Literature DB >> 35756989

Acute Inpatient Rehabilitation Improves Function Independent of Comorbidities in Medically Complex Patients.

Shangming Zhang1, Dan Lin2, Megan E Wright3, Nicole Swallow4.   

Abstract

Objectives: (1) To evaluate the benefits of acute inpatient rehabilitation for a medically complex patient population and (2) to assess the effect of comorbid conditions on rehabilitation outcomes. Design: Retrospective cohort study. Setting: Freestanding inpatient rehabilitation facility. Participants: A total of 270 medically complex adult patients including those with cardiac, pulmonary, and orthopedic conditions, with mean age of 73.6 years; 52.6% were female and 47.4% were male (N=270). Interventions: Not applicable. Main Outcome Measures: Functional Independence Measure (FIM) gain, FIM efficiency, rehabilitation length of stay (RLOS), home discharge rate, and readmission to acute care (RTAC).
Results: Among 270 medically complex patients, mean total FIM gain, mean RLOS, and mean FIM efficiency with SD were 26.0±13.6 points, 12.6±5.9 days, and 2.3±1.6, respectively. A total of 71.9% of patients were discharged to home, 12.2% for RTAC, and 15.9% to a skilled nursing facility (SNF). Hypertension (HTN) was the only comorbidity significantly associated with FIM gain (53.7% [total FIM gain ≥27] vs 67.2% [total FIM gain <27]; P=.024) and FIM efficiency (53.3% [FIM efficiency ≥2.12] vs 67.4% [FIM efficiency <2.12]; P=.025), independent of age, body mass index, sex, race, ethnicity, insurance type, and Charlson Comorbidity Index. The 5 most common reasons for RTAC were cardiac, pulmonary, acute blood loss anemia, infection, and neurologic conditions. Conclusions: Among 270 medically complex patients, 71.9% were discharged to home, 15.9% to an SNF, and 12.2% for RTAC with a mean RLOS 12.6 days, mean total FIM gain of 26 points, and mean FIM efficiency of 2.3, which were all better than those of all admissions at our facility in 2018. Furthermore, RLOS, total FIM gain and FIM efficiency in this study were all better than their corresponding eRehabData weighted national benchmarks (RLOS, 15.82 days; FIM gain, 25.57; FIM efficiency, 2.13) for a total of 202,520 discharges in 2018. These findings support acute inpatient rehabilitation for this patient population. With the exception of HTN, no medical comorbidities or demographic variables were associated with rehabilitation outcomes.
© 2022 The Authors.

Entities:  

Keywords:  Centers for Medicare and Medicaid Services; Comorbidity; Rehabilitation

Year:  2022        PMID: 35756989      PMCID: PMC9214302          DOI: 10.1016/j.arrct.2022.100178

Source DB:  PubMed          Journal:  Arch Rehabil Res Clin Transl        ISSN: 2590-1095


In the United States, intensive inpatient rehabilitation is performed within inpatient rehabilitation facilities (IRFs). The Centers for Medicare and Medicaid Services (CMS) is the largest payer source for patients admitted to IRF and provides reimbursement according to the Inpatient Rehabilitation Facility Prospective Payment System. CMS requires IRFs to comply with the “60 Percent Rule,” which states that at least 60% of patients admitted to IRFs must have 1 of 13 specified diagnoses including stroke, brain injury, spinal cord injury, neurologic disorders, and so on. The benefits of acute inpatient rehabilitation have been studied in patients with CMS “60% compliant,” such as stroke, traumatic brain injury (TBI), spinal cord injury (SCI), Guillain-Barré syndrome, multiple sclerosis, Parkinson disease, lower limb amputation, burn injuries, and unilateral hip fractures.2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 Previous studies have also shown that patients with other “noncompliant” diagnoses such as cancer,, heart failure,17, 18, 19 and chronic graft-vs-host disease also benefited from acute inpatient rehabilitation. Readmission to acute care (RTAC) in acute rehabilitation settings were studied in medically complex patients consisting of Impairment Group Codes (IGCs) 17.1-17.9, as well as mixed CMS compliant and noncompliant IGCs. Inpatient rehabilitation outcomes are influenced by the type and severity of impairments, age, sex, social support, comorbid medical conditions, and functional status on admission.,, Comorbidities play an important role in inpatient rehabilitation outcomes in patients with SCI, stroke, and TBI.,25, 26, 27, 28 Comorbidities have been used to predict functional outcomes in patients with stroke in multiple studies., Preexisting medical comorbidities were associated with lower levels of function on admission and discharge for patients with TBI in IRFs, but there was no association between comorbidities and functional status in patients post orthopedic surgery. A prior study of patients admitted to acute inpatient rehabilitation after hip and knee arthroplasty found that indications for surgery, number of comorbidities, marital status, and race were associated with rehabilitation length of stay (RLOS). However, acute inpatient rehabilitation and the effect of variables such as comorbidities on inpatient rehabilitation outcomes have not been investigated in medically complex patients excluding the CMS “60% compliant” diagnoses. Such an assessment would help inform rehabilitation preadmission assessments and identify opportunities to medically optimize patients and improve functional outcomes. The aims of our investigation were (1) to evaluate the benefits of acute inpatient rehabilitation for a medically complex patient population that does not carry one of the CMS “60% compliant” diagnoses and (2) to assess the effect of comorbid conditions and other variables on rehabilitation outcomes. We hypothesized that (1) medically complex patients who are admitted to an IRF will functionally benefit from acute inpatient rehabilitation and (2) medical comorbidities and/or demographic variables will account for differences in functional outcomes among this patient population.

Methods

Study design and setting

This study, approved by the institutional review board, is a retrospective cohort of medically complex patients admitted to a freestanding IRF with academic affiliation. Informed consent was not applicable because of the nature of the study.

Inclusion criteria

IGCs and rehabilitation impairment categories (RICs) were assigned to each patient and reflected the primary reason for admission to the IRF. This study included 270 patients 18 years or older who were admitted to an IRF between December 2016 and July 2018 with a variety of IGCs under 4 RICs: RIC-9 (other orthopedic), RIC-14 (cardiac), RIC-15 (pulmonary), and RIC-20 (miscellaneous). RIC-9, RIC-14, and RIC-15 included IGC08.9, IGC9, and IGC10.1 and 10.9, respectively. RIC-20 covers numerous IGCs such as IGC16 (debility), IGC17.1 (infection), IGC17.2 (neoplasms), IGC17.3 (nutrition with or without intubation), IGC17.4 (circulation disorder), IGC17.5 (respiratory disorders), IGC17.6 (terminal care), IGC17.7 (skin disorders), IGC17.8 (medical/surgical complications), and IGC17.9 (other medically complex conditions). The aforementioned IGCs under RIC-9, 14, 15, and 20 are noncompliant with the CMS's “60 Percent Rule” and are defined as “medically complex” in this study.

Exclusion criteria

This study excluded patients under RIC-1-8, 10-13, 17-19, or 21 who are CMS's “60 Percent Rule” complaint. However, 55 patients with intensive care unit–acquired weakness equivalent to critical illness myopathy who are considered CMS compliant under RIC-6 were included in this study because they are often coded as having debility (IGC16) under RIC-20.

Data collection

Data were obtained from eRehabData, which is a database composed of RIC, IGC, International Classification of Diseases, Tenth Revision, demographic, medical, and functional information extracted from the Inpatient Rehabilitation Facility Patient Assessment Instrument. Sociodemographic data (age, sex, race, ethnicity, insurance type) and clinical characteristics (body mass index [BMI], major comorbidities) were extracted along with functional data (admission Functional Independence Measure [FIM] and discharge FIM). RLOS (total number of days spent at IRF not including the day of discharge) and discharge disposition (home/assisted living facility/transitional care, skilled nursing facility [SNF], acute care hospital) were also assessed. The Charlson Comorbidity Index (CCI) was used to assess comorbidities. The CCI is a validated scoring tool frequently used for prognostication and comorbidity adjustment that considers 19 conditions, each assigned an integer weight from 1-6, with a weight of 6 representing the most severe morbidity., Additional comorbidities were also tracked beyond those included in the CCI, such as anemia, atrial fibrillation, respiratory failure, bacteremia, hypertension, orthostatic hypotension, and obstructive sleep apnea. The FIM instrument was in use at the time of the study to assess functional status. The FIM instrument is a valid and reliable tool that indicates how much assistance an individual requires to complete a task. It is scored for 18 items across 13 motor and 5 cognitive domains, and each item is scored on a 7-point ordinal scale from 1-7; thus, total FIM scores range from 18 to 126, with higher values indicating greater functional independence. This study examined FIM admission score, FIM gain (FIM discharge score minus FIM admission score), and FIM efficiency (FIM gain divided by RLOS).

Statistical analysis

A dichotomy using the median score of FIM total gain or median score of FIM efficiency was used to categorize 270 patients. Patients were divided into 2 groups: (1) score <27 (n=134) and ≥27 (n = 136) for FIM total gain or (2) score <2.12 (n = 135) and score ≥2.12 (n = 135) in FIM efficiency. Fisher exact test for categorical variables and t test for continuous variables were used to determine the association between patient characteristics and FIM gain, patient characteristics, and FIM efficiency. Fisher exact test for categorical variables and analysis of variance for continuous variables were used to assess associations between discharge destinations and patient characteristics. Multinomial logistic regressions of odds ratios (ORs) and 95% CIs were conducted to further assess the relationship between discharge destinations and FIM total gain or FIM efficiency with the adjustment of age (continuous), BMI (continuous), sex (male, female), insurance type (Medicare, commercial insurance), RLOS (continuous), and hypertension (HTN) (yes, no). HTN was included in the model because it was the only acute managed comorbidity associated with FIM total gain (P=.02) and FIM efficiency (P=.03) in our population. All analyses were conducted using SAS version 9.4.a

Results

A total of 270 medically complex patients met the inclusion and exclusion criteria. Table 1 summarizes the demographic, medical, and functional characteristics of all the patients. The mean age was 73.6 years, and 52.6% were female. The majority of participants were White (94.4%) and non-Hispanic (98.9%). Nearly 80% of participants were Medicare beneficiaries, and the 5 most common medical comorbidities were HTN (60.4%), atrial fibrillation (28.9%), congestive heart failure (27.4%), diabetes without chronic complications (24.8%), and anemia (15.6%). The mean total FIM scores improved significantly from 61.4±12.0 on admission to 87.3±16.5 on discharge (P<.001). The mean FIM motor scores improved from 36.4±9.2 on admission to 58.6±13.2 on discharge (P<.001), and the mean FIM cognitive scores improved from 25.0±5.6 on admission to 28.7±5.1 on discharge (P<.001). The mean total FIM gain with SD was 26.0±13.6 points (interquartile range [IQR], 19.0; range, −10.0 to 78.0), mean FIM efficiency was 2.3±1.6 (IQR, 1.9; range, −3.3 to 11.4), and mean RLOS was 12.6±5.9 days (IQR, 16.0 days; range, 1.0-43.0 days). Of all 270 patients, 71.9% were discharged to home, 15.9% to an SNF, and 12.2% to an RTAC.
Table 1

Characteristics of 270 medically complex patients

CharacteristicTotal
n=270
Age (y), mean ± SD73.6±12.5
BMI, mean ± SD29.6±10.0
Sex, n (%)
 Female142 (52.6)
 Male128 (47.4)
Race, n (%)
 White255 (94.4)
 Non-White15 (5.6)
Ethnicity, n (%)
 Hispanic3 (1.1)
 Non-Hispanic267 (98.9)
Insurance type, n (%)
 Commercial insurance55 (20.4)
 Medicare215 (79.6)
CCI score category, n (%)
 Low (0-2)38 (14.1)
 Moderate (3-4)119 (44.1)
 High (>4)113 (41.8)
FIM score at admission, mean ± SD
 Motor36.4±9.2
 Cognitive25.0±5.6
 Total subscales61.4±12.0
FIM score at discharge, mean ± SD
 Motor58.6±13.2
 Cognitive28.7±5.1
 Total subscales87.3±16.5
FIM gain, mean ± SD
 Motor22.2±11.2
 Cognitive3.7±4.5
 Total subscales26.0±13.6
FIM efficiency, mean ± SD
 Motor2.0±1.3
 Cognitive0.3±0.5
 Total subscales2.3±1.6
RLOS (d), mean ± SD12.6±5.9
Discharge destination, n (%)
 Home194 (71.9)
 Acute care hospital33 (12.2)
 Skilled nursing facilities43 (15.9)
Acutely managed comorbidities, n (%)
 CHF74 (27.4)
 Peripheral vascular disease11 (4.1)
 Diabetes without chronic complications67 (24.8)
 Renal disease, mild to moderate38 (14.1)
 Liver disease, mild8 (3.0)
 Chronic pulmonary disease9 (3.3)
 Myocardial infarction10 (3.7)
 Diabetes with chronic complications30 (11.1)
 Renal disease, severe31 (11.5)
 Liver disease, moderate to severe4 (1.5)
 Metastatic solid tumor2 (0.7)
 AIDS12 (4.4)
 Anemia*42 (15.6)
 Atrial fibrillation*78 (28.9)
 Respiratory failure*4 (1.5)
 Acute pneumonia*26 (9.6)
 Bacteremia*2 (0.7)
 HTN*163 (60.4)
 Orthostatic hypotension*10 (3.7)
 OSA*27 (10.0)

NOTE. BMI calculated as weight in kilograms divided by height in meters squared.

Abbreviations: CHF, congestive heart failure; HTN, essential (primary) hypertension; OSA, obstructive sleep apnea.

Not included in CCI.

Characteristics of 270 medically complex patients NOTE. BMI calculated as weight in kilograms divided by height in meters squared. Abbreviations: CHF, congestive heart failure; HTN, essential (primary) hypertension; OSA, obstructive sleep apnea. Not included in CCI. Regarding total FIM gain, table 2 details that patients with total FIM gain ≥27 were more likely to be discharged to home than those with total FIM gain <27 (86.8% vs 56.7%; P<.001), less likely to be discharged to an SNF (8.8% vs 23.1%; P<.001), and less likely to be emergently transferred to an acute care hospital (4.4% vs 20.2%; P<.001). HTN was the only comorbidity significantly negatively associated with FIM gain (53.7% [total FIM gain ≥27] vs 67.2% [total FIM gain <27]; P=.024). There were no significant differences in age, BMI, sex, race, ethnicity, insurance type, CCI, or RLOS between patients with total FIM gain <27 and those with total FIM gain ≥27.
Table 2

Associations between total FIM gain and characteristics in 270 medically complex patients

CharacteristicTotal FIM Gain <27Total FIM Gain ≥27P Value
n=134n=136
Age (y), mean ± SD74.3±13.272.8±11.8.31
BMI, mean ± SD29.6±12.129.7±7.5.91
Sex, n (%).71
 Female72 (53.7)70 (51.5)
 Male62 (46.3)66 (48.5)
Race, n (%).77
 White126 (94.0)129 (94.9)
 Non-White8 (6.0)7 (5.2)
Ethnicity, n (%).62
 Hispanic2 (1.5)1 (0.7)
 Non-Hispanic132 (98.5)135 (99.3)
Insurance type, n (%).49
 Commercial insurance25 (18.7)30 (22.1)
 Medicare109 (81.3)106 (77.9)
CCI score category, n (%).6
 Low (0-2)16 (11.9)22 (16.2)
 Moderate (3-4)60 (44.8)59 (43.4)
 High (>4)58 (43.3)55 (40.4)
RLOS (d), mean ± SD12.1±6.213.1±5.6.14
Discharge setting, n (%)<.001*
 Home76 (56.7)118 (86.8)
 Acute care hospital27 (20.2)6 (4.4)
 Skilled nursing facilities31 (23.1)12 (8.8)
Acutely managed comorbidities, n (%)
 CHF36 (26.9)38 (27.9).84
 Peripheral vascular disease4 (3.0)7 (5.2).54
 Diabetes without chronic complications27 (20.2)40 (29.4).078
 Renal disease, mild to moderate20 (14.9)18 (13.2).69
 Liver disease, mild1 (0.8)7 (5.2).066
 Chronic pulmonary disease4 (3.0)5 (3.7).999
 Myocardial infarction3 (2.2)7 (5.2).33
 Diabetes with chronic complications18 (13.4)12 (8.8).23
 Renal disease, severe17 (12.7)14 (10.3).54
 Liver disease, moderate to severe04 (2.9).12
 Metastatic solid tumor1 (0.8)1 (0.7).999
 AIDS7 (5.2)4 (2.9).38
 Anemia18 (13.4)24 (17.7).34
 Atrial fibrillation40 (29.9)38 (27.9).73
 Respiratory failure1 (0.8)3 (2.2).62
 Acute pneumonia11 (8.2)15 (11.0).43
 Bacteremia02 (1.5).5
 HTN90 (67.2)73 (53.7).024
 Orthostatic hypotension2 (1.5)8 (5.9).1
 OSA13 (9.7)14 (10.3).87

NOTE. BMI calculated as weight in kilograms divided by height in meters squared.

Abbreviations: CHF, congestive heart failure; HTN, essential (primary) hypertension; OSA, obstructive sleep apnea.

P<.001.

Not included in CCI.

P<.05.

Associations between total FIM gain and characteristics in 270 medically complex patients NOTE. BMI calculated as weight in kilograms divided by height in meters squared. Abbreviations: CHF, congestive heart failure; HTN, essential (primary) hypertension; OSA, obstructive sleep apnea. P<.001. Not included in CCI. P<.05. As shown in table 3, patients with FIM efficiency ≥2.12 had a shorter RLOS than those with FIM efficiency <2.12 (10.7±3.8 vs 14.5±7.0 days; P<.001), were more likely to be discharged to home (83% vs 60.7%; P<.001), less likely to be discharged to an SNF (7.4% vs 24.4%; P<.001), and less likely to be emergently transferred (9.6% vs 14.8%; P<.001). HTN was the only comorbidity significantly negatively associated with FIM efficiency (53.3% [FIM efficiency ≥2.12] vs 67.4% [FIM efficiency <2.12]; P=.025). There were no significant differences in age (P=.77), BMI (P=.28), sex (P=.33), race (P=.60), ethnicity (P=.99), insurance type (P=.13), or CCI (P=.50) between patients with FIM efficiency <2.12 and those with FIM efficiency ≥2.12.
Table 3

Associations between FIM efficiency and characteristics in 270 medically complex patients

CharacteristicFIM efficiency <2.12FIM efficiency ≥2.12P Value
n=135n=135
Age (y), mean ± SD73.3±12.773.8±12.3.77
BMI, mean ± SD30.3±11.629.0±8.2.28
Sex, n (%).33
 Female75 (55.6)67 (49.6)
 Male60 (44.4)68 (50.4)
Race, n (%).6
 White126 (93.3)129 (95.6)
 Non-White9 (6.7)6 (4.4)
Ethnicity, n (%).999
 Hispanic1 (0.7)2 (1.5)
 Non-Hispanic134 (99.3)133 (99.5)
Insurance type, n (%).13
 Commercial insurance33 (24.4)22 (16.3)
 Medicare102 (75.6)113 (83.7)
CCI score category, n (%).5
 Low (0-2)16 (11.9)22 (16.2)
 Moderate (3-4)59 (43.7)60 (44.4)
 High (>4)60 (44.4)53 (39.2)
RLOS (d), mean ± SD14.5±7.010.7±3.8<.001*
Discharge setting, n (%)<.001*
 Home82 (60.7)112 (83.0)
 Acute care hospital20 (14.8)13 (9.6)
 Skilled nursing facilities33 (24.4)10 (7.4)
Acutely managed comorbidities, n (%)
 CHF41 (30.4)33 (24.4).28
 Peripheral vascular disease6 (4.4)5 (3.7).999
 Diabetes without chronic complications31 (23.0)36 (26.7).48
 Renal disease, mild to moderate20 (14.8)18 (13.3).86
 Liver disease, mild1 (0.7)7 (5.2).067
 Chronic pulmonary disease4 (3.0)5 (3.7).999
 Myocardial infarction3 (2.2)7 (5.2).33
 Diabetes with chronic complications17 (12.6)13 (9.6).44
 Renal disease, severe20 (14.8)11 (8.2).086
 Liver disease, moderate to severe04 (3.0).12
 Metastatic solid tumor1 (0.7)1 (0.7).999
 AIDS8 (5.9)3 (2.2).22
 Anemia20 (14.8)22 (16.3).74
 Atrial fibrillation39 (28.9)39 (28.9).999
 Respiratory failure04 (3.0).12
 Acute pneumonia8 (5.9)18 (13.3).062
 Bacteremia1 (0.7)1 (0.7).999
 HTN91 (67.4)72 (53.3).025
 Orthostatic hypotension5 (3.7)5 (3.7).999
 OSA16 (11.9)11 (8.2).31

NOTE. BMI calculated as weight in kilograms divided by height in meters squared.

Abbreviations: CHF, congestive heart failure; HTN, essential (primary) hypertension; OSA, obstructive sleep apnea.

P<.001.

Not included in CCI.

P<.05.

Associations between FIM efficiency and characteristics in 270 medically complex patients NOTE. BMI calculated as weight in kilograms divided by height in meters squared. Abbreviations: CHF, congestive heart failure; HTN, essential (primary) hypertension; OSA, obstructive sleep apnea. P<.001. Not included in CCI. P<.05. As shown in table 4, patients discharged to an acute care hospital were younger than those discharged to home (67.2±15.1 vs 73.7±11.9 years; P=.015) or SNF (67.2±15.1 vs 78.0±11.4 years; P<.001). More patients with commercial insurance were emergently transferred to an acute care hospital as opposed to home or SNF (39.4% vs 20.6% and 4.6%, respectively; P<.001). RLOS was significantly lower for patients emergently discharged to an acute care hospital than those discharged to home or SNF (9.1±7.9 vs 12.7±5.3 and 15.1±5.6 days, respectively; P<.001). Metastatic solid tumors were the only comorbidity significantly associated with discharge location (6.1% [acute care hospital] vs 0% [home] and 0% [SNF]; P=.015). There were no significant differences in BMI (P=.91), sex (P=.99), race (P=.43), ethnicity (P=.38), or CCI (P=.98) between patients discharged to home, SNF, or acute care hospital. The association between renal disease and discharge destination was not statistically significant (P=.059).
Table 4

Associations between discharge settings and characteristics in 270 medically complex patients

CharacteristicAcute Care HospitalHomeSkilled Nurse FacilityP Value
n=33n=194n=43
Age (y), mean ± SD67.2±15.173.7±11.978.0±11.4<.001*
BMI, mean ± SD30.0±15.029.7±9.229.1±9.3.91
Sex, n (%).99
 Female17 (51.5)102 (52.6)23 (53.5)
 Male16 (48.5)92 (47.4)20 (46.5)
Race, n (%).43
 White30 (90.9)185 (95.4)40 (93.0)
 Non-White3 (9.1)9 (4.6)3 (7.0)
Ethnicity, n (%).38
 Hispanic1 (3.0)2 (1.0)0
 Non-Hispanic32 (97.0)192 (99.0)43 (100.0)
Insurance type, n (%)<.001*
 Commercial insurance13 (39.4)40 (20.6)2 (4.6)
 Medicare20 (60.6)154 (79.4)41 (95.4)
CCI score category, n (%).98
 Low (0-2)5 (15.2)28 (14.4)5 (11.6)
 Moderate (3-4)15 (45.5)84 (43.3)20 (46.5)
 High (>4)13 (39.4)82 (42.3)18 (41.9)
RLOS (d), mean ± SD9.1±7.912.7±5.315.1±5.6<.001*
FIM score at admission, mean ± SD
 Motor33.0±10.437.1±8.835.7±9.6.051
 Cognitive26.0±6.824.7±5.525.4±4.5.4
 Total subscales59.0±14.761.8±11.461.1±12.1.45
FIM score at discharge, mean ± SD
 Motor45.4±15.862.1±11.252.8±11.1<.001*
 Cognitive27.4±6.829.1±4.928.1±4.2.14
 Total subscales72.8±20.691.2±14.480.9±13.8<.001*
Acutely managed comorbidities, n (%)
 CHF9 (27.3)53 (27.3)12 (27.9)>.99
 Peripheral vascular disease3 (9.1)8 (4.1)0.12
 Diabetes without chronic complications5 (15.2)50 (25.8)12 (27.9).4
 Renal disease, mild to moderate1 (3.0)28 (14.4)9 (20.9).059
 Liver disease, mild07 (3.6)1 (2.3).85
 Chronic pulmonary disease2 (6.1)7 (3.6)0.34
 Myocardial infarction1 (3.0)9 (4.6)0.44
 Diabetes with chronic complications6 (18.2)20 (10.3)4 (9.3).39
 Renal disease, severe5 (15.2)23 (11.9)3 (7.0).48
 Liver disease, moderate to severe04 (2.1)0>.99
 Metastatic solid tumor2 (6.1)00.015
 AIDS2 (6.1)9 (4.6)0.32
 Anemia8 (24.2)28 (14.4)6 (14.0).35
 Atrial fibrillation7 (21.2)53 (27.3)18 (41.9).1
 Respiratory failure1 (3.0)3 (1.6)0.5
 Acute pneumonia4 (12.1)18 (9.3)4 (9.3).8
 Bacteremia02 (1.0)0>.99
 HTN21 (63.6)114 (58.8)28 (65.1).69
 Orthostatic hypotension09 (4.6)1 (2.3).59
 OSA4 (12.1)19 (9.8)4 (9.3).9

NOTE. BMI calculated as weight in kilograms divided by height in meters squared.

Abbreviations: CHF, congestive heart failure; HTN, essential (primary) hypertension; OSA, obstructive sleep apnea.

P<.05.

P<.001.

Not included in CCI.

Associations between discharge settings and characteristics in 270 medically complex patients NOTE. BMI calculated as weight in kilograms divided by height in meters squared. Abbreviations: CHF, congestive heart failure; HTN, essential (primary) hypertension; OSA, obstructive sleep apnea. P<.05. P<.001. Not included in CCI. The total FIM score at discharge was significantly associated with discharge disposition (see table 4). Patients discharged to home had the highest total discharge FIM followed by those discharged to an SNF and those discharged to acute care (91.2±14.4, 80.9±13.8 and 72.8±20.6, respectively; P<.001). This pattern was also observed for discharge FIM motor subscores (62.1 [home] vs 52.8 [SNF] and 45.4 [acute care hospital]; P<.001) but not for discharge FIM cognitive subscores (29.1 [home] vs 28.1 [SNF] and 27.4 [acute care hospital]; P=.14). As shown in table 5, when compared with patients with total FIM gain <27, those with total FIM gain ≥27 were 89% less likely to be discharged to an acute care hospital (OR, 0.11; P<.001) and 78% less likely to be discharged to an SNF (OR, 0.22; P<.001), after adjustment. Similarly, patients with FIM efficiency ≥2.12 were 75% less likely to be discharged to an SNF (OR, 0.25; P<.001) and 71% less likely to be discharged to an acute care hospital (OR, 0.29; P=.008).
Table 5

Adjusted* logistic regression for relationships between discharge destination and FIM total gain and FIM efficiency

Discharge SettingsOR (95% CI)
FIM Total GainFIM Efficiency
Home (n=194)ReferenceReference
Acute care hospital (n=33)0.11 (0.04-0.34)0.29 (0.12-0.73)
Skilled nursing facilities (n=43)0.22 (0.10-0.49)0.25 (0.11-0.56)

Adjusted for age, BMI, sex, insurance type, CCI category, RLOS, and HTN.

P<.001.

P<.05.

Adjusted* logistic regression for relationships between discharge destination and FIM total gain and FIM efficiency Adjusted for age, BMI, sex, insurance type, CCI category, RLOS, and HTN. P<.001. P<.05. The reasons for RTAC (n=33) are listed in table 6. The 5 most common reasons for RTAC were cardiac (21.1%), pulmonary (21.1%), acute blood loss anemia (21.1%), infection (15.2%), and neurologic (12.2%) conditions.
Table 6

Reasons for RTAC in 33Sof 270 medically complex patients

ReasonFrequency (%)
Cardiac (chest pain, NSTEMI, third degree block, bradycardia, or tachycardia)21.2
Pulmonary (PE, hypoxia, PNA, malignant pleural effusion, or pneumothorax)21.2
Acute blood loss anemia (GIB on anticoagulation or postoperative bleeding)21.2
Infection (postoperative wound infection, neutropenic fever, sepsis, or osteomyelitis)15.2
Neurologic (aphasia, severe headache, or altered mental status)12.2
Others (subtherapeutic INR for LVAD, SBO, or CKD with decreased urine output)9.0

Abbreviations: CKD, chronic kidney disease; GIB, gastrointestinal bleed; INR, international normalized ratio; LVAD, left ventricular assist device; NSTEMI, non-ST segment elevation myocardial infarction; PE, pulmonary embolism; PNA, pneumonia; SBO, small bowel obstruction.

Reasons for RTAC in 33Sof 270 medically complex patients Abbreviations: CKD, chronic kidney disease; GIB, gastrointestinal bleed; INR, international normalized ratio; LVAD, left ventricular assist device; NSTEMI, non-ST segment elevation myocardial infarction; PE, pulmonary embolism; PNA, pneumonia; SBO, small bowel obstruction.

Discussion

To our knowledge, this is the first study to investigate acute inpatient rehabilitation outcomes (FIM gain, FIM efficiency, RLOS, discharge destination, RTAC) in medically complex patients defined by non-CMS–compliant conditions, including a variety of IGCs, such as IGC08.9, IGC9, IGC10.1, IGC10.9, IGC16, and IGC 17.1-17.9. We have shown that medically complex patients greatly benefit from inpatient rehabilitation. A total of 71.9% were discharged to home, 15.9% to an SNF, and 12.2% for RTAC, with a mean RLOS of 12.6 days, mean total FIM gain of 26, and mean FIM efficiency of 2.3 in 270 medically complex patients. The mean RLOS, FIM efficiency, RTAC rate, and community discharge rate of medically complex patients were all better than their corresponding 15.82 days, 2.07, 13.83, and 70.9%, respectively, for all 1092 admissions at our facility in 2018. The mean FIM gain was similar between these 2 groups. Furthermore, RLOS, total FIM gain and FIM efficiency in this study were all better than their corresponding eRehabData-weighted national benchmarks (RLOS, 15.82 days; FIM gain, 25.57; FIM efficiency, 2.13) for a total of 202,520 discharges in 2018. RTAC and community discharge of eRehabData-weighted national benchmarks for all discharges in 2018 were 11.62% and 72.32%, respectively, which are similar to our results. When compared with patients with orthopedic diagnoses,medically complex patients in this study performed better in total FIM gain but not in FIM efficiency. This is likely related to differences in length of stay, which is factored into the FIM efficiency calculation. To compare with the CMS “60% compliant diagnoses,” total FIM gain in this study was lower than that in patients with stroke, Parkinson disease, and Guillain-Barre syndrome after inpatient rehabilitation, whereas their FIM efficiencies (1.6-2.04) were lower than FIM efficiency in medically complex patients. In another study, total FIM gain and FIM efficiency in patients with stroke and TBI were lower than those in medically complex patients. Therefore, medically complex patients greatly benefit from inpatient rehabilitation and should be recommended for acute inpatient rehabilitation. Patients with total FIM gain ≥27 were more likely to be discharged to home than those with total FIM gain <27 (86.8% vs 56.7%; P<.001), less likely to be discharged to an SNF (8.8% vs 23.1%; P<.001), and less likely to be discharged to RTAC (4.4% vs 20.2%; P<.001). Similarly, patients with FIM efficiency ≥2.12 had a shorter RLOS than those with FIM efficiency <2.12 (3.8 days vs 7.0 days; P<.001), were more likely to be discharged to home (83% vs 60.7%; P<.001), less likely to be discharged to an SNF (7.4% vs 24.4%; P<.001), and less likely to be emergently transferred (9.6% vs 14.8%; P<.001). These findings demonstrate an FIM gain of 27 or FIM efficiency of 2.12 predicts a high likelihood of home discharge and low likelihood of RTAC. However, discharge dispositions are multifactorial, including motor and cognitive functional status on admission or at discharge, socioeconomic situation, level of assistance that family or a caregiver can provide, and home setup.,,, Medically complex patients usually having slower and/or chronic onset of impairments may have the advantage of being more likely to have an already established social support system and thus be more likely to be able to go home than those who have acute functional impairments secondary to a stroke. HTN was the only comorbidity that negatively affected the total FIM gain and FIM efficiency in this study. There was no association observed between total FIM gain or FIM efficiency and patient age, BMI, sex, race, ethnicity, insurance type, RLOS, or CCI. However, it is possible that 1 or more comorbidities, in addition to HTN, that may be associated with rehabilitation outcomes were not captured in this study. The lack of association between total FIM gain or FIM efficiency and comorbidities is consistent with a previous study that reported that preexisting medical comorbidities had no effect on admission or discharge FIM scores in the postorthopedic surgery group, although the premorbid conditions were associated with lower admission and discharge FIM scores in the population with TBI. Similarly, no association between comorbidities and RLOS, total FIM gain, or community discharge rate was demonstrated in a study consisting of 280 patients (26% with ischemic/hemorrhagic stroke, 22% with other neurologic conditions, 52% with orthopedic conditions). Metastatic solid tumors were the only comorbidity associated with RTAC in our study (n=2, 6.1%; P=.015). However, only 2 patients with metastatic solid tumors in our study weakened this association. Alam et al reported that patients with neoplasms experience higher transfer rates than those without neoplasms because of increased susceptibility to infection. Lack of correlation between comorbidities and RTAC observed in this study is consistent with previous studies showing that medical comorbidities were not associated with RTAC, and functional status better predicted RTAC in patients with stroke, traumatic SCI, and other conditions.,, A recent study confirmed an increased risk for RTAC from a freestanding IRF when compared with IRFs housed within an acute care hospital. A recent narrative review further provides strong evidence that the principal predictors of RTAC are lower functional status on admission, more severe injury, and higher numbers of comorbidities. This review also highlights that RTAC is a complex, multifactorial patient issue with a complex interplay between the predictors and reasons for RTAC. The 5 most common reasons for RTAC in this study were cardiac, pulmonary, and acute blood loss anemia (21.1% for each category); infection (15.2%); and neurologic (12.2%) conditions, consistent with previous findings., The most common medical reasons for RTAC are infection (27%), neurologic (27%), and noninfectious respiratory (16%) conditions in patients with nontraumatic SCI. Hammond et al reported that the most common RTAC reasons were surgery (36%), infection (22%), noninfectious respiratory conditions (14%), and gastrointestinal conditions (8%). Therefore, knowing those potentially preventable conditions and then optimally managing them should be one of the focuses of our inpatient rehabilitation clinicians to reduce preventable RTAC, improve overall rehabilitation outcomes, and lower the cost.

Study limitations

This study had several limitations. This was a single-center retrospective study at a freestanding IRF, which may limit the ability to extrapolate results to inpatient rehabilitation units located within acute care hospitals. All study participants were admitted under the care of 1 attending physician, introducing the possibility of selection bias. The patient population in our study was predominantly White and non-Hispanic and therefore may not have captured racial or ethnic disparities, if present. Additionally, there are limitations associated with only 2 levels of FIM gain or FIM efficiency as rehabilitation measures using the median dichotomy design that fails to reflect the association between variables and outcome measures. We did not capture other factors that could affect medical complexity, such as concurrent psychiatric diagnoses, family and/or social support during and/or after acute care hospitalization and in the rehabilitation setting, cognitive impairment, and socioeconomic challenges. Further research allowing for these variables may find significant associations with other aspects of a patient's complexity that could lead to better FIM gains and increased home dispositions.

Conclusions

Although admission of medically complex patients to an IRF does not contribute to compliance with CMS's “60 Percent Rule,” there is ample evidence to support the benefits of acute inpatient rehabilitation on functional outcomes in this patient population. Except for HTN, no comorbidity or demographic variables were associated with functional outcomes in our study. Cardiac, pulmonary, acute blood loss anemia, infection, and neurologic conditions were the most common reasons for RTAC, and a focus on medical optimization in these areas may reduce unanticipated acute care transfers in medically complex patients. Medically complex patients in our study had better functional outcomes (total FIM gain, FIM efficiency, RLOS) than eRehabData-weighted national benchmarks, further supporting acute inpatient rehabilitation for this patient population.

Supplier

a. SAS version 9.4; SAS Institute, Cary, NC.
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7.  Comorbidity in post-stroke rehabilitation.

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