Modeling public health care expenditure using patient level data: Empirical evidence from Italy

Vincenzo Atella, Federico Belotti, Valentina Conti (), Claudio Cricelli (), Joanna Kopinska and Andrea Piano Mortari
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Claudio Cricelli: SIMG

No 367, CEIS Research Paper from Tor Vergata University, CEIS

Abstract: In this work we present some results obtained with a unique database of patient level data collected through GPs. The availability of such data opens new scenarios and paradigms for the planning and management of the health care system and for policy impact evaluation studies. The dataset, representative of the Italian population, contains detailed information on prescribed drugs, laboratory tests, outpatient visits and hospitalizations of more than 2 millions patients, managed by 900 GPs overtime. This pool of registers has produced a stock of information on about 25 millions of medical diagnosis, 100 millions of laboratory and diagnostic tests, 10 millions of blood pressure measurements and 50 millions of drug prescriptions. Using this novel dataset we analyze the expenditures of the Italian NHS over time, across age and geographical areas for the period from 2004 to 2011.

Keywords: cost analysis; big data; disease burden; Electronic Medical Records; primary care; cost sharing (search for similar items in EconPapers)
JEL-codes: C55 C81 I18 (search for similar items in EconPapers)
Pages: 36 pages
Date: 2016-02-10, Revised 2016-02-10
New Economics Papers: this item is included in nep-eur and nep-hea
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