Modeling public health care expenditure using patient level data: Empirical evidence from Italy
Atella VincenzoBelotti FedericoConti ValentinaCricelli ClaudioKOPINSKA JOANNAPiano Mortari Andrea
CEIS Research Paper
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
JEL codes: I18, C55, C81
Date: Wednesday, February 10, 2016
Revision Date: Wednesday, February 10, 2016