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Updated: Jan 2, 2026

Optimized Management of Endovascular Treatment for Acute Ischemic Stroke
Published on: January 18, 2018
Value-based healthcare in ischemic stroke care: case-mix adjustment models for clinical and patient-reported outcomes
Arvind Oemrawsingh1, Nikki van Leeuwen2, Esmee Venema2,3
1Center for Medical Decision Making, Department of Public Health, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, the Netherlands. a.oemrawsingh@erasmusmc.nl.
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 (R2) 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 (β = 0.041), socio-economic status (β = - 0.019) and nationality (β = - 0.074). R2-values for the regression models for mortality (5 predictors), mRS score (9 predictors) and EQ-5D utility score (12 predictors), were respectively R2 = 0.44, R2 = 0.42 and R2 = 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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