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2013 | OriginalPaper | Chapter

38. Mining Administrative Health Databases for Epidemiological Purposes: A Case Study on Acute Myocardial Infarctions Diagnoses

Authors : Francesca Ieva, Anna Maria Paganoni, Piercesare Secchi

Published in: Advances in Theoretical and Applied Statistics

Publisher: Springer Berlin Heidelberg

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Abstract

We present a pilot data mining analysis on the subset of the Public Health Database (PHD) of Lombardia Region concerning hospital discharge data relative to Acute Myocardial Infarctions without ST segment elevation (NON-STEMI). The analysis is carried out using nonlinear semi-parametric and parametric mixed effects models, in order to detect different patterns of growth in the number of NON-STEMI diagnoses within the 30 largest clinical structures of Lombardia Region, along the time period 2000–2007. The analysis is a seminal example of statistical support to decision makers in clinical context, aimed at monitoring the diffusion of new procedures and the effects of health policy interventions.

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Metadata
Title
Mining Administrative Health Databases for Epidemiological Purposes: A Case Study on Acute Myocardial Infarctions Diagnoses
Authors
Francesca Ieva
Anna Maria Paganoni
Piercesare Secchi
Copyright Year
2013
Publisher
Springer Berlin Heidelberg
Book
Advances in Theoretical and Applied Statistics

Print ISBN: 978-3-642-35587-5

Electronic ISBN: 978-3-642-35588-2

Copyright Year: 2013

DOI
https://doi.org/10.1007/978-3-642-35588-2_38

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