Donna Huang1, Chloe Slocum2, Julie K Silver3, James W Morgan3, Richard Goldstein3, Ross Zafonte3, Jeffrey C Schneider3. 1. a Department of Physical Medicine and Rehabilitation , Spaulding Rehabilitation Hospital/Harvard Medical School , Massachusetts , USA. 2. b Commonwealth Fund Mongan Fellow, Harvard Medical School, Harvard T.H. Chan School of Public Health , Department of Health Policy and Management, Spaulding Rehabilitation Hospital, Department of Physical Medicine and Rehabilitation , Massachusetts , USA. 3. c Department of Physical Medicine and Rehabilitation , Spaulding Rehabilitation Hospital/Harvard Medical School , Massachusetts , USA.
Abstract
CONTEXT/ OBJECTIVE: Acute care readmission has been identified as an important marker of healthcare quality. Most previous models assessing risk prediction of readmission incorporate variables for medical comorbidity. We hypothesized that functional status is a more robust predictor of readmission in the spinal cord injury population than medical comorbidities. DESIGN: Retrospective cross-sectional analysis. SETTING: Inpatient rehabilitation facilities, Uniform Data System for Medical Rehabilitation data from 2002 to 2012. PARTICIPANTS: traumatic spinal cord injury patients. OUTCOME MEASURES: A logistic regression model for predicting acute care readmission based on demographic variables and functional status (Functional Model) was compared with models incorporating demographics, functional status, and medical comorbidities (Functional-Plus) or models including demographics and medical comorbidities (Demographic-Comorbidity). The primary outcomes were 3- and 30-day readmission, and the primary measure of model performance was the c-statistic. RESULTS: There were a total of 68,395 patients with 1,469 (2.15%) readmitted at 3 days and 7,081 (10.35%) readmitted at 30 days. The c-statistics for the Functional Model were 0.703 and 0.654 for 3 and 30 days. The Functional Model outperformed Demographic-Comorbidity models at 3 days (c-statistic difference: 0.066-0.096) and outperformed two of the three Demographic-Comorbidity models at 30 days (c-statistic difference: 0.029-0.056). The Functional-Plus models exhibited negligible improvements (0.002-0.010) in model performance compared to the Functional models. CONCLUSION: Readmissions are used as a marker of hospital performance. Function-based readmission models in the spinal cord injury population outperform models incorporating medical comorbidities. Readmission risk models for this population would benefit from the inclusion of functional status.
CONTEXT/ OBJECTIVE: Acute care readmission has been identified as an important marker of healthcare quality. Most previous models assessing risk prediction of readmission incorporate variables for medical comorbidity. We hypothesized that functional status is a more robust predictor of readmission in the spinal cord injury population than medical comorbidities. DESIGN: Retrospective cross-sectional analysis. SETTING: Inpatient rehabilitation facilities, Uniform Data System for Medical Rehabilitation data from 2002 to 2012. PARTICIPANTS: traumatic spinal cord injurypatients. OUTCOME MEASURES: A logistic regression model for predicting acute care readmission based on demographic variables and functional status (Functional Model) was compared with models incorporating demographics, functional status, and medical comorbidities (Functional-Plus) or models including demographics and medical comorbidities (Demographic-Comorbidity). The primary outcomes were 3- and 30-day readmission, and the primary measure of model performance was the c-statistic. RESULTS: There were a total of 68,395 patients with 1,469 (2.15%) readmitted at 3 days and 7,081 (10.35%) readmitted at 30 days. The c-statistics for the Functional Model were 0.703 and 0.654 for 3 and 30 days. The Functional Model outperformed Demographic-Comorbidity models at 3 days (c-statistic difference: 0.066-0.096) and outperformed two of the three Demographic-Comorbidity models at 30 days (c-statistic difference: 0.029-0.056). The Functional-Plus models exhibited negligible improvements (0.002-0.010) in model performance compared to the Functional models. CONCLUSION: Readmissions are used as a marker of hospital performance. Function-based readmission models in the spinal cord injury population outperform models incorporating medical comorbidities. Readmission risk models for this population would benefit from the inclusion of functional status.
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