In this work we describe statistical analyses conducted on MOMI2 (MOnth MOnitoring Myocardial Infarction in MIlan) survey, a collection of data concerning patients admitted with STEMI (ST-Elevation Myocardial Infarction) diagnosis in one of the hospitals belonging to the Network in Milan urban area. The main goal of the analyses is statistical exploration, description and model of collected data in order to answer speci c clinical questions (i.e. whether the result of certain healthcare policy is less or more e ective than another one, whether the logistic organization or time scheduling of Emergency Room (ER) and rescue units can be improved, etc). Such results can be used as an e ective support to decisional process for clinical and organizational governance. The fundamental result of this study is not only the use of advanced and innovative statistical tools, but also the social impact of the achieved results thanks to the synergic interaction between statisticians and physicians.

Multilevel models for clinical registers concerning STEMI patients in a complex urban reality: a statistical analysis of MOMI2 survey / F. Ieva, A.M. Paganoni. - In: COMMUNICATIONS IN APPLIED AND INDUSTRIAL MATHEMATICS. - ISSN 2038-0909. - 1:1(2010), pp. 128-147. [10.1685/2010CAIM477]

Multilevel models for clinical registers concerning STEMI patients in a complex urban reality: a statistical analysis of MOMI2 survey

F. Ieva
Primo
;
2010

Abstract

In this work we describe statistical analyses conducted on MOMI2 (MOnth MOnitoring Myocardial Infarction in MIlan) survey, a collection of data concerning patients admitted with STEMI (ST-Elevation Myocardial Infarction) diagnosis in one of the hospitals belonging to the Network in Milan urban area. The main goal of the analyses is statistical exploration, description and model of collected data in order to answer speci c clinical questions (i.e. whether the result of certain healthcare policy is less or more e ective than another one, whether the logistic organization or time scheduling of Emergency Room (ER) and rescue units can be improved, etc). Such results can be used as an e ective support to decisional process for clinical and organizational governance. The fundamental result of this study is not only the use of advanced and innovative statistical tools, but also the social impact of the achieved results thanks to the synergic interaction between statisticians and physicians.
In-hospital mortality ; Generalized Linear Mixed Models ; Data Mining ; ST-Elevation Myocardial Infarction ; Random Effects
Settore SECS-S/01 - Statistica
Settore MED/01 - Statistica Medica
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/233530
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