Context Changes in reimbursement have reduced length of stay (LOS) for patients
receiving inpatient medical rehabilitation. The impact of decreased LOS on
functional status, living setting, and mortality is not known.
Objective To examine changes in LOS, functional status, living setting, and mortality
in patients completing inpatient rehabilitation.
Design Retrospective cohort study from 1994 through 2001 using information
submitted to the Uniform Data System for Medical Rehabilitation.
Setting and Participants Data were analyzed from 744 inpatient medical rehabilitation hospitals
and centers located in 48 US states. A total of 148 807 patient records
from 5 impairment groups (stroke, brain dysfunction, spinal cord dysfunction,
other neurologic conditions, and orthopedic conditions) were examined. Patients’
mean age was 67.8 (SD, 15.8) years; the sample was 59% female and 81% non-Hispanic
white.
Main Outcome Measures Discharge setting, follow-up living setting, change in functional status,
and mortality.
Results Median LOS decreased from 20 to 12 days (P<.001)
from 1994 to 2001. The proportional decrease in median LOS was greatest (42%)
for patients with orthopedic conditions. Mean days to follow-up remained constant
from 89 in 1994 to 90 in 2001. Functional status was clinically stable, while
efficiency (functional status change divided by LOS) increased significantly
(P<.001). Rates of discharge to home and living
at home at follow-up remained stable, ranging from 81% to 93%. However, mortality
at 80- to 180-day follow-up increased from less than 1% in 1994 to 4.7% in
2001.
Conclusions Length of stay for inpatient rehabilitation decreased substantially
from 1994 to 2001. Effectiveness as measured by change in functional status
did not change clinically, and living setting did not change. Efficiency for
functional outcomes improved but mortality at follow-up increased.
Length of stay (LOS) for inpatient medical rehabilitation has decreased
dramatically in recent years1-6 and
is expected to continue declining under the prospective payment system implemented
for inpatient medical rehabilitation in January 2002.1,5 The
impact that reduced LOS has had on rehabilitation outcomes including functional
status, living setting, and mortality is unknown.
We examined changes in LOS for persons receiving inpatient medical rehabilitation
from 1994 through 2001 using a large national database representative of rehabilitation
patients in the United States.7,8 In
addition to exploring trends in LOS for 5 major impairment groups (stroke,
brain dysfunction, other neurologic conditions, spinal cord dysfunction [traumatic
and nontraumatic], and orthopedic conditions), we also examined changes in
rehabilitation effectiveness, efficiency, discharge to home, living setting
at 3- to 6-month follow-up, and mortality. One goal was to establish baseline
data for rehabilitation outcomes prior to the introduction of inpatient rehabilitation
prospective payment by the Centers for Medicare & Medicaid Services (CMS)
in 2002.4-6 We
hypothesized that decreasing LOS would be associated with reduced functional
status and decreased community living at follow-up.
The data were collected by the Uniform Data System for Medical Rehabilitation
(UDSMR). The UDSMR is the largest national registry of standardized information
on medical rehabilitation inpatients in the United States and has been used
by rehabilitation facilities since 1987.7,8 The
UDSMR database includes sociodemographic variables, diagnoses (International Classification of Diseases, Ninth Revision[ICD-9] codes), facility characteristics, patient prehospital living
arrangements and marital status, predisability employment status, discharge
disposition, and cost factors including LOS, source of payment, and hospital
charges.
In addition to descriptive information for patients and facilities,
scores on a standardized measure of basic daily living skills—the Functional
Independence Measure (FIM Instrument)—are recorded at admission, discharge,
and follow-up. The FIM instrument measures functional status using 18 items
covering 6 domains: self-care or activities of daily living (6 items on dressing
upper and lower body, eating, grooming, toileting, and bathing), bladder and
bowel control (2 items), mobility (3 transfer items), locomotion (2 items
on walking/wheelchair use and stairs), communication (2 items on comprehension
and expression), and social cognition (3 items on social interaction, problem
solving, and memory). All 18 items are scored into 1 of 7 levels of function
ranging from complete dependence (level 1) to complete independence (level
7). Total scores range from 18 to 126, with higher scores indicating better
function. Reliability, assessed using intraclass correlation coefficients,
has consistently been found to be greater than 0.85.9-11
Facilities follow the UDSMR protocol in administering the FIM instrument
and subsequent submission of the data. The FIM instrument is administered
within 72 hours after inpatient rehabilitation admission and 72 hours or less
before discharge. Follow-up data obtained during the period of the study (1994-2001)
were collected by the National Follow-up Services between 80 and 180 days
after discharge using telephone interviews. Nurses trained in administering
and interpreting the FIM instrument collected follow-up information. If the
patient was not able to respond appropriately, the nurses used a protocol
for collecting information from proxies (family member or caregiver).12 In addition to the FIM items, information on living
setting, employment status, outpatient therapy, marital status, and rehospitalization
was collected at follow-up. The interview process has been described.12,13
Follow-up information is aggregated with the complete UDSMR patient
record. The interrater and test-retest reliability of the data collection
process, including proxy responses, has been examined by independent researchers
and consistently produced intraclass correlation coefficients between 0.86
and 0.99.13-15 The
sensitivity and responsiveness of the FIM instrument have also been investigated
with excellent results.16 A summary of the
national data collected by the UDSMR is published annually and provides benchmarks
for inpatient medical rehabilitation.17,18 Deaths
during the inpatient rehabilitation stay are not included but represent a
very small (0.2% or less) mortality rate.
In developing the prospective payment system for inpatient medical rehabilitation,4,5 CMS extensively reviewed the UDSMR
data and associated information collection protocols.19 The
review found that UDSMR hospitals included a large portion of the Medicare
rehabilitation cases from most states19 and
that patient demographics, hospital characteristics, and resources used by
Medicare beneficiaries were well represented by the UDSMR database.19 Information regarding the representativeness of the
UDSMR database is included in technical reports published by the CMS.4,19,20
This study was reviewed and approved by the University of Texas Medical
Branch Institutional Review Board. Because of the nature of the study, the
board waived the need for patient informed consent.
Admission, discharge, and follow-up data were reviewed for 226 137
patients receiving inpatient medical rehabilitation services from 1994 through
2001. The data were collected from 744 hospitals in 48 US states (no data
from Alaska or Hawaii). We refined the sample by including patients from the
5 CMS impairment groups in the UDSMR database with the greatest number of
patients: orthopedic conditions (30%), stroke (26%), brain dysfunction (7%),
spinal cord dysfunction (traumatic and nontraumatic) (5%), and other neurologic
conditions (5%). These 5 impairment groups include patients (n = 162 819)
from the rehabilitation impairment groups developed by the UDSMR and adopted
by the CMS to create the rehabilitation impairment categories for prospective
payment (Table 1).
We used clinical criteria developed in previous research on case-mix
groups to exclude patients whose rehabilitation was atypical.21,22 We
excluded patients with missing or out of range values including logarithm
LOS 3 standard deviations or more above the mean for the impairment group
(n = 4577), and cases with incorrect rehabilitation impairment categories
or ICD-9 codes (n = 641). In addition,
we excluded patients who were younger than 16 years (n = 1602),
were readmitted or transferred from another rehabilitation facility (n = 6011),
or were admitted for evaluation only (n = 1181). The remaining 148 807
patients comprised the sample and represented 91% of the usable patient records
from the original sample for the 5 impairment groups. Patients transferred
to acute care facilities (<0.1%) generally do not have discharge FIM scores
and so are not included in this analysis.
Not all facilities contributing data to the UDSMR collect follow-up
information using the National Follow-up Services. The percentage of cases
with follow-up data in the UDSMR database ranged from 34% to 42% for 1994
through 2001. Comparisons between the demographics and FIM instrument data
for patient records with follow-up data vs those without follow-up data revealed
no important differences. In the full database, 60.2% of the cases were female
(59.2% in the sample with follow-up), 83% were non-Hispanic white (81% in
the sample with follow-up), mean age was 66.3 (SD, 14.6) years (67.8 [SD,
15.8] years in the sample with follow-up), and median LOS was 20 days (interquartile
range [IQR], 13-27) (median [IQR], 20 [13-29] in the sample with follow-up).
Length of Stay. Length of stay was calculated
as the total number of inpatient rehabilitation days. When a patient was transferred
to an acute care hospital and returned to the initial rehabilitation service
within 30 days, we counted only those days the patient was in the rehabilitation
service.
Effectiveness. Information on effectiveness
was obtained by subtracting the patient’s admission score on the measure
of functional status from his/her discharge score.
Efficiency. Efficiency was defined as the change
in functional status from admission to discharge divided by the LOS. The shorter
the LOS for a given change in FIM rating, the higher the efficiency rating.
Living Setting. Information on living setting
was collected at both discharge from medical rehabilitation and at follow-up
(80 to 180 days after discharge). Living setting in the UDSMR database is
coded as home, board and care, intermediate care, skilled nursing facility,
hospital, rehabilitation facility, and other. These categories were collapsed
to home and not home for statistical analyses.
Mortality. Information on death after discharge
was recorded at follow-up through interviews by nurses from the National Follow-up
Services with a family member or caregiver.
These measures have been collected, analyzed, and reported annually
as national benchmarks for the rehabilitation community since 1990.16,17
We used descriptive statistics to examine differences in demographic
characteristics, living setting, effectiveness, and efficiency. Analysis of
covariance with repeated measures (time) was used to examine changes in LOS
and days to follow-up. Quasi-likelihood analyses were used to assess outcomes
from 1994 to 2001.23-26 The
models were longitudinal with time (1994 to 2001) and admission, discharge,
and follow-up as independent variables. Dependent variables were effectiveness,
efficiency, follow-up living setting, and mortality.
Covariates included age (recorded at admission), marital status (single,
married, widowed, separated/divorced), sex, race/ethnicity (coded by patient
report as non-Hispanic white or other), living situation (included alone,
with family/relatives, or other), payment source (coded as Medicare/Medicaid
or other), and comorbidities (other diseases based on ICD-9-CM and total number of comorbidities coded as 0, 1-3, or >3). Ethnicity/race
information was included as a covariate because previous research has reported
differences in functional status outcomes based on ethnicity/race. Time from
disease/injury onset to rehabilitation admission and time from discharge to
follow-up were included as time-varying covariates. In some analyses, LOS,
living setting at discharge, and admission (baseline) FIM instrument scores
were also included as covariates.27-29
Separate analyses were computed for each impairment group. When statistically
significant effects were found, we conducted post hoc analyses using orthogonal
comparisons for trend.23,28 We
used an overdispersed Poisson quasi-likelihood model.23 In
all models a log linear time trend was found to be adequate. P<.05 was considered significant and adjustments were made for multiple
comparisons by a modified Bonferroni correction.29 All
statistical tests were conducted using SAS version 8.0 (SAS Institute Inc,
Cary, NC) or SPSS version 12.0 (SPSS Inc, Chicago, Ill) software. Details
regarding the quasi-likelihood approach are provided by Zeger and Liang.30
The final sample included 148 807 records for patients from 744
facilities who received inpatient medical rehabilitation from 1994 through
2001. Descriptive and demographic information for all patients by impairment
group is shown in Table 2. Table 3 presents FIM instrument effectiveness
and efficiency scores, discharge and follow-up setting, and mortality by impairment
group. Table 4 contains admission, discharge,
and follow-up functional status information for each year of the study by
impairment group. Table 5 contains descriptive
longitudinal information on outcomes and covariates.
The total LOS collapsed across all impairment groups decreased from
a median of 20 days (IQR, 13-29) in 1994 to 12 days (IQR, 7-19) in 2001 (F = 67.8, P<.001). The proportional decrease in median LOS was
greatest for patients with orthopedic conditions (42%). Table 6 provides LOS, effectiveness, and efficiency information
over the 8 years. Separate quasi-likelihood models were computed for each
of the 5 impairment groups. Effectiveness declined slightly, but this change
was not believed to be clinically significant. The largest improvement in
efficiency was found for orthopedic conditions (F = 91.4, P<.001), for which the efficiency index improved from
1.6 (SD, 1.0) in 1994 to 2.9 (SD, 1.8) in 2001. The smallest change in efficiency
was for stroke (F = 66.5, P<.001), for
which the efficiency index improved from 1.2 (SD, 0.9) in 1994 to 1.7 (SD,
1.4) in 2001.
There has not been a substantial change in the percentage of patients
discharged to home or living at home following inpatient medical rehabilitation
from 1994 to 2001. The range of percentages for persons discharged home after
rehabilitation was 79% to 82% for stroke; 81% to 88% for brain injury; 85%
to 90% for neurologic conditions; 85% to 92% for spinal cord injury; and 88%
to 92% for orthopedic conditions. The percentages living at home at follow-up
also remained stable (81%-85% for stroke; 84%-88% for brain injury; 84%-88%
for neurologic conditions; 88%-93% for spinal cord injury; and 91%-94% for
orthopedic conditions). Patients with orthopedic conditions were most likely
to be discharged home and/or living at home at follow-up (>90%). Persons with
stroke were the least likely to be discharged home (mean, 81%) or living at
home at follow-up (mean, 83%).
Changes in mortality over time are presented in the Figure. The increase in mortality was small but consistent across
the 5 impairment groups. Overall mortality from discharge to follow-up (80
to 180 days) increased from a mean of less than 1% in 1994 to 4.7% in 2001.
Days to follow-up remained stable (Table 5).
We initially assumed that the increase in mortality might be related to sicker
patients with more comorbidities being referred to rehabilitation in 2001
vs 1994. However, examination of FIM admission scores revealed little change
across impairment groups from 1994 (mean [SD], 72.5 [21.1]) to 2001 (mean
[SD], 72.4 [18.7]). We also evaluated age and comorbidities in the quasi-likelihood
analyses, hypothesizing that if older patients were admitted more frequently
in recent years, mortality rates would increase. However, the average admission
age was 69.9 (SD, 15.3) years in 1994 and 67.8 (SD, 15.6) years in 2001. There
was no clinically important increase in admission age or number of comorbidities
over the study period for any of the 5 impairment groups.
Comorbidities and age were statistically significant covariates in the
quasi-likelihood models. Length of stay and admission FIM scores were statistically
significant covariates in models in which they were included (living setting
at follow-up and mortality). The trend in mortality was statistically significant
for all impairment groups in both adjusted and unadjusted models but least
dramatic for orthopedic conditions (Figure).
We found that the LOS for inpatient medical rehabilitation decreased
significantly from 1994 to 2001 for the 5 impairment groups. No clinically
significant change in daily living skills such as dressing and bathing was
seen, despite a significant reduction in LOS. Functional status remained relatively
stable despite an increase in rehabilitation efficiency. Higher FIM scores
are associated with fewer minutes per day of help required from another person
to complete basic daily living tasks.16,31-33 Granger
and colleagues16 found that in persons with
stroke, each 1-point decrease in FIM score was associated with approximately
2.2 more minutes of assistance by another person to complete activities of
daily living. Carter et al6 recently reported
that an average increase of 1 FIM point from admission to discharge was associated
with a 3% reduction in the expected cost of inpatient rehabilitation care.
The cost implications varied slightly by functional status item.6
The increase in rehabilitation efficiency may be related to changes
in the intensity of rehabilitation services. The number of therapy hours provided
might not have changed from 1994 to 2001, but the total hours became compressed
by providing evening and weekend services.34 Another
potential explanation is the pattern of patient recovery. In the early 1990s,
patients could have reached a maximum level of functional status early in
their rehabilitation program but were allowed to stay in the facility to be
sure they would maintain this functional level prior to discharge. This pattern
may have changed in the late 1990s when pressures for earlier discharge increased.34 Additional research is needed to determine how the
number of rehabilitation therapy hours changed as LOS decreased.
The lack of improvement in effectiveness (absolute change in FIM scores)
may be due to a ceiling effect or plateau at which patients have attained
their maximum functional status given their residual impairment. This speculation
is supported by research from other countries where rehabilitation LOS is
much longer than in the United States but discharge FIM scores are similar.35 Another possible explanation for increased efficiency
is that patients are beginning rehabilitation earlier. The time from disease/injury
onset to rehabilitation admission was shorter in 2001 (median [IQR], 5 [3-10]
days) than in 1994 (median [IQR], 8 [6-16] days) due to the decrease in acute
care hospital LOS. There is evidence that earlier admission to rehabilitation
produces improved functional outcomes for some impairment groups.36
Rehabilitation professionals have also made advances in promoting clinical
research and adopting the principles of evidence-based practice.37 The
entry-level qualification for many rehabilitation professions is now at the
master’s or doctoral level. Empirical evidence regarding the impact
of these changes on patient outcomes is lacking, but the increase in professional
standards, enhanced research, and use of evidence-based models of care, along
with advances in surgical and acute care, may partially account for the improvement
in rehabilitation efficiency. These are areas in need of additional research.
A plausible explanation for increased mortality is more difficult to
pinpoint. The increase could be due to patients with less severe disabilities
being discharged to home health or subacute rehabilitation units in nursing
homes, thus leaving a larger proportion of patients with stroke and other
severe disorders receiving inpatient medical rehabilitation.
For example, clinical pathways are now well developed for some diagnostic
groups, including patients with lower extremity joint replacement or hip fracture.
The current trend based on these pathways is to discharge persons with some
conditions (eg, lower extremity joint replacements) to subacute rehabilitation
units in nursing homes or to home health care without a period of traditional
inpatient rehabilitation.38 However, the proportion
of patients in different impairment groups remained constant over the study
period.17,18 In addition, the
FIM admission scores and number of comorbidities remained stable, suggesting
that changes in discharge patterns are not directly related to increased mortality
in this sample.
In previous research using the UDSMR database, we reported increased
hospital readmission rates associated with decreasing LOS for persons receiving
inpatient medical rehabilitation.39 The percentage
of persons rehospitalized across 8 impairment groups from discharge to follow-up
(80-180 days) increased from 14.8% in 1994 to 18% in 1998. This change in
rehospitalization is consistent with our finding of increased mortality. We
also examined LOS for persons who died (median [IQR], 15 [9-22] days) compared
with persons who did not die (median [IQR], 14 [9-23] days) for the impairment
groups included in this study. The difference in LOS was small and not important.
The decrease in LOS for acute care hospitals means that patients entered
rehabilitation sooner in 2001 than in 1994 (Table
5), and this might contribute to increased mortality. That is, patients
who previously would have died in acute care were transferred or discharged
to inpatient rehabilitation. We do not believe this is an adequate explanation
because patients must be medically stable before they are sent to an inpatient
rehabilitation service. The potential interaction, however, between decreased
LOS in acute hospitals and rehabilitation facilities is complex and should
be explored.
As LOS in acute care hospitals continues to decline, the use of postacute
services is increasing.40-42 From
1994 to 2000, the number of Medicare patients transferred from acute care
hospitals to inpatient medical rehabilitation facilities and skilled nursing
settings increased by 22% and 19%, respectively.42 The
majority of these patients had orthopedic impairments or stroke. The percentage
of patients in the UDSMR database with orthopedic impairments ranged from
33% to 36% from 1994 to 2000. The percentage of patients with stroke ranged
from 26% to 30% for this period.17,18 It
is unknown what the most appropriate postacute care setting is for patients
with stroke and other impairments. A recent review notes that research on
whether postacute care services are equivalent has been inconclusive.42
The limitations of this investigation include those associated with
analyzing a large database.43 The sociodemographic
information in the UDSMR database is obtained from existing medical records
and self-reports. While the consistency of the information collection process
has been extensively examined,6,19-22 the
possibility of coding and reporting errors exists. Another limitation is the
lack of information regarding acute care hospitalization. The UDSMR database
includes detailed patient information that begins when a person enters inpatient
rehabilitation. A priority for our future research is linking the UDSMR database
with Medicare files containing information on acute care. Access to this information
will help better define the sample, allow comparisons with cases not in the
UDSMR database, and provide medical history and background that may help explain
the increase in mortality.
While the UDSMR database has been found to be representative of Medicare
patients receiving inpatient rehabilitation across the United States,19,20 it is not a complete record of all
rehabilitation facilities nationally and the representativeness for non-Medicare
patients is unknown.
Determining the causes of the increase in rehabilitation efficiency
and mortality requires further study. Our goal was to document the recent
change in LOS and examine its association with functional status, living setting,
and mortality. This goal is important in view of the introduction of a prospective
payment system for inpatient medical rehabilitation by CMS in January 2002.44 Our findings provide a baseline with which to compare
future LOS, effectiveness, efficiency, mortality, and other outcomes important
to health care professionals, researchers, and consumers to help evaluate
how change in LOS influences patient care and outcomes.
Corresponding Author: Kenneth J. Ottenbacher,
PhD, University of Texas Medical Branch, 301 University Blvd, Galveston, TX
77555-1137 (kottenba@utmb.edu).
Author Contributions: Dr Ottenbacher had full
access to all of the data in the study and takes responsibility for the integrity
of the data and the accuracy of the data analysis.
Study concept and design: Ottenbacher, Granger.
Acquisition of data: Illig, Smith, Linn.
Analysis and interpretation of data: Ottenbacher,
Ostir.
Drafting of the manuscript: Ottenbacher, Ostir,
Linn.
Critical revision of the manuscript for important
intellectual content: Illig, Smith, Granger.
Statistical analysis: Ottenbacher, Ostir.
Obtained funding: Ottenbacher.
Administrative, technical, or material support:
Illig, Smith, Granger.
Study supervision: Ottenbacher, Linn.
Funding/Support: This research was supported
by National Institutes of Health grants R01 HD34622 and KO2 AG019736 (Dr Ottenbacher).
Role of the Sponsor: The funding agency did
not have any direct influence on the design or conduct of the study; the collection,
analyses, or interpretation of the data; or the preparation, review, or approval
of the manuscript.
1.Chan L, Beaver S, MacLehose RF.
et al. Disability and health care costs in the Medicare population.
Arch Phys Med Rehabil. 2002;83:1196-120212235597
Google ScholarCrossref 2.Anderson GF, Poullier JP. Health spending, access, and outcomes: trends in industrialized countries.
Health Aff (Millwood). 1999;18:178-19210388215
Google ScholarCrossref 3.Heffler S, Smith S, Won G.
et al. Health spending projections for 2001-2011: the latest outlook.
Health Aff (Millwood). 2002;21:207-21811900160
Google ScholarCrossref 4.Buchanan J, Andres P, Haley S.
et al. Final Report of the Assessment of Instruments for
PPS, MR-1501-CMS. Santa Monica, Calif: RAND; 2002
5.Clauser SB, Bierman AS. Significance of functional status data for payment and quality.
Health Care Financ Rev. 2003;24:1-1212894631
Google Scholar 6.Carter GM, Buntin MB, Hayden O.
et al. Analyses for the Initial Implementation of the Inpatient
Rehabilitation Facilities Prospective Payment System. Santa Monica, Calif: RAND; 2002
7. Guide for the Uniform Database for Medical Rehabilitation. Version 5.1. Buffalo: State University of New York at Buffalo; 1997
8.Hamilton BB, Granger CV, Sherwin FS, Zielezny M, Tashman JS. A uniform national data system for medical rehabilitation. In: Fuhrer M, ed. Rehabilitation Outcomes: Analysis
and Measurement. Baltimore, Md: Paul H Brookes; 1987:137-150
9.Hamilton BB, Laughlin JA, Fiedler RC, Granger CV. Interrater reliability of the 7-level Functional Independence Measure
(FIM).
Scand J Rehabil Med. 1994;26:115-1197801060
Google Scholar 10.Ottenbacher KJ, Hsu Y, Granger CV, Fiedler RC. The reliability of the Functional Independence Measure: a quantitative
review.
Arch Phys Med Rehabil. 1996;77:1226-12328976303
Google ScholarCrossref 11.Stineman MG, Shea JA, Jette A.
et al. The Functional Independence Measure: tests of scaling assumptions,
structure, and reliability across 20 diverse impairment categories.
Arch Phys Med Rehabil. 1996;77:1101-11088931518
Google ScholarCrossref 12.Smith PM, Illig S, Fiedler RC, Hamilton BB, Ottenbacher KJ. Intermodal agreement of follow-up telephone functional assessment using
the Functional Independence Measure (FIM) in patients with stroke.
Arch Phys Med Rehabil. 1996;77:431-4358629917
Google ScholarCrossref 13.Ottenbacher KJ, Mann WC, Granger CV, Tomita M, Hurren D, Charvat B. Interrater agreement and stability of functional assessment in the
community based elderly.
Arch Phys Med Rehabil. 1994;75:1297-13017993167
Google Scholar 14.Heinemann AW, Linacre JM, Wright BD, Hamilton BB, Granger C. Prediction of rehabilitation outcomes with disability measures.
Arch Phys Med Rehabil. 1994;75:133-1438311668
Google ScholarCrossref 15.Segal ME, Gillard M, Schall R. Telephone and in-person proxy agreement between stroke patients and
caregivers for the Functional Independence Measure.
Am J Phys Med Rehabil. 1996;75:208-2128663929
Google ScholarCrossref 16.Granger CV, Cotter AC, Hamilton BB, Fiedler RC. Functional assessment scales: a study of persons after stroke.
Arch Phys Med Rehabil. 1993;74:133-1388431095
Google Scholar 17.Fiedler RC, Granger CV, Post LA. Uniform Data System for Medical Rehabilitation: report of first admissions
for 1998.
Am J Phys Med Rehabil. 2000;79:87-9210678608
Google ScholarCrossref 18.Fiedler RC, Granger CV, Russell CF. The Uniform Data System for Medical Rehabilitation: report of first
admissions for 1997.
Am J Phys Med Rehabil. 1998;77:444-4509798838
Google ScholarCrossref 19.Carter GM, Relles DA, Buchanan JL.
et al. Classification System for Inpatient Rehabilitation
Patients: A Review and Proposed Revisions to the Functional Independence Measure-Function
Related Groups. Washington, DC: US Dept of Commerce, National Technical Information
Services; September 1997
20.Carter GM, Buchanan JL, Donyo T, Inkela M, Spritzer KL. A Prospective Payment System for Inpatient Rehabilitation. Washington, DC: US Dept of Commerce, National Technical Information
Services; September 1997
21.Stineman MG, Escarce JJ, Goin JE, Hamilton BB, Granger CV, Williams SV. A case mix classification system for medical rehabilitation.
Med Care. 1994;32:366-3798139301
Google ScholarCrossref 22.Stineman MG, Hamilton BB, Granger CV, Goin JE, Escarce JJ, Williams SV. Four methods for characterizing disability in the formation of function
related groups.
Arch Phys Med Rehabil. 1994;75:1277-12837993164
Google Scholar 23.Heyde CC. Quasi-likelihood Analysis and Its Applications. New York, NY: Springer-Verlag; 1997:chap 10, 11
24.Raudenbush SW, Bryk AS. Hierarchical Linear Models: Applications and Data
Analysis Methods. 2nd ed. Thousand Oaks, Calif: Sage Publications; 2002
25.Lu WS, Tsutakawa RK. Analysis of mortality rates via marginal extended quasi-likelihood.
Stat Med. 1996;15:1397-14078841650
Google ScholarCrossref 26.Schafer JL. Analysis of Incomplete Multivariate Data. New York, NY: Chapman & Hall; 1997
27.Wedderburn RWM. Quasi-likelihood functions, generalized linear models, and the Gauss-Newton
method.
Biometrika. 1974;61:439-447
Google Scholar 28.Keppel G. Design and Analysis: A Researcher’s Handbook. Englewood Cliffs, NJ: Prentice-Hall; 1973:105-132
29.Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach
to multiple testing.
J R Stat Soc Ser B Methodol. 1995;57:289-300
Google Scholar 30.Zeger SL, Liang KY. Longitudinal data analysis for discrete and continuous outcomes.
Biometrics. 1986;42:121-1303719049
Google ScholarCrossref 31.Hamilton BB, Deutsch A, Russell C, Fiedler RC, Granger CV. Relation of disability costs to function: spinal cord injury.
Arch Phys Med Rehabil. 1999;80:385-39110206599
Google ScholarCrossref 32.Granger CV, Cotter AC, Hamilton BB, Fiedler RC, Hens MM. Functional assessment scales: a study of persons with multiple sclerosis.
Arch Phys Med Rehabil. 1990;71:870-8752222154
Google Scholar 33.Granger CV, Divan N, Fiedler RC. Functional assessment scales: a study of persons after traumatic brain
injury.
Am J Phys Med Rehabil. 1995;74:107-1137710723
Google Scholar 34.Carter GM, Relles DA, Ridgeway GK, Rimes CM. Measuring function for Medicare inpatient rehabilitation payment.
Health Care Financ Rev. 2003;24:25-4412894633
Google Scholar 35.Tesio L, Granger CV, Perucca L, Franchignoni F, Battaglia M, Russell C. The FIM instrument in the United States and Italy: a comparative study.
Am J Phys Med Rehabil. 2002;81:168-17611989512
Google ScholarCrossref 36.Musicco M, Emberti L, Nappi G, Caltagirone C.Italian Multicenter Study on Outcomes of Rehabilitation of Neurological
Patients. Early and long-term outcome of rehabilitation in stroke patients: the
role of patient characteristics, time of initiation, and duration of interventions.
Arch Phys Med Rehabil. 2003;84:551-55812690594
Google ScholarCrossref 37.Law M, . Evidence-Based Rehabilitation: A Guide to Practice. Thorofare, NJ: Slack Inc; 2002
38.Johnson MF, Kramer AM, Lin MK, Kowalsky JC, Steiner JF. Outcomes of older persons receiving rehabilitation for medical and
surgical conditions compared with hip fracture and stroke.
J Am Geriatr Soc. 2000;48:1389-139711083313
Google Scholar 39.Ottenbacher KJ, Smith PM, Illig SB, Fiedler RC, Granger CV. Length of stay and hospital readmission for persons with disabilities.
Am J Public Health. 2000;90:1920-192311111267
Google ScholarCrossref 40.Kane R. A Study of Post Acute Care: Final Report. Minneapolis: Institute for Health Services Research, University of
Minnesota School of Public Health; 1994
41.Gage B. Impact of the BBA on post-acute utilization.
Health Care Financ Rev. 1999;20:103-12611482117
Google Scholar 42.Cotterill PG, Gage BJ. Overview: Medicare post-acute care since the Balanced Budget Act.
Health Care Financ Rev. 2002;24:1-1612690691
Google Scholar 44.Centers for Medicare and Medicaid Services. Final Rule, Inpatient Rehabilitation Facility Prospective Payment System
(IRF-PAI).
42 CFR §412 (CMS-1474-F), RIN 0938-AL95. Washington, DC: Dept
of Health and Human Services, Centers for Medicare and Medicaid Services;
2000. Available at: http://www.cms.hhs.gov/providers/irfpps/pubs.asp. Accessed January 20, 2004