- Email: [email protected]
Relationships between impairment and physical disability as measured by the functional independence measure
566
Relationships Between Impairment and Physical Disability as Measured by the Functional Independence Measure Allen W. Heinemann, Carl Granger, MD
PhD, John Michael Linacre, PhD, Benjamin D. Wright, PhD, Byron B. Hamilton,
MD, PhD,
ABSTRACT. Heinemann AW, Linacre JM, Wright BD, Hamilton BB, Granger C. Relationships between impairment and physical disability as measured by the Functional Independence Measure. Arch Phys Med Rehabil 1993;74: 566-573. l This study was conducted to scale the Functional Independence Measure (FIM) with Rasch Analysis and to determine the similarity of scaled measures across impairment groups. The results show that the FIM contains two fundamental subsets of items: one measures motor and the second measures cognitive function. Rasch analysis of the Uniform Data System for Medical Rehabilitation patient sample yielded interval measures of motor and cognitive functions. The validity of the FIM was supported by the patterns of item difficulties across impairment groups. Adequate clinical precision of the FIM was demonstrated, though suggestions for improvement emerged. The frequency of misfit between patients and the performance scales varied across impairment groups, but was acceptable. The results of this project will enable clinicians and researchers to plan cost-effective treatment by providing a valid measure of disability. 0 1993 by the American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and
Rehabilitation
Clinicians the urgent
and researchers
in rehabilitation
acknowledge
need to demonstrate and improve the reliability and validity of instruments to assess the functional status of patients. Medical rehabilitation lacks functional assessment scales with generalizability across programs and patients because not enough effort has been expended on the psychometric properties of measures: standardization, scalability, reliability, and validity. Just as physical chemistry thrived as a science when the thermometer was invented to measure temperature, medical rehabilitation is poised for innovation, based on sensitive and reliable instruments to measure patient outcomes. The need for adequate measurement ofdisability is apparent both in patient care and clinical research: for determining compensation, predicting outcome, planning placement, estimating care requirements, and indicating changes in functional status. From a nationally used functional assessment scale, the Functional Independence Measure (FIM), this study constructs functional assessment measures, with properties similar to those expected of physical measurements, using a statistical tool, Rasch analysis. The objectives were to assess the utility of Rasch analysis for scaling the FIM into a measure of disability severity and From the Rehabilitation Institute of Chicago, Department of Physical Medicine and Rehabilitation (Dr. Heinemann). Northwestern University Medical School. Chicago. IL. MESA Psychometric Laboratory. Department of Education (Drs. Linacre. Wright). University of Chicago. Chicago. IL, Center for Functional Assessment Research (Drs. Hamilton, Granger), State University of New York at Buffalo. Buffalo, NY. This research supported by the National Institute on Disability and Rehabilitation Research (H133C90167) and the Centers for Disease Control (R49/CCR503609). Submitted for publication October 15. 1991. Accepted in revised form July 21, 1992. Reprint requests to Allen W. Heinemann, PhD, 44X East Ontarto Street. Suite 650, Chicago. IL 606 I I. 0 1993 by the American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation 0003.9993/93/7406-0218$3.00/O
Arch Phys Med Rehabil Vol74, June 1993
to determine the extent to which measures of disability are comparable for patients with differing impairments. FUNCTIONAL ASSESSMENT To be useful, functional measures must be constructed that have reliability and validity as well as clinical significance.le4 Reliability is the precision of measurement. Construct validity is concerned with whether the instrument measures the characteristic it purports to measure. Items should cooperate to support a single construct, and within that construct, they should be ordered in difficulty according to clinical experience. Even when indices of disability appear to have high reliability, they may still not yield data that is suitable for numerical analysis because they are restricted to ordinal data. A measurement procedure that can develop reliable. valid, and interval-scaled functional assessment measures is Rasch analysis.5 FIM items are recorded on an ordinal scale of functional dependence to independence; these data, as they stand, only allow rank ordering. Rasch analysis, however, can transform these ratings to an interval scale on which the intervals between units of the scale have equal values. Measures from an interval scale can be validly subjected to the usual statistical analyses that relate independent and dependent variables. In order to produce a valid measurement tool, ordinal functional assessments must be transformed to interval measurements.6 This is necessary if one wants to measure an individual’s functional ability or make quantitative comparisons between individuals or across groups of individuals. INTRODUCTION TO RASCH MEASUREMENT Rasch analysis is a statistical technique for constructing interval measures from ordinal data designed to be unidimensional. The data in this study were ratings of the degree
IMPAIRMENT AND FIM-MEASURED DISABILITY. Heinemann
of competence with which patients perform various behavioral tasks. The FIM raw scores are counts oflevels ofperformance that the person demonstrates. When the underlying variations in behavior are dominated by one dimension, each patient can be characterized by a single latent ability measure, and each item by a single latent difficulty calibration both of which are positions along a shared linear measurement continuum. These latent measures and calibrations can not be observed directly. but are inferred from the ordinal observations obtained when patients are rated on the behavioral tasks. The observations are modeled as a realization of those latent measures and calibrations. When the data approximate unidimensionality well enough. the measures become useful in the diagnosis and evaluation of patients’ treatment. Rasch analysi?.’ provides the means of calibrating a scale structure on which linear measures underlying the observations are defined. The measures are expressed initially in log-odds units (logits). HYPOTHESIS Initially. we hypothesized that the items comprising the FIM would form one unidimensional scale with item difficulties being consistent across impairment groups. METHODS
Sample Rehabilitation inpatients who received services at hospitals subscribing to the Uniform Data System (UDS) for Medical Rehabilitation comprised the sample. More than 190 facilities subscribed to the UDS Data Management Service, and contributed 33,709 records of rehabilitation admissions from January t 987. through June 1989. Patients admitted only for evaluations or readmitted to rehabilitation were excluded from this analysis: the 27,669 cases analyzed included admission and discharge FIM ratings for each patient admitted for their first inpatient rehabilitation. Table 1 shows the number of patients in each of 13 UDSdefined impairment groups. Table 1: Impairment Distribution of Sample --__ Impairment
I 4. I R.
Group
Stroke-Left hemiparesls Stroke-Right hemiparesis IC. Stroke-Bilateral 3 Brain dysfunction 7 Neurologic conditions i: Spinal cord dysfunction 5 Amputation 6. Arthritis 7. Back pain 8. Orthopedic impairment 9. Cardiac impairment IO. Pulmonaq impairment I I. Burns I’. Congenital deformit) I3 Other impairment Total
n 5.008 4.745 339 7.477 I .394 I.727 I .400 1,334 152 6.X60 IX! 162 47 3x
1.374 17.669
Percent 18 17
I 9 5 6 5 5 3 25
567
Instruments The Functional Independence Measure (FIM) was developed by the American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation Task Force to Develop a National Uniform Data System for Medical Rehabilitation8 to rate severity of patient disability and the outcomes of medical rehabilitation. It assesses self-care (eating, grooming. bathing. dressing upper body. dressing lower body, toileting), sphincter management (bladder and bowel management), mobility (transfers to bed, chair or wheelchair, to toilet. and to tub or shower), locomotion (walking or wheelchair propulsion. stair climbing), communication (comprehension and expression). and social cognition (social interaction, problem solving, memory) on a seven-level scale. The scale is anchored by extreme ratings of total assistance ( 1) and complete independence (7). and considers extent of assistance. supervision, and use of adaptive equipment. The UDS data set also includes patient demographic characteristics. diagnoses, impairment groups. length of hospital inpatient stay. and hospital charges. FIM data were reported by clinicians within 72 hours of admission and discharge using published scoring criteria.” Inter-rater agreement of FIM scores was assessed by comparing pairs of clinicians ratings for a sample of ten inpatients from each hospital. The criteria included a FIM score intra-class correlation coefficient of .90 or greater; five of the six FIM subscores meeting the same criterion with none below .75; and at least 14 of the 18 FIM items equaling or exceeding a Kscore of .45. Data from hospitals not meeting these criteria were placed in a separate file and excluded from aggregation for UDS reports and for this study.
Statistical Analyses Rasch analysis of FIM items was conducted with BIGSCALE.” a standard computer program for the analysis of rating scale data.a Our goal was to construct a set of linear measures that are useful over as large a range of impairments as possible without losing clear distinctions between patients with different impairments. Because observations can never be more than approximate realizations of latent parameters, the estimates obtained from Rasch (or any other) analysis cannot be exact parameter values. Consequently BIGSCALE obtains for each parameter (1) its estimated value. (2) a standard error for that estimate. indicating the precision (reliability) of the estimate. and (3) fit statistics, indicating the extent to which the model specifications of unidimensionality have been usefully met by the data. The FIM does not indicate the further (full) extent of dependence of patients rated “Total Assist” on ull items, nor the further extent of independence of patients rated “Complete Independence” on all items. The infinite range of functional possibilities implied below the floor and above the ceiling of available FIM ratings was represented by finite values just beyond the most extreme estimable measures. Linacre and colleagues” demonstrated for at1 impair-
Arch Phys Med Rehabil Vol74, June 1993
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IMPAIRMENT AND FIM-MEASURED DISABILITY, Heinemann
errors of items indicated acceptable item fit and the coherence of items within each measure. The standard error of the measures was always of the order of .O1 logits because of the large sample sizes. The mean squares for both measures were always within 3% of 1.O (.98 to 1.03) indicating excellent item fit. Three motor items tended to fit less well: bowel management, bladder management, and stair climbing. This finding may reflect the fact that clinicians rate both management and continence in the bowel and bladder items; strength, safety, and opportunity may affect ratings on stair climbing. Nonetheless, the fit statistics for the scale as a whole were good. Readers interested in the item-fit details for each group may contact the first author. The matrices of motor and cognitive item difficulties were factor analyzed’* to determine the proximity of the 15 impairment groups with respect to variable definition. Principal component decomposition without rotation was used.13 Factor analysis was not used to distinguish motor and cognitive items, but rather to learn if impairment groups experience the item difficulties similarly. A shared definition of motor function should work the same way for all impairment groups: factor analysis reveals the extent to which this definition is shared. As discussed below, this result was observed, though slight variations were found. Table 2 shows the factor loadings of the motor items: table 3 shows the factor loadings of the cognitive items. The three largest factors are reported. But, only the first factors RESULTS had eigenvalues greater than 1.0 accounting for 95% and 92% of the variance for motor and cognitive items. The Sample Characteristics minuscule second and third factors are reported to bring The sample of 27,669 were 53% women: 90% white: 44% out the relative uniqueness of several impairment groups. married: 38% separated, divorced and widowed; and 18% In order to understand the implications of the factors in never married. The mean age was 62.1 years. The mean terms of FIM items, we compared FIM calibrations of the number of days from onset of impairment that precipitated impairment groups found at the extremes of factors. For the rehabilitation admission was 113.2 days. The mean motor items, Factor 1 is defined by the difficulty of feeding length of rehabilitation stay was 29.5 days. relative to stair climbing and locomotion. Though stair Each of the 13 impairment groups were analyzed sepa- climbing is always the most difficult item and feeding the rately. The stroke sample was further separated into three easiest item, patients with amputations (fig 2) found stair subgroups: left hemiparesis, right hemiparesis, and bilateral climbing and locomotion to be relatively difficult, while involvement. The heterogeneous composition of the pain patients with burns (fig 2) found feeding to be more chalcategory forced us to concentrate only on cases with back lenging. Factor 2 is defined by the difficulty of bladder and pain for that group. bowel management. Patients with spinal dysfunction and congenital deformities (fig 2) found bowel and bladder manScaling Characteristics of the FIM Across agement to be more difficult than did patients with pulmoImpairment Groups nary impairment (fig 3). The relative difficulty of items across impairment groups Figures 1, 2, and 3 show consistent motor item difficulties across impairment groups. The large negative logit val- parallels the actual nature of these groups’ medical condiues indicate that feeding and grooming are the easiest mo- tion. The similarity of various impairment groups that emerged from factor analyses of the item difficulties paraltor items on which to achieve an independent rating, lels clinical experience, supporting the validity of the meawhereas stair climbing. tub/shower transfers and locomosurement system. For example, bladder and bowel managetion, with large positive logit values, are the most difficult. Figures 4, 5, and 6 show the consistency across groups of ment were relatively easier items for patients with stroke, the five cognitive items. Comprehension and expression are brain dysfunction, neurologic conditions, cardiac condithe easiest items; problem solving is the most difficult. tions, pulmonary conditions, burns, and other disabling Item fit statistics for the separate set of motor and cogni- impairments. Bladder and bowel management were relative items for all patients were reported by Linacre” and tively harder items for patients with spinal cord dysfunction and congenital deformities. Feeding was a relatively easy found to be acceptable. Similarly, for each impairment group reported here, the standard deviations of item diffi- item whereas stairs were a relatively harder item for patients with amputations, arthritis, back pain, and orthopedic conculties, average mean squares of items, and typical standard ment groups combined that the optimal Rasch scaling solution to the FIM is to distinguish between motor and cognitive items. The results of combining all 18 items were much less satisfactory because the fit statistics revealed a large proportion of misfitting items. Examination of these misfitting items revealed that the motor and cognitive items formed separate groupings. Consequently, we examined the subset of I3 motor and five cognitive items separately. The item difficulties for each FIM item comprising the motor and cognitive scales across each of the impairment groups were computed first. The comparability of item difficulties at admission and discharge was examined. Though patient performance is expected to improve during rehabilitation, a finding that some items were relatively more difficult at admission or discharge would interfere with the quantitative study of rehabilitation because it would require that FIM measures be constructed differently at admission and discharge. The result necessary for a measure of change is to find item difficulties sufficiently similar at both times that a generalized measure on which change during treatment could be measured is possible. Linacre” examined this issue by calculating item difficulties at admission and discharge separately. They found that the item difficulties were sufficiently similar at both time points to allow us to combine admission and discharge ratings for the analyses described below.
Arch Phys Med Rehabil Vol74, June 1993
IMPAIRMENT
Fig l-Line graphs are plots of item difficulties for 13 FIM motor items (in logits) for patients with stroke resulting in left hemiparesis, right hemiparesis, and bilateral impairment: brain dysfunction; neurologic impairments; and the average item difficulties across all 15 impairment groups. Group numbers correspond to labeling used in tables 1,2, and 3. +, IA stroke-left: -t, IB stroke-right; W. 1C stroke-bilateral; 0,2 brain dysfunction: X, 3 neurologic; f, average.
AND FIM-MEASURED
DISABILITY,
Heinemann
569
Y
‘Et
3
ditions: the converse was true for patients with burns, brain dysfunction. and congenital deformities. Factor analysis was also used to identify similarities and differences between the impairment groups on the cognitive item difficulties. Table 3 shows that one factor accounted for the majority of the variance among the cognitive items. The first factor was defined by the relative difficulty of verbal expression. Patients with right hemiparesis following stroke found verbal expression to be relatively difficult (fig 4) whereas patients with brain dysfunction found this task to be relatively easy (fig 4). The second factor was defined by the difficulty of social interaction. Pa-
tients with right hemiparesis following stroke found this task to be relatively easy (fig 4) whereas patients with spinal dysfunction found this task to be relatively difficult (fig 5). Impairment groups that appeared most similar on the cognitive measure include patients with ( 1) left hemiparesis, bilateral strokes. brain dysfunction and congenital deformities: (2) patients with stroke resulting in right hemiparesis: and (3) all other impairments. Patients with right hemiparesis found verbal expression to be more difficult than patients with left hemiparesis and bilateral strokes. brain dysfunction, and congenital deformities. Patients with left hemiparesis, bilateral strokes. brain dysfunction.
---
Function
Fig 2-Line graphs are plots of item difficulties for 13 FIM motor items (in logits) for patients with amputations, arthritis, orthopedie impairments, spinal cord dysfunction, congenital deformities, and the average item difficulties across all impairment groups. Group numbers correspond to labeling used in tables 1,2, and 3. +, 5 amputation: 8, 4 spinal cord; -t, 6 arthritis: -S, 8 orthopedic; X, 12 congenital; t, average.
Arch Phys MeU Rehabil Vol74, June 1993
570
IMPAIRMENT
AND FIM-MEASURED
DISABILITY,
Heinemann
Fig 3-Line graphs are plots of item difficulties for 13 FIM motor items (in logits) for patients with back pain, cardiac impairment, pulmonary impairment, burns, other impairments, and the average item difficulties across all 15 impairment groups. Group numbers correspond to labeling used in tables 1, 2, and 3. +, 7 pain; *, 10 pulmonary; 0,ll burns; t, 9 cardiac; X, 13 other impairment; t, average.
congenital deformities. and stroke resulting in right hemiparesis were distinguished from all other groups by the relatively less difficulty of social interaction.
undergone important changes. This project brings together these two advancing fields at an opportune moment. The FIM, a largely empirically developed instrument, has emerged, pushed by a growing consensus that there is a need for a uniform, valid. reproducible, precise, and feasible-to-use instrument to assess patient function.’ Rasch analysis has developed as a useful technique to evaluate instruments that are intended to measure scaled behavior,4,5,7including disability. 14.15 In responding to these needs and opportunities, this project examined the scalability of the FIM using Rasch analysis. FIM item difficulties vary somewhat across impairment
DISCUSSION The measurement characteristics of functional assessment instruments used in medical rehabilitation have come under scrutiny as the field has moved toward uniformity in assessment of severity of disability and quantification of rehabilitation outcomes. 3.4At the same time, measurement concepts and techniques applied to human behavior have
Fig d-Line graphs are plots of item difficulties for five FIM cognitive items (in logits) for patients with stroke resulting in left hemiparesis, right hemiparesis, and bilateral impairment, brain dysfunction, neurologic impairments, and the average item difficulties across all 15 impairment groups. Group numbers correspond to labeling used in tables 1, 2, and 3. _), IA stroke-left; t, 1B stroke right; W, 1C stroke bilateral; 8, 2 brain dysfunction; X, 3 neurologic; f , average.
~1 0.2 ‘3 ci
-0.8
Arch Phys Med Rehabil VoI74, June 1993
I
Verbal Expression
,
Auditoty Comprehension
I
Social Interaction
Function
I
Memory
I
Problem Solving
IMPAIRMENT
Fig !&Line graphs are plots of item difficulties for tive FIM cognitive items (in logits) for patients with spinal cord dysfunction, back pain, orthopedic impairments, cardiac impairment. other impairments, and the average item difficulties across all 15 impairment groups. Group numbers correspond to labeling used in tables 1, 2. and 3. -W. 4 spinal cord; t, 7 pain; *. 8 orthopedic: -ft, 9 cardiac: +C, 13 other impairment; -t, average.
Verbal
AND FIM-MEASURED
Auditory
Expression
Comprehension
L
41.8
Verbal
I
Expression
Auditory
571
Heinemann
Social Interaction
Memory
Problem
Solving
Function
groups. Fo,r the most part, one motor scale can accommodate all impairment groups, except patients with back pain and burns. One cognitive scale is useful for all impairment groups except patients with strokes. brain dysfunction, and congenital impairments. These groups can be managed with a second cognitive scale. The motor scale appears to be generally applicable because back pain and burns are not major diagnoses for most inpatient medical rehabilitation programs. The two cognitive scales are manageable and possibly mergable. depending on how they perform in clinical use. Further study is needed to see if that is feasible.
U.6- --I__ “---~=-----3
DISABILITY,
1
Comprehension
,
Social Interaction
Function
The construct validity of the FlM is supported by the pattern of results. Specific items were more difficult for some impairment groups in ways that make clinical sense. Patients with amputations found stair climbing and locomotion to be relatively difficult; patients with burns found feeding to be more challenging than did other impairment groups. The factor analysis of motor item difficulties across the impairment groups reveal distinct brain, limb. and spinal cord dysfunction. With the cognitive items, verbal expression distinguished patients with right and left hemiparesis following stroke. These distinctions parallel clinical
,
Memory
Problem
I
Solving
I
Fig 6-Line graphs are plots of item difficulties for five FIM cognitive items (in logits) for patients with amputations, arthritis, pulmonary impairment, burns, congenital impairments, and the average item difticulties across all 15 impairment groups. Group numbers correspond to labeling used in tables 1, 2, and 3. +, 5 amputation; t, 6. arthritis; +K, 10 pulmonary; 8.11 burns; *, 12 congenital: f, average.
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experience. They show that the FIM measures fundamental aspects of disability. Specific suggestions for revision of the FIM also emerge from these analyses. The number of transfer items could be reduced because they assess partially redundant aspects of function. Bowel and bladder items could be redefined as two separate items that distinguish levels of assistance required from frequency of incontinence. Three items that have two modes-locomotion (wheelchair vs walking). comprehension (auditory vs visual), and expression (vocal vs nonvocal)-could be rated as separate items. An easier stair climbing item could be developed that could quantify intermediate levels of ability, Finally, “not tested” ratings could be assigned a value other than “ 1” (total assist) so as to distinguish these different situations. A limitation of this study is that it focussed on inpatients undergoing medical rehabilitation at hospitals that subscribe to the Uniform Data System. Though the representativeness of the sample appears good, given the number of subscribers and their geographic distribution, it is possible that subscribing hospitals are not representative of all sites where comprehensive rehabilitation is delivered. The utility of these results to outpatients, skilled nursing facility, and home-based service patients and others needs to be demonstrated. In summary, we found that the FIM could be scaled as an interval measure for each of the 13 impairment groups. Motor and cognitive aspects of function were important to be distinguished and were treated separately. Item difficulties varied slightly across impairment groups, reflecting the unique impact of various kinds of impairments. The validity of the FIM is supported by this pattern of item difficulties and the factor analysis. The results make clear the fact that raw scores are not linear and should not be used in parametric statistical analyses. These results have immediate application in quality assurance and program evaluation efforts. Clinicians and researchers in rehabilitation medicine now have a linear mea-
Impairment
Group
Factor Loadings Impairment
Eigenvalues Percent of variance IA. Stroke-Left hemiparesis 19. Stroke-Right hemiparesis If. Stroke-Bilateral 3 Brain dysfunction 3:Neurologic 4. Spinal cord dysfunction 5. Amputation 6. Arthritis 7. Back pain 8. Orthopedic impairment 9. Cardiac impairment 10. Pulmonary impairment 1I. Burns 12. Congenital deformity 13. Other impairment
Arch Phys Med Rehabil Vol74, June 1993
2
3
7.77 95.18 0.12 0.6’ 0.58 0.53 0.66 0.68 1.04 0.89 0.11 0.93 0.74 0.72 0.41 0.53 0.72
0.21 2.54 0.06 0.02 0.04 0.03 -0.07 -0.25 -0.07 0.03 -0.00 0.00 0.10 0.24 0.12 -0.22 -0.03
0.08 0.92 0.02 0.06 0.05 0.04 0.03 -0.01 0.11 -0.09 -0.15 -0.10 0.04 0.07 -0.09 0.04 -0.00
Group
Eigenvalues Percent of variance I A. Stroke-Left hemipdresis 19. Stroke-Right hemiparesis IC. Stroke-Bilateral 2. Brain dysfunction 3. Neurologic 4. Spinal cord dysfunction
5. 6. 7. 8. 9. IO.
Amputation Arthritis Back pain Orthopedtc Cardiac Pulmonary I 1. Burns 12. Congenital 13. Other
1
Z
3
7.99 91.55 0.49 0.19 0.43 0.61 0.46
0.20 6.13 PO.07 PO.2 I m-o.13 PO.13 0.02
0.04
0.48 0.42 0.31 0.48 0.46 0.50 0.11 0.37 0.61 0.48
0.19 0.08 0.0 I 0.13 0.02 0.13 0.09 0.05 -0.17 0.03
I.25 0.01 PO.03 PO.03 PO.09 PO.03
-0.03 0.01
0.03 0.03 0.0 I -0.08 0.01 0.09 0.11 -0.01
sure whose scoring is not dependent on local data. Discharge expectancies can be established based on these scaling results, and programs can evaluate their outcomes in terms of attainment of discharge performance. Demonstration of patient function as consisting of two distinct aspects of behavior suggests that both domains are important in helping patients live independently and in estimating caregiver requirements. Acknowledgments:
Mamott
and Richard
The authors extend their appreciation Kayton for technical data analysis.
to Brian
References
5
I
Heinemann
Table 3: Cognitive Item Difficulties: Factor Analysis
Table 2: Motor Item Difficulties: Factor Analysis Factor Loadings
DISABILITY,
6
7 8
9
Feinstein AR, Josephy BR. Wells CK. Scientific and clinical problems in indexes of functional disability. Ann Int Med I986:105:413-20. Keith RA. Functional assessment measures in medical rehabilitation: current status. Arch Phys Med Rehabil 1984:65:74-X. Merbitz C. Morris J. Grip J. Ordinal scales and foundations of misinference. Arch Phys Med Rehabil 1989:70:308- 12. Wright BD. Linacre JM. Observations are always ordinal: measurements. however, must be interval. Arch Phys Med Rehabil 1989;70:857-60. Rasch G. Probabilistic models for some intelligence and attainment tests. Chicago: University of Chicago. 1980. Lambert RW. Wright BD. Inter-institutional differences in implementation of a functional assessment instrument. Arch Phys Med Rehabil 1989:70:A-5. Wright BD, Masters G. Rating scale analysis: Rasch measurement. Chicago: MESA. 1982. Hamilton 99. Granger CV. Sherwin FS, Zielezny M, Tashman JS. A uniform national data system for medical rehabilitation. in: Fuhrer MJ. ed. Rehabilitation outcomes: analvsts and measurement. Baltimore: Brooks, 1987. Guide for Use of the Uniform Data Set for Medical Rehabilitation. Research
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1987. Wright BD, Linacre JM, Schultz M. BIGSCALE:
11.
for rating scale analysis. Linacre JM. Heinemann
Buffalo:
A Rasch program Chicago: MESA, 1988. AW. Wright BD, Granger C, Hamilton 99.
The Functional Independence Measure as a measure of disabilitv. Research Report 9 1-O1. Chicaao: Rehabilitation Services Evaluation Unit, Rehabilitation Institute if Chicago. 199 I, 12 Harman HH. Modern factor analysis. 2nd ed. Chicago: University of Chicago,
1967.
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The system for statistics. Evanston, IL: Sytat,
Incorporalcd, 1986. 4. McArthur DL. (‘ohen MJ. Schandler SL. Rasch analysis of functional assessment scales: an example using pain. .Arch Phys Med Rehahil I99 I ;7’:29h-304, -r _ Silverstein H. FIshcr WP. Kllgore KM, Harley JP. Harvey RF. App!),inp psyzhometnc
criteria to functional
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tation: II. detining 1992:73:507-l x.
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Supplier a. Benjamin Wright. MD. Michael Llnacrc. South Kimbark. ChIcago. IL. 606q7.
L\rih
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Rchahil
Press. 5X3.5
Arch Phys Med Rehabil Vol74, June 1993
Relationships Between Impairment and Physical Disability as Measured by the Functional Independence Measure Allen W. Heinemann, Carl Granger, MD
PhD, John Michael Linacre, PhD, Benjamin D. Wright, PhD, Byron B. Hamilton,
MD, PhD,
ABSTRACT. Heinemann AW, Linacre JM, Wright BD, Hamilton BB, Granger C. Relationships between impairment and physical disability as measured by the Functional Independence Measure. Arch Phys Med Rehabil 1993;74: 566-573. l This study was conducted to scale the Functional Independence Measure (FIM) with Rasch Analysis and to determine the similarity of scaled measures across impairment groups. The results show that the FIM contains two fundamental subsets of items: one measures motor and the second measures cognitive function. Rasch analysis of the Uniform Data System for Medical Rehabilitation patient sample yielded interval measures of motor and cognitive functions. The validity of the FIM was supported by the patterns of item difficulties across impairment groups. Adequate clinical precision of the FIM was demonstrated, though suggestions for improvement emerged. The frequency of misfit between patients and the performance scales varied across impairment groups, but was acceptable. The results of this project will enable clinicians and researchers to plan cost-effective treatment by providing a valid measure of disability. 0 1993 by the American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and
Rehabilitation
Clinicians the urgent
and researchers
in rehabilitation
acknowledge
need to demonstrate and improve the reliability and validity of instruments to assess the functional status of patients. Medical rehabilitation lacks functional assessment scales with generalizability across programs and patients because not enough effort has been expended on the psychometric properties of measures: standardization, scalability, reliability, and validity. Just as physical chemistry thrived as a science when the thermometer was invented to measure temperature, medical rehabilitation is poised for innovation, based on sensitive and reliable instruments to measure patient outcomes. The need for adequate measurement ofdisability is apparent both in patient care and clinical research: for determining compensation, predicting outcome, planning placement, estimating care requirements, and indicating changes in functional status. From a nationally used functional assessment scale, the Functional Independence Measure (FIM), this study constructs functional assessment measures, with properties similar to those expected of physical measurements, using a statistical tool, Rasch analysis. The objectives were to assess the utility of Rasch analysis for scaling the FIM into a measure of disability severity and From the Rehabilitation Institute of Chicago, Department of Physical Medicine and Rehabilitation (Dr. Heinemann). Northwestern University Medical School. Chicago. IL. MESA Psychometric Laboratory. Department of Education (Drs. Linacre. Wright). University of Chicago. Chicago. IL, Center for Functional Assessment Research (Drs. Hamilton, Granger), State University of New York at Buffalo. Buffalo, NY. This research supported by the National Institute on Disability and Rehabilitation Research (H133C90167) and the Centers for Disease Control (R49/CCR503609). Submitted for publication October 15. 1991. Accepted in revised form July 21, 1992. Reprint requests to Allen W. Heinemann, PhD, 44X East Ontarto Street. Suite 650, Chicago. IL 606 I I. 0 1993 by the American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation 0003.9993/93/7406-0218$3.00/O
Arch Phys Med Rehabil Vol74, June 1993
to determine the extent to which measures of disability are comparable for patients with differing impairments. FUNCTIONAL ASSESSMENT To be useful, functional measures must be constructed that have reliability and validity as well as clinical significance.le4 Reliability is the precision of measurement. Construct validity is concerned with whether the instrument measures the characteristic it purports to measure. Items should cooperate to support a single construct, and within that construct, they should be ordered in difficulty according to clinical experience. Even when indices of disability appear to have high reliability, they may still not yield data that is suitable for numerical analysis because they are restricted to ordinal data. A measurement procedure that can develop reliable. valid, and interval-scaled functional assessment measures is Rasch analysis.5 FIM items are recorded on an ordinal scale of functional dependence to independence; these data, as they stand, only allow rank ordering. Rasch analysis, however, can transform these ratings to an interval scale on which the intervals between units of the scale have equal values. Measures from an interval scale can be validly subjected to the usual statistical analyses that relate independent and dependent variables. In order to produce a valid measurement tool, ordinal functional assessments must be transformed to interval measurements.6 This is necessary if one wants to measure an individual’s functional ability or make quantitative comparisons between individuals or across groups of individuals. INTRODUCTION TO RASCH MEASUREMENT Rasch analysis is a statistical technique for constructing interval measures from ordinal data designed to be unidimensional. The data in this study were ratings of the degree
IMPAIRMENT AND FIM-MEASURED DISABILITY. Heinemann
of competence with which patients perform various behavioral tasks. The FIM raw scores are counts oflevels ofperformance that the person demonstrates. When the underlying variations in behavior are dominated by one dimension, each patient can be characterized by a single latent ability measure, and each item by a single latent difficulty calibration both of which are positions along a shared linear measurement continuum. These latent measures and calibrations can not be observed directly. but are inferred from the ordinal observations obtained when patients are rated on the behavioral tasks. The observations are modeled as a realization of those latent measures and calibrations. When the data approximate unidimensionality well enough. the measures become useful in the diagnosis and evaluation of patients’ treatment. Rasch analysi?.’ provides the means of calibrating a scale structure on which linear measures underlying the observations are defined. The measures are expressed initially in log-odds units (logits). HYPOTHESIS Initially. we hypothesized that the items comprising the FIM would form one unidimensional scale with item difficulties being consistent across impairment groups. METHODS
Sample Rehabilitation inpatients who received services at hospitals subscribing to the Uniform Data System (UDS) for Medical Rehabilitation comprised the sample. More than 190 facilities subscribed to the UDS Data Management Service, and contributed 33,709 records of rehabilitation admissions from January t 987. through June 1989. Patients admitted only for evaluations or readmitted to rehabilitation were excluded from this analysis: the 27,669 cases analyzed included admission and discharge FIM ratings for each patient admitted for their first inpatient rehabilitation. Table 1 shows the number of patients in each of 13 UDSdefined impairment groups. Table 1: Impairment Distribution of Sample --__ Impairment
I 4. I R.
Group
Stroke-Left hemiparesls Stroke-Right hemiparesis IC. Stroke-Bilateral 3 Brain dysfunction 7 Neurologic conditions i: Spinal cord dysfunction 5 Amputation 6. Arthritis 7. Back pain 8. Orthopedic impairment 9. Cardiac impairment IO. Pulmonaq impairment I I. Burns I’. Congenital deformit) I3 Other impairment Total
n 5.008 4.745 339 7.477 I .394 I.727 I .400 1,334 152 6.X60 IX! 162 47 3x
1.374 17.669
Percent 18 17
I 9 5 6 5 5 3 25
567
Instruments The Functional Independence Measure (FIM) was developed by the American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation Task Force to Develop a National Uniform Data System for Medical Rehabilitation8 to rate severity of patient disability and the outcomes of medical rehabilitation. It assesses self-care (eating, grooming. bathing. dressing upper body. dressing lower body, toileting), sphincter management (bladder and bowel management), mobility (transfers to bed, chair or wheelchair, to toilet. and to tub or shower), locomotion (walking or wheelchair propulsion. stair climbing), communication (comprehension and expression). and social cognition (social interaction, problem solving, memory) on a seven-level scale. The scale is anchored by extreme ratings of total assistance ( 1) and complete independence (7). and considers extent of assistance. supervision, and use of adaptive equipment. The UDS data set also includes patient demographic characteristics. diagnoses, impairment groups. length of hospital inpatient stay. and hospital charges. FIM data were reported by clinicians within 72 hours of admission and discharge using published scoring criteria.” Inter-rater agreement of FIM scores was assessed by comparing pairs of clinicians ratings for a sample of ten inpatients from each hospital. The criteria included a FIM score intra-class correlation coefficient of .90 or greater; five of the six FIM subscores meeting the same criterion with none below .75; and at least 14 of the 18 FIM items equaling or exceeding a Kscore of .45. Data from hospitals not meeting these criteria were placed in a separate file and excluded from aggregation for UDS reports and for this study.
Statistical Analyses Rasch analysis of FIM items was conducted with BIGSCALE.” a standard computer program for the analysis of rating scale data.a Our goal was to construct a set of linear measures that are useful over as large a range of impairments as possible without losing clear distinctions between patients with different impairments. Because observations can never be more than approximate realizations of latent parameters, the estimates obtained from Rasch (or any other) analysis cannot be exact parameter values. Consequently BIGSCALE obtains for each parameter (1) its estimated value. (2) a standard error for that estimate. indicating the precision (reliability) of the estimate. and (3) fit statistics, indicating the extent to which the model specifications of unidimensionality have been usefully met by the data. The FIM does not indicate the further (full) extent of dependence of patients rated “Total Assist” on ull items, nor the further extent of independence of patients rated “Complete Independence” on all items. The infinite range of functional possibilities implied below the floor and above the ceiling of available FIM ratings was represented by finite values just beyond the most extreme estimable measures. Linacre and colleagues” demonstrated for at1 impair-
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errors of items indicated acceptable item fit and the coherence of items within each measure. The standard error of the measures was always of the order of .O1 logits because of the large sample sizes. The mean squares for both measures were always within 3% of 1.O (.98 to 1.03) indicating excellent item fit. Three motor items tended to fit less well: bowel management, bladder management, and stair climbing. This finding may reflect the fact that clinicians rate both management and continence in the bowel and bladder items; strength, safety, and opportunity may affect ratings on stair climbing. Nonetheless, the fit statistics for the scale as a whole were good. Readers interested in the item-fit details for each group may contact the first author. The matrices of motor and cognitive item difficulties were factor analyzed’* to determine the proximity of the 15 impairment groups with respect to variable definition. Principal component decomposition without rotation was used.13 Factor analysis was not used to distinguish motor and cognitive items, but rather to learn if impairment groups experience the item difficulties similarly. A shared definition of motor function should work the same way for all impairment groups: factor analysis reveals the extent to which this definition is shared. As discussed below, this result was observed, though slight variations were found. Table 2 shows the factor loadings of the motor items: table 3 shows the factor loadings of the cognitive items. The three largest factors are reported. But, only the first factors RESULTS had eigenvalues greater than 1.0 accounting for 95% and 92% of the variance for motor and cognitive items. The Sample Characteristics minuscule second and third factors are reported to bring The sample of 27,669 were 53% women: 90% white: 44% out the relative uniqueness of several impairment groups. married: 38% separated, divorced and widowed; and 18% In order to understand the implications of the factors in never married. The mean age was 62.1 years. The mean terms of FIM items, we compared FIM calibrations of the number of days from onset of impairment that precipitated impairment groups found at the extremes of factors. For the rehabilitation admission was 113.2 days. The mean motor items, Factor 1 is defined by the difficulty of feeding length of rehabilitation stay was 29.5 days. relative to stair climbing and locomotion. Though stair Each of the 13 impairment groups were analyzed sepa- climbing is always the most difficult item and feeding the rately. The stroke sample was further separated into three easiest item, patients with amputations (fig 2) found stair subgroups: left hemiparesis, right hemiparesis, and bilateral climbing and locomotion to be relatively difficult, while involvement. The heterogeneous composition of the pain patients with burns (fig 2) found feeding to be more chalcategory forced us to concentrate only on cases with back lenging. Factor 2 is defined by the difficulty of bladder and pain for that group. bowel management. Patients with spinal dysfunction and congenital deformities (fig 2) found bowel and bladder manScaling Characteristics of the FIM Across agement to be more difficult than did patients with pulmoImpairment Groups nary impairment (fig 3). The relative difficulty of items across impairment groups Figures 1, 2, and 3 show consistent motor item difficulties across impairment groups. The large negative logit val- parallels the actual nature of these groups’ medical condiues indicate that feeding and grooming are the easiest mo- tion. The similarity of various impairment groups that emerged from factor analyses of the item difficulties paraltor items on which to achieve an independent rating, lels clinical experience, supporting the validity of the meawhereas stair climbing. tub/shower transfers and locomosurement system. For example, bladder and bowel managetion, with large positive logit values, are the most difficult. Figures 4, 5, and 6 show the consistency across groups of ment were relatively easier items for patients with stroke, the five cognitive items. Comprehension and expression are brain dysfunction, neurologic conditions, cardiac condithe easiest items; problem solving is the most difficult. tions, pulmonary conditions, burns, and other disabling Item fit statistics for the separate set of motor and cogni- impairments. Bladder and bowel management were relative items for all patients were reported by Linacre” and tively harder items for patients with spinal cord dysfunction and congenital deformities. Feeding was a relatively easy found to be acceptable. Similarly, for each impairment group reported here, the standard deviations of item diffi- item whereas stairs were a relatively harder item for patients with amputations, arthritis, back pain, and orthopedic conculties, average mean squares of items, and typical standard ment groups combined that the optimal Rasch scaling solution to the FIM is to distinguish between motor and cognitive items. The results of combining all 18 items were much less satisfactory because the fit statistics revealed a large proportion of misfitting items. Examination of these misfitting items revealed that the motor and cognitive items formed separate groupings. Consequently, we examined the subset of I3 motor and five cognitive items separately. The item difficulties for each FIM item comprising the motor and cognitive scales across each of the impairment groups were computed first. The comparability of item difficulties at admission and discharge was examined. Though patient performance is expected to improve during rehabilitation, a finding that some items were relatively more difficult at admission or discharge would interfere with the quantitative study of rehabilitation because it would require that FIM measures be constructed differently at admission and discharge. The result necessary for a measure of change is to find item difficulties sufficiently similar at both times that a generalized measure on which change during treatment could be measured is possible. Linacre” examined this issue by calculating item difficulties at admission and discharge separately. They found that the item difficulties were sufficiently similar at both time points to allow us to combine admission and discharge ratings for the analyses described below.
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Fig l-Line graphs are plots of item difficulties for 13 FIM motor items (in logits) for patients with stroke resulting in left hemiparesis, right hemiparesis, and bilateral impairment: brain dysfunction; neurologic impairments; and the average item difficulties across all 15 impairment groups. Group numbers correspond to labeling used in tables 1,2, and 3. +, IA stroke-left: -t, IB stroke-right; W. 1C stroke-bilateral; 0,2 brain dysfunction: X, 3 neurologic; f, average.
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ditions: the converse was true for patients with burns, brain dysfunction. and congenital deformities. Factor analysis was also used to identify similarities and differences between the impairment groups on the cognitive item difficulties. Table 3 shows that one factor accounted for the majority of the variance among the cognitive items. The first factor was defined by the relative difficulty of verbal expression. Patients with right hemiparesis following stroke found verbal expression to be relatively difficult (fig 4) whereas patients with brain dysfunction found this task to be relatively easy (fig 4). The second factor was defined by the difficulty of social interaction. Pa-
tients with right hemiparesis following stroke found this task to be relatively easy (fig 4) whereas patients with spinal dysfunction found this task to be relatively difficult (fig 5). Impairment groups that appeared most similar on the cognitive measure include patients with ( 1) left hemiparesis, bilateral strokes. brain dysfunction and congenital deformities: (2) patients with stroke resulting in right hemiparesis: and (3) all other impairments. Patients with right hemiparesis found verbal expression to be more difficult than patients with left hemiparesis and bilateral strokes. brain dysfunction, and congenital deformities. Patients with left hemiparesis, bilateral strokes. brain dysfunction.
---
Function
Fig 2-Line graphs are plots of item difficulties for 13 FIM motor items (in logits) for patients with amputations, arthritis, orthopedie impairments, spinal cord dysfunction, congenital deformities, and the average item difficulties across all impairment groups. Group numbers correspond to labeling used in tables 1,2, and 3. +, 5 amputation: 8, 4 spinal cord; -t, 6 arthritis: -S, 8 orthopedic; X, 12 congenital; t, average.
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Fig 3-Line graphs are plots of item difficulties for 13 FIM motor items (in logits) for patients with back pain, cardiac impairment, pulmonary impairment, burns, other impairments, and the average item difficulties across all 15 impairment groups. Group numbers correspond to labeling used in tables 1, 2, and 3. +, 7 pain; *, 10 pulmonary; 0,ll burns; t, 9 cardiac; X, 13 other impairment; t, average.
congenital deformities. and stroke resulting in right hemiparesis were distinguished from all other groups by the relatively less difficulty of social interaction.
undergone important changes. This project brings together these two advancing fields at an opportune moment. The FIM, a largely empirically developed instrument, has emerged, pushed by a growing consensus that there is a need for a uniform, valid. reproducible, precise, and feasible-to-use instrument to assess patient function.’ Rasch analysis has developed as a useful technique to evaluate instruments that are intended to measure scaled behavior,4,5,7including disability. 14.15 In responding to these needs and opportunities, this project examined the scalability of the FIM using Rasch analysis. FIM item difficulties vary somewhat across impairment
DISCUSSION The measurement characteristics of functional assessment instruments used in medical rehabilitation have come under scrutiny as the field has moved toward uniformity in assessment of severity of disability and quantification of rehabilitation outcomes. 3.4At the same time, measurement concepts and techniques applied to human behavior have
Fig d-Line graphs are plots of item difficulties for five FIM cognitive items (in logits) for patients with stroke resulting in left hemiparesis, right hemiparesis, and bilateral impairment, brain dysfunction, neurologic impairments, and the average item difficulties across all 15 impairment groups. Group numbers correspond to labeling used in tables 1, 2, and 3. _), IA stroke-left; t, 1B stroke right; W, 1C stroke bilateral; 8, 2 brain dysfunction; X, 3 neurologic; f , average.
~1 0.2 ‘3 ci
-0.8
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Verbal Expression
,
Auditoty Comprehension
I
Social Interaction
Function
I
Memory
I
Problem Solving
IMPAIRMENT
Fig !&Line graphs are plots of item difficulties for tive FIM cognitive items (in logits) for patients with spinal cord dysfunction, back pain, orthopedic impairments, cardiac impairment. other impairments, and the average item difficulties across all 15 impairment groups. Group numbers correspond to labeling used in tables 1, 2. and 3. -W. 4 spinal cord; t, 7 pain; *. 8 orthopedic: -ft, 9 cardiac: +C, 13 other impairment; -t, average.
Verbal
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Expression
Comprehension
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Memory
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Solving
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groups. Fo,r the most part, one motor scale can accommodate all impairment groups, except patients with back pain and burns. One cognitive scale is useful for all impairment groups except patients with strokes. brain dysfunction, and congenital impairments. These groups can be managed with a second cognitive scale. The motor scale appears to be generally applicable because back pain and burns are not major diagnoses for most inpatient medical rehabilitation programs. The two cognitive scales are manageable and possibly mergable. depending on how they perform in clinical use. Further study is needed to see if that is feasible.
U.6- --I__ “---~=-----3
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Comprehension
,
Social Interaction
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The construct validity of the FlM is supported by the pattern of results. Specific items were more difficult for some impairment groups in ways that make clinical sense. Patients with amputations found stair climbing and locomotion to be relatively difficult; patients with burns found feeding to be more challenging than did other impairment groups. The factor analysis of motor item difficulties across the impairment groups reveal distinct brain, limb. and spinal cord dysfunction. With the cognitive items, verbal expression distinguished patients with right and left hemiparesis following stroke. These distinctions parallel clinical
,
Memory
Problem
I
Solving
I
Fig 6-Line graphs are plots of item difficulties for five FIM cognitive items (in logits) for patients with amputations, arthritis, pulmonary impairment, burns, congenital impairments, and the average item difticulties across all 15 impairment groups. Group numbers correspond to labeling used in tables 1, 2, and 3. +, 5 amputation; t, 6. arthritis; +K, 10 pulmonary; 8.11 burns; *, 12 congenital: f, average.
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experience. They show that the FIM measures fundamental aspects of disability. Specific suggestions for revision of the FIM also emerge from these analyses. The number of transfer items could be reduced because they assess partially redundant aspects of function. Bowel and bladder items could be redefined as two separate items that distinguish levels of assistance required from frequency of incontinence. Three items that have two modes-locomotion (wheelchair vs walking). comprehension (auditory vs visual), and expression (vocal vs nonvocal)-could be rated as separate items. An easier stair climbing item could be developed that could quantify intermediate levels of ability, Finally, “not tested” ratings could be assigned a value other than “ 1” (total assist) so as to distinguish these different situations. A limitation of this study is that it focussed on inpatients undergoing medical rehabilitation at hospitals that subscribe to the Uniform Data System. Though the representativeness of the sample appears good, given the number of subscribers and their geographic distribution, it is possible that subscribing hospitals are not representative of all sites where comprehensive rehabilitation is delivered. The utility of these results to outpatients, skilled nursing facility, and home-based service patients and others needs to be demonstrated. In summary, we found that the FIM could be scaled as an interval measure for each of the 13 impairment groups. Motor and cognitive aspects of function were important to be distinguished and were treated separately. Item difficulties varied slightly across impairment groups, reflecting the unique impact of various kinds of impairments. The validity of the FIM is supported by this pattern of item difficulties and the factor analysis. The results make clear the fact that raw scores are not linear and should not be used in parametric statistical analyses. These results have immediate application in quality assurance and program evaluation efforts. Clinicians and researchers in rehabilitation medicine now have a linear mea-
Impairment
Group
Factor Loadings Impairment
Eigenvalues Percent of variance IA. Stroke-Left hemiparesis 19. Stroke-Right hemiparesis If. Stroke-Bilateral 3 Brain dysfunction 3:Neurologic 4. Spinal cord dysfunction 5. Amputation 6. Arthritis 7. Back pain 8. Orthopedic impairment 9. Cardiac impairment 10. Pulmonary impairment 1I. Burns 12. Congenital deformity 13. Other impairment
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2
3
7.77 95.18 0.12 0.6’ 0.58 0.53 0.66 0.68 1.04 0.89 0.11 0.93 0.74 0.72 0.41 0.53 0.72
0.21 2.54 0.06 0.02 0.04 0.03 -0.07 -0.25 -0.07 0.03 -0.00 0.00 0.10 0.24 0.12 -0.22 -0.03
0.08 0.92 0.02 0.06 0.05 0.04 0.03 -0.01 0.11 -0.09 -0.15 -0.10 0.04 0.07 -0.09 0.04 -0.00
Group
Eigenvalues Percent of variance I A. Stroke-Left hemipdresis 19. Stroke-Right hemiparesis IC. Stroke-Bilateral 2. Brain dysfunction 3. Neurologic 4. Spinal cord dysfunction
5. 6. 7. 8. 9. IO.
Amputation Arthritis Back pain Orthopedtc Cardiac Pulmonary I 1. Burns 12. Congenital 13. Other
1
Z
3
7.99 91.55 0.49 0.19 0.43 0.61 0.46
0.20 6.13 PO.07 PO.2 I m-o.13 PO.13 0.02
0.04
0.48 0.42 0.31 0.48 0.46 0.50 0.11 0.37 0.61 0.48
0.19 0.08 0.0 I 0.13 0.02 0.13 0.09 0.05 -0.17 0.03
I.25 0.01 PO.03 PO.03 PO.09 PO.03
-0.03 0.01
0.03 0.03 0.0 I -0.08 0.01 0.09 0.11 -0.01
sure whose scoring is not dependent on local data. Discharge expectancies can be established based on these scaling results, and programs can evaluate their outcomes in terms of attainment of discharge performance. Demonstration of patient function as consisting of two distinct aspects of behavior suggests that both domains are important in helping patients live independently and in estimating caregiver requirements. Acknowledgments:
Mamott
and Richard
The authors extend their appreciation Kayton for technical data analysis.
to Brian
References
5
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Table 3: Cognitive Item Difficulties: Factor Analysis
Table 2: Motor Item Difficulties: Factor Analysis Factor Loadings
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