Christopher R Pretz1, James E Graham2, Addie Middleton3, Amol M Karmarkar3, Kenneth J Ottenbacher3. 1. Research Department, Craig Hospital, Englewood, CO. 2. Division of Rehabilitation Sciences, University of Texas Medical Branch, Galveston, TX. Electronic address: jegraham@utmb.edu. 3. Division of Rehabilitation Sciences, University of Texas Medical Branch, Galveston, TX.
Abstract
OBJECTIVES: To model 12-month rehospitalization risk among Medicare beneficiaries receiving inpatient rehabilitation for spinal cord injury (SCI) or traumatic brain injury (TBI) and to create 2 (SCI- and TBI-specific) interactive tools enabling users to generate monthly projected probabilities of rehospitalization on the basis of an individual patient's clinical profile at discharge from inpatient rehabilitation. DESIGN: Secondary data analysis. SETTING: Inpatient rehabilitation facilities. PARTICIPANTS: Medicare beneficiaries receiving inpatient rehabilitation for SCI (n=2587) or TBI (n=10,864). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Monthly rehospitalization (yes/no) based on Medicare claims. RESULTS: Results are summarized through computer-generated interactive tools, which plot individual level trajectories of rehospitalization probabilities over time. Factors associated with the probability of rehospitalization over time are also provided, with different combinations of these factors generating different individual level trajectories. Four case studies are presented to demonstrate the variability in individual risk trajectories. Monthly rehospitalization probabilities for the individual high-risk TBI and SCI cases declined from 33% to 15% and from 41% to 18%, respectively, over time, whereas the probabilities for the individual low-risk cases were much lower and stable over time: 5% to 2% and 6% to 2%, respectively. CONCLUSIONS: Rehospitalization is an undesirable and multifaceted health outcome. Classifying patients into meaningful risk strata at different stages of their recovery is a positive step forward in anticipating and managing their unique health care needs over time.
OBJECTIVES: To model 12-month rehospitalization risk among Medicare beneficiaries receiving inpatient rehabilitation for spinal cord injury (SCI) or traumatic brain injury (TBI) and to create 2 (SCI- and TBI-specific) interactive tools enabling users to generate monthly projected probabilities of rehospitalization on the basis of an individual patient's clinical profile at discharge from inpatient rehabilitation. DESIGN: Secondary data analysis. SETTING: Inpatient rehabilitation facilities. PARTICIPANTS: Medicare beneficiaries receiving inpatient rehabilitation for SCI (n=2587) or TBI (n=10,864). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Monthly rehospitalization (yes/no) based on Medicare claims. RESULTS: Results are summarized through computer-generated interactive tools, which plot individual level trajectories of rehospitalization probabilities over time. Factors associated with the probability of rehospitalization over time are also provided, with different combinations of these factors generating different individual level trajectories. Four case studies are presented to demonstrate the variability in individual risk trajectories. Monthly rehospitalization probabilities for the individual high-risk TBI and SCI cases declined from 33% to 15% and from 41% to 18%, respectively, over time, whereas the probabilities for the individual low-risk cases were much lower and stable over time: 5% to 2% and 6% to 2%, respectively. CONCLUSIONS: Rehospitalization is an undesirable and multifaceted health outcome. Classifying patients into meaningful risk strata at different stages of their recovery is a positive step forward in anticipating and managing their unique health care needs over time.
Authors: Carl V Granger; Amol M Karmarkar; James E Graham; Anne Deutsch; Paulette Niewczyk; Margaret A Divita; Kenneth J Ottenbacher Journal: Am J Phys Med Rehabil Date: 2012-04 Impact factor: 2.159
Authors: Carl V Granger; Samuel J Markello; James E Graham; Anne Deutsch; Timothy A Reistetter; Kenneth J Ottenbacher Journal: Am J Phys Med Rehabil Date: 2010-04 Impact factor: 2.159
Authors: Allan J Kozlowski; Christopher R Pretz; Kristen Dams-O'Connor; Scott Kreider; Gale Whiteneck Journal: Arch Phys Med Rehabil Date: 2012-08-17 Impact factor: 3.966