From data collection to knowledge data discovery: a medical application of data mining.
Prison inmates are exposed to a variety of major risk factors (psychiatric disorders, suicide attempts, illicit drug use). From 1986 to 1996, the USA prison population more than doubled while in France, it increased from 35655 in 1980 to 51623 in 1995. In spite of these findings, very little information concerning the inmates population is available. At the present time, there is a desire to adopt a policy based on the prevention of recidivism, on adequate release planning and referrals to community-based services. The aim of the RAPPEL project was to build an information system for assessing the social and health status of prison inmates. The pilot project was set up at the prison of Loos and allowed the collection and analysis of nearly 15000 records. The aim of this paper is to present the extension of the project consisting in developing a regional network grouping 11 jails. Information locally available will serve as the basis for the information system of regional jails. Data mining techniques will provide solutions for the extraction of new information. Three data mining tools were experimented : association rules, classification trees and clustering. Further extension consists in a distributed approach allowing direct access to the information system by WEB tools.
Duhamel
A
A
CERIM, Faculté de Médecine, 59045 Lille Cedex, France. alain.duhamel@univ-lille2.fr
Picavet
M
M
Devos
P
P
Beuscart
R
R
D002965:Classification; D003625:Data Collection / Q000379:methods*; D003627:Data Interpretation, Statistical; D019992:Databases as Topic; D005602:France; D006304:Health Status; D006801:Humans; D016247:Information Storage and Retrieval; D010865:Pilot Projects; D011329:Prisoners / Q000706:statistics & numerical data*; D012959:Socioeconomic Factors; D011795:Surveys and Questionnaires