Impact of Comorbidities on Stroke Rehabilitation Outcomes: Does the Method Matter?

Berlowitz DR, Hoenig H, Cowper DC, Duncan PW, Vogel WB. Impact of comorbidities on stroke rehabilitation outcomes: does the method matter?ObjectivesTo examine the impact of comorbidities in predicting stroke rehabilitation outcomes and to examine differences among 3 commonly used comorbidity measures—the Charlson Index, adjusted clinical groups (ACGs), and diagnosis cost groups (DCGs)—in how well they predict these outcomes.DesignInception cohort of patients followed for 6 months.SettingDepartment of Veterans Affairs (VA) hospitals.ParticipantsA total of 2402 patients beginning stroke rehabilitation at a VA facility in 2001 and included in the Integrated Stroke Outcomes Database.InterventionsNot applicable.Main Outcome MeasuresThree outcomes were evaluated: 6-month mortality, 6-month rehospitalization, and change in FIM score.ResultsDuring 6 months of follow-up, 27.6% of patients were rehospitalized and 8.6% died. The mean FIM score increased an average of 20 points during rehabilitation. Addition of comorbidities to the age and sex models improved their performance in predicting these outcomes based on changes in c statistics for logistic and R2 values for linear regression models. While ACG and DCG models performed similarly, the best models, based on DCGs, had a c statistic of .74 for 6-month mortality and .63 for 6-month rehospitalization, and an R2 of .111 for change in FIM score.ConclusionsComorbidities are important predictors of stroke rehabilitation outcomes. How they are classified has important implications for models that may be used in assessing quality of care.