Functional status predicts acute care readmissions from inpatient rehabilitation in the stroke population

Objective: Acute care readmission risk is an increasingly recognized problem that has garnered significant attention, yet the reasons for acute care readmission in the inpatient rehabilitation population are complex and likely multifactorial. Information on both medical comorbidities and functional status is routinely collected for stroke patients participating in inpatient rehabilitation. We sought to determine whether functional status is a more robust predictor of acute care readmissions in the inpatient rehabilitation stroke population compared with medical comorbidities using a large, administrative data set. Methods: A retrospective analysis of data from the Uniform Data System for Medical Rehabilitation from the years 2002 to 2011 was performed examining stroke patients admitted to inpatient rehabilitation facilities. A Basic Model for predicting acute care readmission risk based on age and functional status was compared with models incorporating functional status and medical comorbidities (Basic-Plus) or models including age and medical comorbidities alone (Age-Comorbidity). C-statistics were compared to evaluate model performance. Findings: There were a total of 803,124 patients: 88,187 (11%) patients were transferred back to an acute hospital: 22,247 (2.8%) within 3 days, 43,481 (5.4%) within 7 days, and 85,431 (10.6%) within 30 days. The C-statistics for the Basic Model were 0.701, 0.672, and 0.682 at days 3, 7, and 30 respectively. As compared to the Basic Model, the best-performing Basic-Plus model was the Basic+Elixhauser model with C-statistics differences of +0.011, +0.011, and + 0.012, and the best-performing Age-Comorbidity model was the Age+Elixhauser model with C-statistic differences of -0.124, -0.098, and -0.098 at days 3, 7, and 30 respectively. Conclusions: Readmission models for the inpatient rehabilitation stroke population based on functional status and age showed better predictive ability than models based on medical comorbidities

Impact of Cognition on Burn Inpatient Rehabilitation Outcomes

Background: A significant proportion of burn injury patients are admitted to inpatient rehabilitation facilities (IRFs). There is increasing interest in the use of functional variables, such as cognition, in predicting IRF outcomes. Cognitive impairment is an important cause of disability in the burn injury population, yet its relationship to IRF outcomes has not been studied. Objective: To assess how cognitive function affects rehabilitation outcomes in the burn injury population. Design: Retrospective study. Setting: Inpatient rehabilitation facilities in the United States. Participants: A total of 5347 adults admitted to an IRF with burn injury between 2002 and 2011. Methods or Interventions: Multivariable regression was used to model rehabilitation outcome measures, using the cognitive domain of the Functional Independence Measure (FIM) instrument as the independent variable and controlling for demographic, medical, and facility covariates. Main Outcome Measurements: FIM total gain, readmission to an acute care setting at any time during inpatient rehabilitation, readmission to an acute care setting in the first 3 days of IRF admission, rate of discharge to the community setting, and length of stay efficiency. Results: Cognitive FIM total at admission was a significant predictor of FIM total gain, length of stay efficiency, and acute readmission at 3 days (P \u3c .05). Cognitive FIM total scores did not have an impact on acute care readmission rate or discharge to the community setting. Conclusions: Cognitive status may be an important predictor of rehabilitation outcomes in the burn injury population. Future work is needed to further examine the impact of specific cognitive interventions on rehabilitation outcomes in this population. Level of Evidence: I

Assessing the ability of comorbidity indexes to capture comorbid disease in the inpatient rehabilitation burn injury population

Objective: Burn patients exhibit comorbidities that influence outcomes. This study examines whether existing comorbidity measures capture comorbidities in the burn inpatient rehabilitation population. Design: Data were obtained from the Uniform Data System for Medical Rehabilitation from 2002 to 2011 for adults with burn injury. International Classification of Diseases, 9th Revision, codes were used to assess three comorbidity measures (Charlson Comorbidity Index, Elixhauser Comorbidity Index, Centers for Medicare and Medicaid Services Comorbidity Tiers). The number of subjects and unique comorbidity codes (91% of frequency) captured by each comorbidity measure was calculated. Results: The study included 5347 patients with a median total body surface area burn decile of 20%Y29%, mean age of 51.6 yrs, and mean number of comorbidities of 7.6. There were 2809 unique International Classification of Diseases, 9th Revision, comorbidity codes. The Charlson Comorbidity Index, Elixhauser Comorbidity Index, and Centers for Medicare and Medicaid Services Comorbidity Tiers did not capture 67%, 27%, and 58% of the subjects, respectively. There were 107 unique comorbidities that occurred with a frequency of greater than 1%. Of these, 67% were not captured in all three comorbidity measures. Conclusions: Commonly used comorbidity indexes do not reflect the extent of comorbid disease in the burn rehabilitation population. Future work is needed to assess the need for comorbidity indexes specific to the inpatient rehabilitation setting

Cognition in patients with burn injury in the inpatient rehabilitation population.

OBJECTIVE: To analyze potential cognitive impairment in patients with burn injury in the inpatient rehabilitation population. DESIGN: Rehabilitation patients with burn injury were compared with the following impairment groups: spinal cord injury, amputation, polytrauma and multiple fractures, and hip replacement. Differences between the groups were calculated for each cognitive subscale item and total cognitive FIM. Patients with burn injury were compared with the other groups using a bivariate linear regression model. A multivariable linear regression model was used to determine whether differences in cognition existed after adjusting for covariates (eg, sociodemographic factors, facility factors, medical complications) based on previous studies. SETTING: Inpatient rehabilitation facilities. PARTICIPANTS: Data from Uniform Data System for Medical Rehabilitation from 2002 to 2011 for adults with burn injury (N=5347) were compared with other rehabilitation populations (N=668,816). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Comparison of total cognitive FIM scores and subscales (memory, verbal comprehension, verbal expression, social interaction, problem solving) for patients with burn injury versus other rehabilitation populations. RESULTS: Adults with burn injuries had an average total cognitive FIM score ± SD of 26.8±7.0 compared with an average FIM score ± SD of 28.7±6.0 for the other groups combined (P CONCLUSIONS: Adults with burn injury have worse cognitive FIM scores than other rehabilitation populations. Future research is needed to determine the impact of this comorbidity on patient outcomes and potential interventions for these deficits

Functional Status Predicts Acute Care Readmissions from Inpatient Rehabilitation in the Stroke Population

Objective: Acute care readmission risk is an increasingly recognized problem that has garnered significant attention, yet the reasons for acute care readmission in the inpatient rehabilitation population are complex and likely multifactorial. Information on both medical comorbidities and functional status is routinely collected for stroke patients participating in inpatient rehabilitation. We sought to determine whether functional status is a more robust predictor of acute care readmissions in the inpatient rehabilitation stroke population compared with medical comorbidities using a large, administrative data set. Methods: A retrospective analysis of data from the Uniform Data System for Medical Rehabilitation from the years 2002 to 2011 was performed examining stroke patients admitted to inpatient rehabilitation facilities. A Basic Model for predicting acute care readmission risk based on age and functional status was compared with models incorporating functional status and medical comorbidities (Basic-Plus) or models including age and medical comorbidities alone (Age-Comorbidity). C-statistics were compared to evaluate model performance. Findings: There were a total of 803,124 patients: 88,187 (11%) patients were transferred back to an acute hospital: 22,247 (2.8%) within 3 days, 43,481 (5.4%) within 7 days, and 85,431 (10.6%) within 30 days. The C-statistics for the Basic Model were 0.701, 0.672, and 0.682 at days 3, 7, and 30 respectively. As compared to the Basic Model, the best-performing Basic-Plus model was the Basic+Elixhauser model with C-statistics differences of +0.011, +0.011, and + 0.012, and the best-performing Age-Comorbidity model was the Age+Elixhauser model with C-statistic differences of -0.124, -0.098, and -0.098 at days 3, 7, and 30 respectively. Conclusions: Readmission models for the inpatient rehabilitation stroke population based on functional status and age showed better predictive ability than models based on medical comorbidities

Women Physicians Are Underrepresented in Recognition Awards From the Association of Academic Physiatrists

Objective: Determine representation by gender for individual recognition awards presented to physicians by the Association of Academic Physiatrists (AAP). Design: Cross-sectional survey was used. Lists of individual recognition award recipients for the 27-yr history of the AAP awards (1990–2016) were analyzed. The primary outcome measures were the total numbers of men versus women physician award recipients overall and for the past decade (2007–2016). Results: No awards were given to women physicians for the past 4 yrs (2013–2016) or in half of the award categories for the past decade (2007–2016). No woman received the outstanding resident/fellow award since its inception (2010–2016). There was a decrease in the proportion of awards given to women in the past decade (2007–2016, 7 of 39 awards, 17.9%) as compared with the first 17 yrs (1990–2006, 10 of 46 awards, 21.7%). Furthermore, compared with their proportional membership within the specialty, women physicians were underrepresented for the entire 27-yr history of the AAP awards (1990–2016, 17 of 85 awards, 20%). According to the Association of American Medical Colleges, the proportion of full-time female physical medicine and rehabilitation faculty members was 38% in 1992 and 41% in 2013. Conclusions: Women physicians have been underrepresented by the AAP in recognition awards. Although the reasons are not clear, these findings should be further investigated

Functional Status Predicts Acute Care Readmissions from Inpatient Rehabilitation in the Stroke Population.

OBJECTIVE: Acute care readmission risk is an increasingly recognized problem that has garnered significant attention, yet the reasons for acute care readmission in the inpatient rehabilitation population are complex and likely multifactorial. Information on both medical comorbidities and functional status is routinely collected for stroke patients participating in inpatient rehabilitation. We sought to determine whether functional status is a more robust predictor of acute care readmissions in the inpatient rehabilitation stroke population compared with medical comorbidities using a large, administrative data set. METHODS: A retrospective analysis of data from the Uniform Data System for Medical Rehabilitation from the years 2002 to 2011 was performed examining stroke patients admitted to inpatient rehabilitation facilities. A Basic Model for predicting acute care readmission risk based on age and functional status was compared with models incorporating functional status and medical comorbidities (Basic-Plus) or models including age and medical comorbidities alone (Age-Comorbidity). C-statistics were compared to evaluate model performance. FINDINGS: There were a total of 803,124 patients: 88,187 (11%) patients were transferred back to an acute hospital: 22,247 (2.8%) within 3 days, 43,481 (5.4%) within 7 days, and 85,431 (10.6%) within 30 days. The C-statistics for the Basic Model were 0.701, 0.672, and 0.682 at days 3, 7, and 30 respectively. As compared to the Basic Model, the best-performing Basic-Plus model was the Basic+Elixhauser model with C-statistics differences of +0.011, +0.011, and + 0.012, and the best-performing Age-Comorbidity model was the Age+Elixhauser model with C-statistic differences of -0.124, -0.098, and -0.098 at days 3, 7, and 30 respectively. CONCLUSIONS: Readmission models for the inpatient rehabilitation stroke population based on functional status and age showed better predictive ability than models based on medical comorbidities

Logistic Regression Coefficients for the Basic Model.

<p>Data presented as Coefficient (95% Confidence Interval).</p><p>Logistic Regression Coefficients for the Basic Model.</p

Logistic regression models.

<p>*Deyo-Charlson sum scores are calculated as follows: The first sum score is based on summing the total number of comorbidities that a subject has that are on the Deyo-Charlson index. The second sum score is the total number of points from the Charlson index that the patient has.</p><p>Logistic regression models.</p