be used to determine morbidity and mortality among infants with CLD

Regional NICU (Simpson Memorial Maternity Pavilion) in Edinburgh serving an area in southeastern Scotland

Prospective cohort

Kelly & Hewson (2000)

To determine factors related to hospital readmission among children with chronic conditions

Geelon Hospital children's ward in the Barwon Region of Victoria, Australia

Mixed methods

– Premature infants with CLD discharged from NICU recruited – Oxygen saturation and heart rate monitoring were conducted for at least 6 hours overnight prior to discharge – Notification of readmission provided by parents – RSV screening completed or determination of ALTE diagnosis made during hospitalization – Children admitted 4 or more times from July 1996 to June 1997 identified using hospital database – Data regarding admissions obtained via medical record and compared to total child admissions – Individual opinions regarding admissions from families and HCP – Consensus of opinions determined by investigators – Meeting conducted with individuals providing opinions – Participant data compared to greater population – Numbers of patients with 4 or more readmissions compared to numbers in following 12 months

– 50% readmitted to the hospital – 83% of infants with home oxygen readmitted – 44% of infants not on home oxygen readmitted – 11 readmitted infants with RSV infection – 8 infants readmitted with clinical history of acute life threatening event – Significant differences between mean oxygen saturations and variability in oxygen saturation for infants readmitted and infants not readmitted (p=0.001) – 27 children with 4 or more admissions, 144 hospitalizations, 749 days in hospital – 25 of 27 children had chronic illness – 2% of admitted patients had 8.7% of admissions and 16.2% of admission days – Most commonly identified factors for readmission in 27 children with 4 or more admissions, according to consensus: severe, complicated chronic illness (48%); medical dependence (33%); lack of community services (30%)

Hospital Readmissions and Repeat Emergency

Iles & Edmunds (1996)

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Table 1 (continued) Purpose

Setting

Design

Procedure

Results/findings specific to hospital readmissions or repeat ED visits

Liese et al. (2003) and RoecklWiedmann et al. (2003)

To determine risk factors of hospitalization related to RSV among premature infants and to estimate the costs associated with RSV readmission

9 NICUs in southern Germany

Liese et al. (2003): Retrospective cohort RoecklWiedmann et al. (2003): Economic evaluation

Liese et al. (2003): – Infants born in any of 9 NICUs in 1-year period in Germany included – Clinical data, demographics, and details regarding hospitalization obtained via medical record – Questionnaires sent to parents to determine readmissions, possible presence of respiratory illness, and family characteristics – Medical records of readmitted infants reviewed Roeckl-Wiedmann et al. (2003): – Used decision-analysis for costeffectiveness and sensitivity calculations – Based probabilities of RSVreadmission on data from Liese et al. (2003)

Mackie et al. (2008)

To determine risk factors and rates of hospital readmission among children with chronic heart disease

Data obtained from a physician claims database and a hospital discharge database in Quebec, Canada

Retrospective cohort

– Identified index cardiac hospitalizations from 1990 to 2005 and followed each patient for 31 days to determine readmissions – Reviewed prior 90-day period to determine whether admission was index or readmission – Demographic, diagnostic, and procedure-related data obtained from administrative database

Liese et al. (2003): – 10.6% readmitted for acute respiratory infection – 5.2% readmitted for RSV – Incidence rate of RSV-readmission 69.8 cases/1000 preterm infants per RSV season – Highest probability of readmission with acute respiratory infection (25%) or RSV (15.4%) in infants with CLD – Median LOS for RSV readmission 8 days –16.2% of infants with RSV readmission required ICU stay – Statistically significant predictors of RSV readmission: male (pb0.001), CLD (pb0.009), siblings attending day care (pb0.001) Roeckl-Wiedmann et al. (2003): – Prophylaxis most cost effective among infants with male gender, CLD, siblings in day care, discharge between October and December – Impact of drug cost on analysis increased with fewer RSV readmission risk factors – 5% with readmission within 7 days – 9% with readmission within 14 days – 14% with readmission within 31 days – Median time to readmission 12 days – Readmission within 31 days occurred in 22% of infants and 11% of children N1 year (pb0.0001) – Readmission more common with severe CHD (pb0.0001) – 59% of readmissions for cardiac diagnoses – 12% of readmissions for respiratory diagnoses – 35% identical diagnosis for index and readmission – Predictors of readmission within 31 days: severe CHD, younger age, 1 or more visits to the ED in the 6 months before index admission, longer length of stay, 4 or more ICD-9 diagnoses, hospital discharge on the weekend

S.M. Hudson

Citation

To investigate the impact of changes in the Medicaid program on hospitalization patterns in children

Data obtained from the Comprehensive Hospital Abstract Reporting System in Washington state

Retrospective cohort

– Hospitalization rates, LOS, insurance data obtained from a large database for children ages 0– 17 years from 1991 to 1998 – Population data obtained from the Department of Social and Health Services

Pollack et al. (2004)

To describe ED use among children enrolled in Medicaid and Michigan's Title V program for CSHCN

Data obtained from claims data at Michigan's Medicaid and Title V program

Retrospective cohort

Pollack et al. (2007)

To determine whether ED use by children with chronic illness can be reduced by a managed care program

EDs in 6 counties in the urban southeast section of Michigan

Evaluation study using before-andafter design

– All claims submitted to Michigan Medicaid and Title V program examined – Demographic data obtained from Title V eligibility data – Individuals dually enrolled for at least 1 month and with no private insurance from January 1998 through June 1999 included – ED visit info obtained from claims data – Children dually enrolled in Michigan Medicaid and Title V program and changed from fee-forservice and managed care between July 1999 and June 2001 within a 6 county-region of Michigan included – ED data obtained from claims information – Children enrolled in fee-forservice for at least 1 month then enrolled in managed care for at least 1 month included

– Children with Medicaid had significantly higher rate of readmission – Readmission rate for children with Medicaid and chronic condition significantly declined over study period (pb0.001) – Readmission rate for children with Medicaid without chronic condition significantly declined over study period (pb0.001) – 24% with≥1 ED visit – b2% with N10 visits – Infants with 3× more ED visits than other ages – Non-Hispanic blacks with highest ED visits, 20% higher than non-Hispanic whites – Children with SSI and TANF had more ED visits – Higher ED visits associated with anemia, asthma, epilepsy, hemophilia, and diabetes

Hospital Readmissions and Repeat Emergency

Neff et al. (2002)

– 23% reduction in probability of ED use associated with managed care enrollment (pb0.01) – ED visits more likely in children b1 year (pb0.001) – Reduction in ED use with managed care participants lower among blacks

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Table 1 (continued) Citation

Purpose

Setting

Design

Procedure

Results/findings specific to hospital readmissions or repeat ED visits

Santelli, Kouzis, & Newcomer (1996)

To compare healthcare utilization among adolescents in schools with school-based health centers (SBHC) with adolescents in schools without SBHC

9 middle and high schools with SBHC and 4 middle and high schools without SBHC in Baltimore, MD

Crosssectional survey

– School principals and other personnel in 13 schools selected a sample of classrooms considered representative to complete survey – 9 schools with SBHC included and 4 schools without SBHC selected on sociodemographic similarities – Anonymous questionnaire completed by students in May 1991 – Surveys completed on scannable form and were scanned by Public School Office of Testing and Research

Silva et al. (1995)

To describe the path of infants with CLD discharged on home oxygen

Retrospective case series

Sutton et al. (2008)

To determine the feasibility and effect of an ED-based coordination program on ED care of CSHCN

Data obtained from neonatal records at King Edward Memorial Hospital for Women and the Respiratory Clinic at Princess Margaret Hospital, Western Australia ED at a large tertiary children's hospital (Royal Children's Hospital) in Melbourne, Australia

– Infants on home supplemental oxygen identified via respiratory clinic – Infants with CLD included – Data obtained retrospectively from hospital records and clinic notes – Children with chronic conditions visiting the ED 4 or more times in a 12-month period were identified and enrolled in a ED-based coordination program – Patterns of ED use tracked prospectively from 2003 to 2006 in enrolled patients

– 38% reported ≥1 ED visit in the previous year – 19% reported hospitalization – Students with SBHC reported fewer hospitalizations (pb0.001) – 12% 1 hospitalization – 8% 2 or more hospitalizations – 20% 1 ED visit – 19% 2 or more ED visits – Significant predictors of ED use: black (pb0.01), one or more chronic illness (pb0.01), health insurance (pb0.05), older age (pb0.05) – SBHC protected against ED use in students enrolled in the school N1 year – Significant predictors of hospitalization: black (pb0.001), one or more chronic illness (pb0.001), health insurance (pb0.01), older age (pb0.001), lower grade (pb0.001) – SBHC protective against hospitalization – 64% readmitted ≥1 time – 46% readmissions for asthma – 23% readmissions for URI/bronchiolitis – Mean number of readmissions 2.5 – Median length of readmission stay 4.5 days

Evaluation study

S.M. Hudson

– Number of ED visits unchanged among program enrollees during study period (p=0.41) – Number of hospital admissions among program enrollees unchanged during study period (p=0.67) – Admission rates after ED visit unchanged among program enrollees during study period (p=0.7) – Percentage of ED visits after program telephone consult decreased during study period (p=0.02) – ED visits considered avoidable prevented by telephone consultation increased from 8/month at beginning of study period to 30/month at end of study period

To examine characteristics of patients with frequent ED visitation at a pediatric ED

The sole tertiary referral center in Hawaii for pediatrics (Kapiolani Medical Center for Women and Children, Honolulu, HI)

Retrospective case series

– ED visit information stored in database during study period from November 1987 to May 1992 – Patients with 10 or more ED visits in study period identified as frequent users – Outpatient and inpatient records reviewed for demographics and chronic conditions

Hospital Readmissions and Repeat Emergency

Yamamoto et al. (1995)

– 55% of parents surveyed believed program enrollment prevented ED visit – 99 patients N15 ED visits – 39 patients N20 ED visits – 17 patients N25 visits – 10 patients N30 visits – Of 357 patients with ≥10 ED visits: – 74% with chronic disease (17 with severe functional impairment) – 92% with up-to-date immunizations – 95% with pediatrician as PCP – 2% with no PCP – 38% private insurance – 0.3% military insurance – 60% Medicaid – 1.4% no insurance – Ethnic distribution of those with ≥10 ED visits significantly different from those with b3 ED visits (pb0.0001) – Polynesian groups greater proportion of frequent ED users – Significant difference in geographic distribution of those with ≥10 visits to those with b3 visits (pb0.0001) – Frequent users living closer to medical center

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328 Roeckl-Wiedmann et al., 2003). Characteristics of the studies are described in Table 1.

Results Population Characteristics Characteristics of study samples are presented in Table 2. Analysis of the sample characteristics revealed two major groups: samples of children with and without chronic conditions and samples of infants with a history of prematurity with and without chronic lung disease (CLD). A wide variety of diagnoses were represented in the samples; the most commonly observed conditions were neurological or neuromuscular disorders, CLD, cardiovascular disease, and congenital anomalies. Among the studies of children with chronic conditions, 10 samples included only children with chronic conditions or compared children with chronic conditions to a control population (Berry et al., 2009; Boyd & Hunsberger, 1998; Burke, Kauffmann, Costello, & Dillon, 1991; FreiJones, Field, & DeBaun, 2009; Graf, Montagnino, Hueckel, & McPherson, 2008; Kelly & Hewson, 2000; Mackie, IonescuIttu, Pilote, Rahme, & Marelli, 2008; Pollack, Wheeler, Cowan, & Freed, 2007; Pollack et al., 2004; Sutton, Stanley, Babl, & Phillips, 2008) and the remaining 7 samples included a blend of children with chronic conditions and well children (Berry et al., 2011; Cook, Krischer, & Kraft, 1986; Feudtner et al., 2009; Fosarelli, DeAngelis, & Mellits, 1987; Neff et al., 2002; Santelli, Kouzis, & Newcomer, 1996; Yamamoto et al., 1995). A population comprised solely of CMC was evident in only three studies (Berry et al., 2009; Graf et al., 2008; Sutton et al., 2008); many of the samples contained a mix of CSHCN and CMC. Similarly, many of the samples in the group that consisted of infants with a history of prematurity included a combination of infants with and without CLD. Child age at time of investigation was not frequently reported among this group, but gestational age at birth was often reported. Additionally, among studies of infants with a history of prematurity, only one study reported gender and race/ethnicity data for the full sample (Carbonell-Estrany et al., 2000).

Setting Characteristics The most commonly observed settings were hospitals or large existing databases. Single center and multicenter settings were well represented in a nearly equal number of studies. In contrast, few studies were conducted in either rural or community-based settings. Single centers included freestanding children's hospitals (Boyd & Hunsberger, 1998; Frei-Jones et al., 2009; Graf et al., 2008; Sutton et al., 2008; Yamamoto et al., 1995), hospitals caring for children and adults (Kelly & Hewson, 2000; Silva, Hagan, & Sly, 1995), and single-center neonatal intensive care units (NICUs) (Chang, Hsu, Kao, Hung, & Huang, 1998; Chien, Tsao,

S.M. Hudson Chou, Tang, & Tsou, 2002; Furman, Baley, Borawski-Clark, Aucott, & Hack, 1996; Iles & Edmunds, 1996). Eight of the study reports described multicenter settings, in which the number of settings ranged from two NICUs serving a 17county area (deRegnier, Roberts, Ramsey, Weaver, & O'Shea, 1997) to a database of over 30 children's hospitals (Berry et al., 2009; Berry et al., 2011; Feudtner et al., 2009). Settings of other large databases included a physician claims database (Mackie et al., 2008) and a state-wide hospital reporting system (Neff et al., 2002). Only four studies reported findings from a rural or community-based setting. In one example, subjects were recruited from a community-based organization and interviewed in their own homes (Burke et al., 1991). Other community-based settings included a primary care clinic (Fosarelli et al., 1987) and settings that encompassed wider geographical spans such as rural areas of 24 counties (Cook et al., 1986) and 13 middle and high schools (Santelli et al., 1996). All studies were conducted in industrialized nations, and the following countries were represented by order of highest to lowest frequency: United States (US), Australia, Canada, Taiwan, Germany, Scotland, and Spain. In a few studies, attention to rural versus urban location was suggested or stated. One children's hospital was described as being located in an urban setting (Graf et al., 2008), and other children's hospitals were portrayed as regional centers. The setting of one study was specifically focused on rural areas (Cook et al., 1986).

Hospital Readmissions and Repeat ED Visits as Measures and Outcome Measures In the sample articles, hospital readmissions and ED visits among CMC were explored in a variety of ways. In several studies, the characteristics of hospital readmissions or ED visits in specific populations were investigated. Characteristics of hospital admissions and/or ED visits in children with and without chronic conditions were examined in two studies. Berry et al. (2011) researched characteristics of hospitalization that included the admission rate, frequency, charges, diagnoses, and length of stay (LOS) while Santelli et al. (1996) investigated admission and ED visit rates among children with and without access to a student-based health center. Characteristics of hospital admissions and ED visits were also explored in populations comprised solely of children with chronic conditions and subpopulations of children with chronic conditions. The characteristics examined included ED visit rates (Cook et al., 1986) and hospital readmission rates (Berry et al., 2009; Graf et al., 2008; Mackie et al., 2008), although the time considered for readmissions ranged from a 30-day period (Berry et al., 2009) to a 6-month period (Graf et al., 2008). In studies of infants with a history of prematurity, characteristics examined included readmission rates, month of readmission, diagnosis, and LOS (Chien et al., 2002; Furman et al., 1996).

Hospital Readmissions and Repeat Emergency Whereas in some studies the characteristics of hospital admissions and ED visits in particular populations were explored, in other studies population characteristics associated with high rates of readmissions or ED visits were examined. Characteristics of children with and without chronic conditions and with high rates of ED visits were examined in two studies (Fosarelli et al., 1987; Yamamoto et al., 1995) and characteristics of children with chronic conditions and high ED visit rates were examined in one additional study (Pollack et al., 2004). Similarly, characteristics that predicted hospital readmission were sought in two studies (deRegnier et al., 1997; Feudtner et al., 2009). In studies examining the factors associated with readmissions and repeat visits and in studies investigating populations with high readmission and repeat visit rates, children with chronic conditions were repeatedly found to have higher health care utilization rates than children without chronic conditions, as were infants with a history of prematurity and CLD (Berry et al., 2011; CarbonellEstrany et al., 2000; Chien et al., 2002; deRegnier et al., 1997; Fosarelli et al., 1987; Liese et al., 2003; Santelli et al., 1996; Yamamoto et al., 1995). The number and complexity of chronic conditions and the presence of technological assistive devices also contributed to a higher number of readmissions or ED visits (Berry et al., 2011; Mackie et al., 2008; Santelli et al., 1996). Further population characteristics associated with increased hospital and ED utilization were respiratory or neurological illness, non-Hispanic black race, public insurance or Medicaid, and younger gestational age in infants with a history of prematurity (Berry et al., 2009; Berry et al., 2011; Feudtner et al., 2009; Furman et al., 1996; Neff et al., 2002; Pollack et al., 2004; Santelli et al., 1996; Yamamoto et al., 1995). Hospital readmissions were also studied as outcomes of treatments or interventions. In three studies, readmissions were analyzed as an outcome in infants with a history of prematurity and CLD receiving home oxygen therapy (Chang et al., 1998; Iles & Edmunds, 1996; Silva et al., 1995). As outcomes of interventions, ED visit rates were collected in two studies (Pollack et al., 2007; Sutton et al., 2008), and the 30-day hospital readmission rate was evaluated in one additional study (Frei-Jones et al., 2009). Finally, hospital readmissions were explored through individual perceptions of the readmission experience. The perceptions of children themselves was the focus of one study, which examined coping with hospital readmissions and perceived assistance with coping (Boyd & Hunsberger, 1998). Parental or familial perceptions were examined in two studies; the perceptions of stress related to hospital readmissions was the focus of one (Burke et al., 1991), while family and health care professional opinions regarding the causes of readmissions was the concentration of another (Kelly & Hewson, 2000).

329

Discussion Definitions of Hospital Readmissions Hospital readmissions were defined in a variety of ways, with a length of readmission that ranged from as few as 7 days to as long as 2 years. In certain studies, a clear definition of hospital readmissions was not presented. Landrum and Weinrich (2006) recommended consistent use of a definitional framework for measuring hospital readmissions that included: identification of an index hospitalization; admission reason, diagnosis, and/or purpose; time frame from discharge to readmission; and the data source. Few studies in the sample described identification of an index hospitalization, although many examined the readmission cause or diagnosis. Wide gaps were observed in the discharge to readmission time frame, and in some cases the time frame was not explicitly stated.

Population Characteristics In the sample of studies investigating hospital readmissions or repeat ED visits, few populations were solely composed of CMC. The majority of study populations included either CSHCN or well children and CSHCN, with the sample of CSHCN including the subpopulation, CMC. However, even among the studies specifically examining CMC, a consistent definition of the population was not applied. Wide variations in terms, definitions, and operationalizations of terms have been used in studies of children with chronic conditions (van der Lee, Mokkink, Grootenhuis, Heymans, & Offringa, 2007), which can hinder comparability among studies. Use of a single term with a clear definition such as the one presented by Cohen et al. (2011) in describing and selecting a study population can lead to a lucid understanding of population problems and interventions explicitly structured to meet the needs of the population. CMC in particular have high levels of health care requirements and health care utilization (Cohen et al., 2011), suggesting the need to examine hospital readmissions and ED visits solely in this distinct population and not as a part of a larger population.

Setting Characteristics The majority of study settings in this review were either multicenter or freestanding children's hospitals in the US and other industrialized countries, with few studies occurring in rural settings. This gap is significant since geographical proximity to tertiary centers may influence health care utilization patterns (Pollack et al., 2004; Yamamoto et al., 1995). Children living in rural areas may have limited access to health care, and in the US, approximately 22% of rural or small town households include CSHCN (Child and Adolescent Health Measurement Initiative, n.d.). Thus, further

330

Table 2

Comparison of Study Samples.

Reference

Size

Most Common Child Conditions

Race/Ethnicity

Child Age

Child Gender

Insurance Status

Technology Use

Berry et al. (2009)

917 children undergoing tracheotomy

55.9% chronic lung disease (CLD) 47.6% neurological impairment

44.8% white/ non-Hispanic 24.1% black 15.7% other 15.4% Hispanic

57.1% b1 year 29.5% 1–12 years 13.3% 13–18 years

59.3% male 40.7% female

54% public 27.7% private/HMO 1.7% self-pay 16.6% other/ unknown

Berry et al. (2011)

248,349 children with 0 hospital readmissions

22.3% any complex chronic condition (CCC) 9.7% neuromuscular 7% cardiovascular

50.4% white 21.8% black 18.3% Hispanic 2.1 % Asian 7.4% other

9% b30 days 18% 31–365 days 28.6% 1–4 years 27.7% 5–12 years 14% 13–18 years 2.7% N18 years

55.7% male 44.3% female

40,237 children with 1 hospital readmission

48.8% any CCC 21.5% neuromuscular 12.7% cardiovascular

49.5% white 26.8% black 15.9% Hispanic 1.9% Asian 5.9% other

3.5% b30 days 16.1% 31–365 days 28.7% 1–4 years 30% 5–12 years 16.8% 13–18 years 4.9% N18 years

55.5% male 44.5% female

13,523 children with 2 hospital readmissions

69.3% any CCC 31.3% neuromuscular 17.2% cardiovascular

48% white 30.4% black 14.9% Hispanic 1.5% Asian 5.2% other

1.9% b30 days 13.2% 31–365 days 28.5% 1–4 years 31.8% 5–12 years 17.9% 13–18 years 6.7% N18 years

53.9% male 46.1% female

6927 children with 3 hospital readmissions

78.5% any CCC 34.9% neuromuscular 18% cardiovascular

49.4% white 30.2% black 13.6% Hispanic 1.7% Asian 5.1% other

1% b30 days 9.9% 31–365 days 27.5% 1–4 years 32.9% 5–12 years 20.8% 13–18 years 7.9% N18 years

53.4% male 46.6% female

40.9% public 32.7% commercial 20.3% other 6% self-pay 0.1% data missing 46% public 30.5% commercial 18.4% other 5% self-pay 0.1% data missing 49.9% public 28.3% commercial 17.4% other 4.4% self-pay 0% data missing 51.2% public 27.8% commercial 16.6% other 4.3% self-pay 0.1% data missing

57.6% sometimes ventilated 25.2% never ventilated 17.2% always ventilated 5.3% any technology

19.7% any technology

35% any technology

43.5% any technology

S.M. Hudson

89% any CCC 39.6% neuromuscular 22.4% malignancy

45.6% white 34.4% black 13.9% Hispanic 1.7% Asian 4.3% other

0.4% b30 days 6.1% 31–365 days 25.1% 1–4 years 33.2% 5–12 years 24.1% 13–18 years 11.1% N18 years

52.1% male 47.9% female

Boyd & Hunsberger (1998)

6 children with repeated hospitalizations

Not provided

2 at 10 years 1 at 12 years 3 at 13 years

33% male 67% female

Burke et al. (1991)

30 mothers of children with chronic illness or disability 30 mothers of healthy children sociodemographically matched to above 100 parents of children with disabilities attending a weekend retreat 6 community health nurses 9 mothers of chronically ill children before, during, and after hospitalization 584 children born ≤32 weeks gestational age

1 with Wilson's disease 1 with hydrocephalus 1 with spina bifida, tethered cord 1 with hypertension 1 with seizures 1 with acute kidney failure, Wegener's syndrome Cerebral palsy or myelodysplasia

Not provided

Not provided

None

Not provided

Children with physical disability or chronic illness N/A

CarbonellEstrany et al. (2000)

56.3% public 26.1% commercial 14.1% other 3.5% self-pay 0.1% data missing Not provided

52.6% any technology

Not provided

Not provided

Not provided

Not provided

Not provided

Not provided

Not provided

Not provided

Not provided

Not provided

Not provided

Not provided

Not provided

N/A

N/A

N/A

N/A

N/A

Orthopedic, cardiac, immunologic and oncologic related hospitalizations

Not provided

Not provided

Not provided

Not provided

Not provided

6.5% CLD

91.9% white 8.1% other

Median=76 days Median gestational age 30 weeks

51.5% Male 48.9% female

Not provided

Not provided

Hospital Readmissions and Repeat Emergency

9237 children with 4 or more hospital readmissions

(continued on next page)

331

332

Table 2 (continued) Reference

Size

Most Common Child Conditions

Race/Ethnicity

Child Age

Child Gender

Insurance Status

Technology Use

Chang et al. (1998)

34% CLD

Not provided

Not provided

50% male 50% female

Not provided

Chien et al. (2002)

111 infants with history of prematurity 60 infants with history of prematurity

42% CLD

Not provided

Not provided

50% male 50% female

Not provided

Cook et al. (1986)

672 Medicaid-eligible children

31.1% 0–4 years 41.4% 5–10 years 27.5% 11–16 years Not provided

Not provided

678 infants with history of prematurity 186,856 children discharged from a hospitalization

67.2% black 32.1% white 0.7% other 38% black

56.7% male 43.3% female

deRegnier et al. (1997) Feudtner et al. (2009)

25% neurological 21% congenital anomalies 57% no CLD 16.4% mild CLD 26.6% severe CLD 9.3% neuromuscular 5.5% malignancy

21% home supplemental oxygen 28% home supplemental oxygen Not provided

48% male 52% female

Not provided

Not provided

52.9% white 23.5% black 15.1% Hispanic 1.9% Asian 6.6% other 50.3% white 28.4% black 13.8% Hispanic 1.8% Asian 5.7% other

26.6% 2–4 years 28.7% 5–9 years 28.9% 10–14 years 15.7% 15–18 years

54.4% male 45.6% female

36.7% government 38.3% private 25% other

Not provided

26% 2–4 years 26.7% 5–9 years 29.4% 10–14 years 17.8% 15-18 years

53.1% male 46.9% female

43.2% government 33.2% private 23.6% other

Not provided

24.9% b1 month 62.1% 1–2 months 13% N2 months

52.9% male 47.1% female

80.9% medical assistance 4.1% private insurance 15% no insurance

Not provided

Fosarelli et al. (1987)

16.8% neuromuscular 15.8% malignancy

293 children younger than 12 months remaining enrolled for 3 years

27% chronic condition including: asthma, cardiac disease, seizure disorders, cerebral palsy, hematologic disorders, family/social dysfunction, learning disorders, and miscellaneous 73% None

87% black 13% white

S.M. Hudson

31,188 children readmitted to the hospital within 1 year

100% SCD 53% comorbidities

Not provided

Mean 11.2 years

46% Male 54% female

56 control group children with SCD

100% SCD 46% comorbidities

Not provided

Mean 12.7 years

52% male 48% female

Furman et al. (1996) Graf et al. (2008)

98 infants with CLD and history of prematurity 70 children with tracheostomy

100% CLD

61% black

Not provided

Not provided

33% white 40% Hispanic 21% black 6% other

Median age= 18.5 months

61% male 39% female

49% Medicaid 39% private 7% self-pay/ none

81% required medical device 12% required 3 or more devices

Iles & Edmunds (1996) Kelly & Hewson (2000)

40 infants with CLD

26% congenital heart disease 26% mental retardation/ cerebral palsy 27% primary lung disease 36% gastroesophageal reflux 100% CLD

Not provided

Not provided

Not provided

Not provided

Not provided

7 at 5 at 5 at 6 at 4 at

Not provided

Not provided

15% home supplementary oxygen Not provided

27 children or adolescents with 4 or more admissions

4 with major developmental delay and seizures 4 with congenital abnormalities/ syndromes 3 with cystic fibrosis 3 with constipation or neurointestinal dysplasia

0–1 year 2–5 years 5–9 years 10–14 years N15 years

72% Medicaid or other statesponsored insurance 71% Medicaid or other statesponsored insurance Not provided

Not provided

68 children with sickle cell disease (SCD)

Not provided

Not provided

Hospital Readmissions and Repeat Emergency

Frei-Jones et al. (2009)

(continued on next page)

333

334

Table 2 (continued) Reference

Size

Most Common Child Conditions

Race/Ethnicity

Child Age

Child Gender

Insurance Status

Technology Use

Liese et al. (2003), and RoecklWiedmann et al. (2003) Mackie et al. (2008)

717 infants with history of prematurity

7.4% CLD 17.4% cardiac abnormalities 12% retinopathy

Not provided

Not provided

52.3% male 47.7% female

Not provided

Not provided

3157 children with congenital heart disease (CHD) not readmitted 518 children with CHD readmitted within 90 days 372,406 children with or without a chronic condition

38% severe CHD

Not provided

Median 3.6 years

51% male 49% female

Not provided

Not provided

47% severe CHD

Not provided

Median 1.2 years

52% male 48% female

Not provided

Not provided

Not provided

Not provided

Ages 0–17 years

Not provided

35.5% Medicaid 64.5% nonMedicaid 43.1% SSI 16.8% TANF 23.3% healthy Kids 7.2% Medicaid for persons under 21 3.2% Medicaid for the disabled 6.2% Medicaid for caretaker relatives 0.1% other eligibility 51% SSI 49% other eligibility

Not provided

Neff et al. (2002)

10,800 CSHCN dual-enrolled in Medicaid and Michigan's Children Special Health Care Services

14.2% cerebral palsy 12.5% diseases of the ear and mastoid process 8.9% congenital anomalies 2.7% respiratory distress syndrome

51.7% white 30.8% black 3.6% Hispanic 2.9% other 11% unknown

14.8% b1 year 26% 1–4 years 26.2% 5–9 years 18.6% 10–14 years 14% 15–20 years 0.4% 21 years

55% male 45% female

Pollack et al. (2007)

434 CSHCN dually-enrolled in Medicaid and Michigan's Title V program

Chronic illnesses including: 16% cerebral palsy 1.5% cystic fibrosis 1.3% hemophilia

61% white 27% black 12% other

6.8% b1 year 26.6% 1–4 years 28.2% 5–9 years 16.7% 10–14 years 16.4% 15–20 years 0.7% 21 years

54.8% male 45.2% female

Not provided

Not provided

S.M. Hudson

Pollack et al. (2004)

3258 students in schools with and without health centers

52% one or more physical condition

73% black 22% white 5% other

Mean 14.5 years

44% male 56% female

Silva et al. (1995)

56 neonates with CLD discharged home with supplementary oxygen 220 CSHCN enrolled in a emergencydepartment based coordination program

100% CLD

Not provided

68% male 32% female

24.5% cerebral palsy 18.6% genetic disorders 12.3% developmental delay

Not provided

(corrected) 48% b1 month 23% 1–2 months 20% 3–5 months 7% N6 months Mean 8.1 years

265 with chronic conditions 231 with pulmonary condition

6% white 1% black 4% Japanese 9% Filipino 5% other/mixed Asian 32% Hawaiian/ part Hawaiian 26% Samoan 5% other Pacific Islander 12% other/ mixed

Sutton et al. (2008)

Yamamoto et al. (1995)

357 children seen in the emergency department 10 times or more over a 4.6 year study period

Ages 0 to 21 years

3% none 22% Medicaid 38% private insurance 36% don't know Not provided

47.7% male 52.3% female

Not provided

Not provided

38% private 0.3% military 60% Medicaid or state assistance 1.4% none

Not provided

100% supplementary home oxygen

20.5% no devices/ implants 49.5% 1 device/ implant 30% 2 or more devices/ implants Not provided

Hospital Readmissions and Repeat Emergency

Santelli et al. (1996)

335

336 study of hospital readmissions and ED visits conducted in this setting could lend greater understanding of the impact of rural living on hospital utilization. The lack of communitybased settings utilized among studies poses another significant gap. Community-based settings represented in the sample included a primary care clinic and the school environment. According to SET, community-level influences interact with individual-level influences; therefore, individual and family-level readmission behaviors are influenced by factors in the community. In addition, the ECCM puts forth that positive influence on health outcomes requires efforts be made by health care professionals to strengthen and support the community and to determine the strengths and needs of people in the community (Barr et al., 2003). A step toward addressing hospital readmissions and repeat ED visits in CMC could include expanding the knowledge base in this area by investigating the influence of community factors on individual behaviors and exploring the community-level strengths and needs identified by CMC, their families, and the health care professionals involved in their care. The knowledge base in this area could be further expanded by exploring the connections between the health care system and the community and the effect of these connections on hospital readmissions and repeat ED visits by CMC.

Hospital Readmissions and Repeat ED Visits as Measures and Outcome Measures Many of the studies reviewed examined either characteristics describing populations with high numbers of hospital readmissions or ED visits, or readmission and ED visit patterns within particular populations. Health care providers could benefit from knowledge of consistently identified characteristics associated with increased hospital readmissions and ED visits. A gap was identified in that few studies examined the child's, parent/primary caregiver's, or health care provider's perceptions of hospital readmissions and repeat ED visits. Additional studies addressing this gap are needed to provide a more comprehensive understanding of the problem by incorporating individual perceptions of the readmission and repeat ED visit experience.

Addressing Hospital Readmissions and Repeat ED Visits Determining strategies for addressing hospital readmissions and repeat ED visits is necessary since changes proposed by the Affordable Care Act (Patient Protection and Affordable Care Act, 2010) are directed at preventing avoidable hospital readmissions. Beginning in 2012, the Centers for Medicare and Medicaid Services (CMS) have reduced Medicare payments to hospitals with readmissions above a determined rate for selected conditions (Centers for Medicare and Medicaid Services, 2011). The payment reductions will increase annually and will be expanded to

S.M. Hudson include additional diagnoses in future years. It can be anticipated that Medicaid payment reductions may also be initiated, thus impacting hospital readmissions in children. Strategies for reducing hospital readmissions and repeat ED visits include the promotion of health care/medical homes and care coordination. Care coordination programs have been found to decrease hospitalization rates, number of hospital days, hospital charges, and ED visits in CMC (Gordon et al., 2007; Peter et al., 2011). The health care/medical home is one example of a care coordination model. The medical home is described as care provision for infants, children, and adolescents that is “accessible, continuous, comprehensive, family centered, coordinated, and compassionate” (Ad Hoc Task Force on Definition of the Medical Home, 1992, p. 774); the American Association of Pediatrics recommends all CSHCN have a medical home (Medical Home Initiatives for Children With Special Needs Project Advisory Committee, 2002). Similarly, the National Association of Pediatric Nurse Practitioners (NAPNAP) has issued a position statement in support of family-centered, coordinated, accessible health care for children (National Association of Pediatric Nurse Practitioners, 2009). The NAPNAP also encouraged the use of language in legislation or policies pertaining to the health care/medical home model that is all-provider inclusive (i.e. health care home rather than medical home). Potential benefits of the health care/medical home model to CSHCN include decreased health care utilization and improved parental satisfaction (Kelly, Golnik, & Cady, 2008; Palfrey et al., 2004; Raphael, Zhang, Liu, Tapia, & Giardino, 2009). Additionally, the health care/medical home model may be expected to receive greater attention in the immediate future as one of 20 care models or payment systems to be tested by CMS for improved care coordination (Guterman, Davis, Stremikis, & Drake, 2010). Despite advantageous findings associated with care coordination and recommendations for use of a health care/medical home, less than 47% of US parents or primary caregivers of CSHCN report receiving coordinated care through a health care/medical home (Child and Adolescent Health Measurement Initiative, n.d.), and parents and primary caregivers of CMC report spending greater time on care coordination than other CSHCN (Kuo, Cohen, Agrawal, Berry, & Casey, 2011).

Limitations This integrative review has limitations. First, the review was conducted by a single author. Although attempts were made to conduct the review in a systematic, reproducible manner, interrater reliability was lacking. Second, author choice of terms that described hospital readmissions and repeat ED visits may have resulted in the exclusion of relevant studies. Finally, although over half of the sample studies were conducted in the US, and all studies were conducted in industrialized countries, health care systems in international settings differ from the US health care system. The applicability of the findings from this review to the US

Hospital Readmissions and Repeat Emergency health care setting may be limited by the inclusion of studies in international settings.

Conclusions The majority of published literature on hospital readmissions and repeat ED visits among CMC has focused on describing characteristics associated with frequent readmissions or repeat ED visits. One major gap in the literature is that few of the studies were conducted solely with samples of CMC; the majority included well children and CSHCN. Another gap in the literature was the small number of studies conducted in either rural or community-based settings; most study settings were multicenter or freestanding children's hospitals. These gaps are important because CMC are a unique population with needs beyond those of well children and CSHCN, and because an understanding of factors associated with hospital readmissions and repeat ED visits in rural or community-based settings could contribute to a more comprehensive understanding of the problem. Further studies focusing solely on hospital readmissions and repeat ED visits among CMC must be conducted since this population has distinct, high-level needs. In every case, future research should be based on clearly defined measures of hospital readmissions and ED visits, and the CMC population should be identified using consistent terms and an unambiguous definition. Consideration should be made to the time frame used to define readmissions in future studies. Periods longer than the 30-day window considered by CMS may be necessary to accurately capture readmissions. Further studies should also be conducted that examine hospital readmissions and repeat ED visits in rural-dwelling CMC, since geographical location may influence health care utilization. Additional research investigating methods for reducing preventable readmissions or ED visits may also be necessary. Care coordination has been specified as one strategy for addressing high health care utilization rates. A review of studies examining the role of care coordination in hospital readmissions and ED visits among CMC would be a beneficial addition to the literature in this area. Gaps that may be identified through such a literature review could delineate further avenues for future inquiry. Beyond research, findings of the review have implications for nursing practice. Nurses must be aware of the heightened national focus on addressing preventable hospital readmissions and should be active participants in creating and implementing interventions attending to the issue. In both the primary and acute care settings, nurses can develop educational plans with CMC and their families that are tailored toward reducing the risk of readmissions or repeat ED visits. Primary care and acute care nurses may also consider seeking care coordination services (such as a health care/medical home) for CMC as a strategy for reducing readmissions and repeat ED visits. Since characteristics of

337 CSHCN and CMC with high readmission and repeat ED visit rates have been identified, nurses should be aware of increased risk for readmissions among patients with these characteristics. Additionally, community-based nurses should be particularly aware of these characteristics and should consider efforts to improve community resources among CMC, particularly for those children with multiple risk factors for increased readmissions and ED visits. Greater knowledge of the ECCM in nursing practice could also be of benefit as this model outlines how the health care system can work with communities to promote wellness in chronically ill populations. Awareness and action toward strengthening the relationship between patients and the health care team could lead to improved health outcomes; in particular, action should be focused on assessing community-based needs and strengthening community resources.

Acknowledgments The author wishes to thank Dr. Marilyn Laken, Dr. Gayenell Magwood, Dr. Martina Mueller, and Dr. Lisa Kerr for their assistance in the preparation of this manuscript. No extramural funding. No previous presentations. No commercial financial support.

References Ad Hoc Task Force on Definition of the Medical Home (1992). The medical home. Pediatrics, 90, 774. Barr, V. J., Robinson, S., Marin-Link, R., Underhill, L., Dotts, A., Ravensdale, D., et al. (2003). The expanded chronic care model: An integration of concepts and strategies from population health promotion and the chronic care model. Hospital Quarterly, 7, 73–82. Beck, C. E., Khambalia, A., Parkin, P. C., Raina, P., & Macarthur, C. (2006). Day of discharge and hospital readmission rates within 30 days in children: A population based study. Paediatrics and Child Health, 11, 409–412. Berry, J. G., Graham, D. A., Graham, R. J., Zhou, J., Putney, H. L., O'Brien, J. E., et al. (2009). Predictors of clinical outcomes and hospital resource use of children after tracheotomy. Pediatrics, 124, 563–572, http: //dx.doi.org/10.1542/peds.2008-3491. Berry, J. G., Hall, D. E., Kuo, D. Z., Cohen, E., Agrawal, R., Feudtner, C., et al. (2011). Hospital utilization and characteristics of patients experiencing recurrent readmissions within children's hospitals. Journal of the American Medical Association, 305, 682–690, http: //dx.doi.org/10.1001/jama.2011.122. Boyd, J. R., & Hunsberger, M. (1998). Chronically ill children coping with repeated hospitalizations: Their perceptions and suggested interventions. Journal of Pediatric Nursing, 13, 330–342. Bramlett, M., Read, D., Bethell, C., & Blumberg, S. (2009). Differentiating subgroups of children with special health care needs by health status and complexity of health care needs. Maternal and Child Health Journal, 13, 151–163, http://dx.doi.org/10.1007/s10995-008-0339-z. Bronfenbrenner, U. (1994). Ecological models of human development. (2nd ed). International Encyclopedia of Education, 3, Oxford: Elsevier. Buescher, P. A., Whitmire, J. T., Brunssen, S., & Kluttz-Hile, C. E. (2006). Children who are medically-fragile in North Carolina: Using Medicaid

338 data to estimate prevalence and medical care costs in 2004. Maternal and Child Health Journal, 10, 461–466, http://dx.doi.org/10.1007/ s10995-006-0081-3. Burke, S. O., Kauffmann, E., Costello, E. A., & Dillon, M. C. (1991). Hazardous secrets and reluctantly taking charge: Parenting a child with repeated hospitalizations. Image – the Journal of Nursing Scholarship, 23, 39–45. Carbonell-Estrany, X., Quero, J., Bustos, G., Cotero, A., Domenech, E., Garcia-Alix, A., et al. (2000). Rehospitalization because of respiratory syncytial virus infection in premature infants younger than 33 weeks of gestation: A prospective study. Pediatric Infectious Disease Journal, 19, 592–597. Medicare program: Proposed changes to the hospital inpatient prospective payment systems for acute care hospitals and the long-term care hospital prospective payment system and fiscal year 2012 rates, Vol. 76. (pp. 25788–26084). (2011).Baltimore, MD: Department of Health and Human Services. Chang, J., Hsu, C., Kao, J., Hung, H., & Huang, F. (1998). Home oxygen therapy for chronic lung disease in very low-birth-weight infants. Acta Pædiatrica Sinica, 39, 237–241. Chien, Y. -H., Tsao, P. -N., Chou, H. -C., Tang, J. -R., & Tsou, K. -I. (2002). Rehospitalization of extremely-low-birth-weight infants in first 2 years of life. Early Human Development, 66, 33–40. Child and Adolescent Health Measurement Initiative. (n.d.). 2005/06 National survey of children with special health care needs. Retrieved October 17, 2011, from www.cshcndata.org. Cohen, E., Kuo, D. Z., Agrawal, R., Berry, J. G., Bhagat, S. K. M., Simon, T. D., et al. (2011). Children with medical complexity: An emerging population for clinical and research initiatives. Pediatrics, 127, 529–538, http://dx.doi.org/10.1542/peds.2010-0910. Cook, B. A., Krischer, J. P., & Kraft, R. E. (1986). Use of health care by chronically ill children in rural Florida. Public Health Reports, 101, 644–652. deRegnier, R., Roberts, D., Ramsey, D., Weaver, R. G., & O'Shea, T. M. (1997). Association between the severity of chronic lung disease and first-year outcomes of very low birth weight infants. Journal of Perinatology, 17, 375–382. Feudtner, C., Levin, J. E., Srivastava, R., Goodman, D. M., Slonim, A. D., Sharma, V., et al. (2009). How well can hospital readmission be predicted in a cohort of hospitalized children? A retrospective, multicenter study. Pediatrics, 123, 286–293, http://dx.doi.org/ 10.1542/peds.2007-3395. Fosarelli, P. D., DeAngelis, C., & Mellits, E. D. (1987). Health services use by children enrolled in a hospital-based primary care clinic: A longitudinal perspective. Pediatrics, 79, 196–202. Frei-Jones, M. J., Field, J. J., & DeBaun, M. R. (2009). Multi-modal intervention and prospective implementation of standardized sickle cell pain admission orders reduces 30-day readmission rate. Pediatric Blood and Cancer, 53, 401–405, http://dx.doi.org/10.1002/pbc.22048. Furman, L., Baley, J., Borawski-Clark, E., Aucott, S., & Hack, M. (1996). Hospitalization as a measure of morbidity among very low birth weight infants with chronic lung disease. The Journal of Pediatrics, 128, 447–452. García, J. A., Yee, M. C., Chan, B. K. S., & Romano, P. S. (2003). Potentially avoidable rehospitalizations following acute myocardial infarction by insurance status. Journal of Community Health, 28, 167–184, http://dx.doi.org/10.1023/a:1022904206936. Goodman, D. M., Mendez, E., Throop, C., & Ogata, E. S. (2002). Adult survivors of pediatric illness: The impact on pediatric hospitals. Pediatrics, 110, 583–589, http://dx.doi.org/10.1542/peds.110.3.583. Gordon, J. B., Colby, H. H., Bartelt, T., Jablonski, D., Krauthoefer, M. L., & Havens, P. (2007). A tertiary care primary care partnership model for medically complex and fragile children and youth with special health care needs. Archives of Pediatric and Adolescent Medicine, 161, 937–944, http://dx.doi.org/10.1001/archpedi.161.10.937. Graf, J. M., Montagnino, B. A., Hueckel, R., & McPherson, M. L. (2008). Pediatric tracheostomies: A recent experience from one academic center.

S.M. Hudson Pediatric Critical Care Medicine, 9, 96–100, http://dx.doi.org/10.1097/ 01.PCC.0000298641.84257.53. Guterman, S., Davis, K., Stremikis, K., & Drake, H. (2010). Innovation in Medicare and Medicaid will be central to health reform's success. Health Affairs, 29, 1188–1193, http://dx.doi.org/10.1377/hlthaff.2010.0442. Iles, R., & Edmunds, A. T. (1996). Prediction of early outcome in resolving chronic lung disease of prematurity after discharge from hospital. Archives of Disease in Childhood, 74, 304–308, http://dx.doi.org/ 10.1136/adc.74.4.304. Ireys, H. T., Anderson, G. F., Shaffer, T. J., & Neff, J. M. (1997). Expenditures for care of children with chronic illnesses enrolled in the Washington State Medicaid Program, fiscal year 1993. Pediatrics, 100, 197–204, http://dx.doi.org/10.1542/peds.100.2.197. Kelly, A., Golnik, A., & Cady, R. (2008). A medical home center: Specializing in the care of children with special health care needs of high intensity. Maternal and Child Health Journal, 12, 633–640, http: //dx.doi.org/10.1007/s10995-007-0271-7. Kelly, A., & Hewson, P. (2000). Factors associated with recurrent hospitalization in chronically ill children and adolescents. Journal of Paediatrics and Child Health, 36, 13–18, http://dx.doi.org/10.1046/ j.1440-1754.2000.00435.x. Kuo, D. Z., Cohen, E., Agrawal, R., Berry, J. G., & Casey, P. H. (2011). A national profile of caregiver challenges among more medically complex children with special health care needs. Archives of Pediatric and Adolescent Medicine, 165, 1020–1026, http://dx.doi.org/10.1001/ archpediatrics.2011.172. Lagoe, R. J., Noetscher, C. M., & Murphy, M. P. (2001). Hospital readmission: Predicting the risk. Journal of Nursing Care Quality, 15, 69–83. Landrum, L., & Weinrich, S. (2006). Readmission data for outcomes measurement: Identifying and strengthening the empirical base. Quality Management in Health Care, 15, 83–95. Liese, J., Grill, E., Fischer, B., Roeckl-Wiedmann, I., Carr, D., Belohradsky, B., et al. (2003). Incidence and risk factors of respiratory syncytial virusrelated hospitalizations in premature infants in Germany. European Journal of Pediatrics, 162, 230–236, http://dx.doi.org/10.1007/s00431002-1105-7. Mackie, A. S., Ionescu-Ittu, R., Pilote, L., Rahme, E., & Marelli, A. J. (2008). Hospital readmissions in children with congenital heart disease: A population-based study. American Heart Journal, 155, 577–584, http://dx.doi.org/10.1016/j.ahj.2007.11.003. McKay, M. D., Rowe, M. M., & Bernt, F. M. (1997). Disease chronicity and quality of care in hospital readmissions. Journal for Healthcare Quality, 19, 33–37. McPherson, M., Arango, P., Fox, H., Lauver, C., McManus, M., Newacheck, P. W., et al. (1998). A new definition of children with special health care needs. Pediatrics, 102, 137–139, http://dx.doi.org/10.1542/peds.102.1.137. Medical Home Initiatives for Children With Special Needs Project Advisory Committee (2002). The medical home. Pediatrics, 110, 184–186. National Association of Pediatric Nurse Practitioners (2009). NAPNAP position statement on pediatric health care/medical home: Key issues on delivery, reimbursement, and leadership. Journal of Pediatric Health Care, 23, 23A–24A, http://dx.doi.org/10.1016/j.pedhc.2009.02.005. Neff, J. M., Valentine, J., Park, A., Hicks-Thomson, J., Christakis, D. A., Muldoon, J., et al. (2002). Trends in pediatric hospitalizations of children in Washington State by insurance and chronic condition status, 1991–1998. Archives of Pediatric and Adolescent Medicine, 156, 703–709, http://dx.doi.org/10.1001/archpedi.156.7.703. Oster, A., & Bindman, A. B. (2003). Emergency department visits for ambulatory care sensitive conditions. Medical Care, 41, 198–207. Palfrey, J. S., Sofis, L. A., Davidson, E. J., Liu, J., Freeman, L., & Ganz, M. L. (2004). The Pediatric Alliance for Coordinated Care: Evaluation of a medical home model. Pediatrics, 113, 1507–1516. Patient Protection and Affordable Care Act, H.R.3590, 111th US Congress (2010). Peter, S., Chaney, G., Zappia, T., Van Veldhuisen, C., Pereira, S., & Santamaria, N. (2011). Care coordination for children with complex care

Hospital Readmissions and Repeat Emergency needs significantly reduces hospital utilization. Journal for Specialists in Pediatric Nursing, 16, 305–312, http://dx.doi.org/10.1111/j.17446155.2011.00303.x. Pollack, H. A., Dombkowski, K. J., Zimmerman, J. B., Davis, M. M., Cowan, A. E., Wheeler, J. R., et al. (2004). Emergency department use among Michigan children with special health care needs: An introductory study. Health Services Research, 39, 665–692. Pollack, H. A., Wheeler, J. R., Cowan, A. E., & Freed, G. L. (2007). The impact of managed care enrollment on emergency department use among children with special health care needs. Medical Care, 45, 139–144. Raphael, J. L., Zhang, Y., Liu, H., Tapia, C. D., & Giardino, A. P. (2009). Association of medical home care and disparities in emergency care utilization among children with special health care needs. Academic Pediatrics, 9, 242–248. Reynolds, S., Desguin, B., Uyeda, A., & Davis, A. T. (1996). Children with chronic conditions in a pediatric emergency department. Pediatric Emergency Care, 12, 166–168. Roeckl-Wiedmann, I., Liese, J., Grill, E., Fischer, B., Carr, D., & Belohradsky, B. (2003). Economic evaluation of possible prevention of RSV-related hospitalizations in premature infants in Germany. European Journal of Pediatrics, 162, 237–244, http://dx.doi.org/ 10.1007/s00431-002-1106-6. Sallis, J. F., Owen, N., & Fisher, E. B. (2008). Ecological models of health behavior. In K. Glanz, B. K. Rimer, & K. Viswanath (Eds.), Health behavior and health education (pp. 465–485). (4th ed.). San Francisco, CA: Jossey-Bass. Santelli, J., Kouzis, A., & Newcomer, S. (1996). School-based health centers and adolescent use of primary care and hospital care. Journal of Adolescent Health, 19, 267–275.

339 Silva, D. T., Hagan, R., & Sly, P. D. (1995). Home oxygen management of neonatal chronic lung disease in western Australia. Journal of Paediatrics and Child Health, 31, 185–188. Simon, T. D., Berry, J., Feudtner, C., Stone, B. L., Sheng, X., Bratton, S. L., et al. (2010). Children with complex chronic conditions in inpatient hospital settings in the United States. Pediatrics, 126, 647–655, http: //dx.doi.org/10.1542/peds.2009-3266. Stokols, D. (1996). Translating social ecological theory into guidelines for community health promotion. American Journal of Health Promotion, 10, 282–298. Sutton, D., Stanley, P., Babl, F. E., & Phillips, F. (2008). Preventing or accelerating emergency care for children with complex healthcare needs. Archives of Disease in Childhood, 93, 17–22, http://dx.doi.org/ 10.1136/adc.2007.117960. van der Lee, J. H., Mokkink, L. B., Grootenhuis, M. A., Heymans, H. S., & Offringa, M. (2007). Definitions and measurement of chronic health conditions in childhood: A systematic review. Journal of the American Medical Association, 297, 2741–2751, http://dx.doi.org/10.1001/ jama.297.24.2741. Wagner, E. H., Davis, C., Sachaefer, J., Von Korff, M., & Austin, B. (1999). A survey of leading chronic disease management programs: Are they consistent with the literature? Managed Care Quarterly, 7, 56–66. Whittemore, R., & Knafl, K. (2005). The integrative review: Updated methodology. Journal of Advanced Nursing, 52, 546–553. Yamamoto, L. G., Zimmerman, K. R., Butts, R. J., Anaya, C., Lee, P., Miller, N. C., et al. (1995). Characteristics of frequent pediatric emergency department users. Pediatric Emergency Care, 11, 340–346.