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.
Number: 367
Keywords: cost analysis, big data, disease burden, Electronic Medical Records, primary care, cost sharing
JEL codes: I18, C55, C81
Volume: 14
Issue: 3
Date: Wednesday, February 10, 2016
Revision Date: Wednesday, February 10, 2016