In this work, we develop Bayes rules for several families of loss functions for hospital report cards under a Bayesian semiparametric hierarchical model. Moreover, we present some robustness analysis with respect to the choice of the loss function, focusing on the number of hospitals our procedure identifies as “unacceptably performing”. The analysis is carried out on a case study dataset arising from MOMI2 (Month MOnitoring Myocardial Infarction in MIlan) survey on patients admitted with ST-Elevation Myocardial Infarction to the hospitals of Milan Cardiological Network. The major aim of this work is the ranking of the health-care providers performances, together with the assessment of the role of patients’ and providers’ characteristics on survival outcome.

Hospital clustering in the treatment of acute myocardial infarction patients via a bayesian semiparametric approach / A. Guglielmi, F. Ieva, A.M. Paganoni, F. Ruggeri (STUDIES IN CLASSIFICATION, DATA ANALYSIS, AND KNOWLEDGE ORGANIZATION). - In: Statistical Models for Data Analysis / [a cura di] P. Giudici, S. Ingrassia, M. Vichi. - Prima edizione. - [s.l] : Springer, 2013. - ISBN 9783319000312. - pp. 141-149 (( Intervento presentato al 8. convegno Classification and Data Analysis Group tenutosi a Pavia nel 2011 [10.1007/978-3-319-00032-9_17].

Hospital clustering in the treatment of acute myocardial infarction patients via a bayesian semiparametric approach

F. Ieva
Secondo
;
2013

Abstract

In this work, we develop Bayes rules for several families of loss functions for hospital report cards under a Bayesian semiparametric hierarchical model. Moreover, we present some robustness analysis with respect to the choice of the loss function, focusing on the number of hospitals our procedure identifies as “unacceptably performing”. The analysis is carried out on a case study dataset arising from MOMI2 (Month MOnitoring Myocardial Infarction in MIlan) survey on patients admitted with ST-Elevation Myocardial Infarction to the hospitals of Milan Cardiological Network. The major aim of this work is the ranking of the health-care providers performances, together with the assessment of the role of patients’ and providers’ characteristics on survival outcome.
Computer Science Applications1707 Computer Vision and Pattern Recognition; Information Systems; Information Systems and Management; Analysis
Settore SECS-S/01 - Statistica
2013
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/422642
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