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Value-based healthcare in ischemic stroke care: case-mix adjustment models for clinical and patient-reported outcomes

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...

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Detalles Bibliográficos
Autores principales: Oemrawsingh, Arvind, van Leeuwen, Nikki, Venema, Esmee, Limburg, Martien, de Leeuw, Frank-Erik, Wijffels, Markus P., de Groot, Aafke J., Hilkens, Pieter H. E., Hazelzet, Jan A., Dippel, Diederik W. J., Bakker, Carla H., Voogdt-Pruis, Helene R., Lingsma, Hester F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6896707/
https://www.ncbi.nlm.nih.gov/pubmed/31805876
http://dx.doi.org/10.1186/s12874-019-0864-z
Descripción
Sumario: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 (β = 0.041), socio-economic status (β = − 0.019) and nationality (β = − 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.