期刊
BMC MEDICAL RESEARCH METHODOLOGY
卷 19, 期 1, 页码 -出版社
BMC
DOI: 10.1186/s12874-019-0864-z
关键词
Ischemic stroke; Case-mix; Risk adjustment model; Patient-reported outcome measure; Value-based healthcare
资金
- Stichting Kwaliteitsgelden Medisch Specialisten
- insurance company Achmea/Zilveren Kruis
Background: Patient-Reported Outcome Measures (PROMs) have been proposed for benchmarking health care quality across hospitals, which requires extensive case-mix adjustment. The current study's aim was to develop and compare case-mix models for mortality, a functional outcome, and a patient-reported outcome measure (PROM) in ischemic stroke care. Methods: Data from ischemic stroke patients, admitted to four stroke centers in the Netherlands between 2014 and 2016 with available outcome information (N = 1022), was analyzed. Case-mix adjustment models were developed for mortality, modified Rankin Scale (mRS) scores and EQ-5D index scores with respectively binary logistic, proportional odds and linear regression models with stepwise backward selection. Predictive ability of these models was determined with R-squared (R-2) and area-under-the-receiver-operating-characteristic-curve (AUC) statistics. Results: Age, NIHSS score on admission, and heart failure were the only common predictors across all three case-mix adjustment models. Specific predictors for the EQ-5D index score were sex (beta = 0.041), socio-economic status (beta = -0.019) and nationality (beta = -0.074). R-2-values for the regression models for mortality (5 predictors), mRS score (9 predictors) and EQ-5D utility score (12 predictors), were respectively R-2 = 0.44, R-2 = 0.42 and R-2 = 0.37. Conclusions: The set of case-mix adjustment variables for the EQ-5D at three months differed considerably from the set for clinical outcomes in stroke care. The case-mix adjustment variables that were specific to this PROM were sex, socio-economic status and nationality. These variables should be considered in future attempts to risk-adjust for PROMs during benchmarking of hospitals.
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