TY - JOUR
T1 - Impact of comorbidities on stroke rehabilitation outcomes
T2 - does the method matter?
AU - Berlowitz, Dan R.
AU - Hoenig, Helen
AU - Cowper, Diane C.
AU - Duncan, Pamela W.
AU - Vogel, W. Bruce
PY - 2008/10
Y1 - 2008/10
N2 - Berlowitz DR, Hoenig H, Cowper DC, Duncan PW, Vogel WB. Impact of comorbidities on stroke rehabilitation outcomes: does the method matter? Objectives: To 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. Design: Inception cohort of patients followed for 6 months. Setting: Department of Veterans Affairs (VA) hospitals. Participants: A total of 2402 patients beginning stroke rehabilitation at a VA facility in 2001 and included in the Integrated Stroke Outcomes Database. Interventions: Not applicable. Main Outcome Measures: Three outcomes were evaluated: 6-month mortality, 6-month rehospitalization, and change in FIM score. Results: During 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. Conclusions: Comorbidities 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.
AB - Berlowitz DR, Hoenig H, Cowper DC, Duncan PW, Vogel WB. Impact of comorbidities on stroke rehabilitation outcomes: does the method matter? Objectives: To 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. Design: Inception cohort of patients followed for 6 months. Setting: Department of Veterans Affairs (VA) hospitals. Participants: A total of 2402 patients beginning stroke rehabilitation at a VA facility in 2001 and included in the Integrated Stroke Outcomes Database. Interventions: Not applicable. Main Outcome Measures: Three outcomes were evaluated: 6-month mortality, 6-month rehospitalization, and change in FIM score. Results: During 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. Conclusions: Comorbidities 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.
KW - Cerebrovascular accident
KW - Comorbidity
KW - Rehabilitation
KW - Risk adjustment
UR - http://www.scopus.com/inward/record.url?scp=55649103918&partnerID=8YFLogxK
U2 - 10.1016/j.apmr.2008.03.024
DO - 10.1016/j.apmr.2008.03.024
M3 - Article
C2 - 18929019
AN - SCOPUS:55649103918
VL - 89
SP - 1903
EP - 1906
JO - Archives of Physical Medicine and Rehabilitation
JF - Archives of Physical Medicine and Rehabilitation
SN - 0003-9993
IS - 10
ER -