Intelligent Data Mining for Medical Quality Management
Wolf Stühlinger, Oliver Hogl, Herbert Stoyan, Michael Müller · 2000
. In the healthcare sector cost pressure is growing, quality demands are rising and the competitive situation amongst suppliers is mounting. These developments confront hospitals more than ever with the necessities of critically reviewing their own efficiency under both medical and economical aspects. At the same time growing capture of medical data and integration of distributed and heterogeneous databases create a completely new base for medical quality and cost management. Against this background we applied intelligent data mining methods to patient data from several clinics and from years 1996 to 1998. This includes data-driven as well as interest-driven analyses. Questions were targeted on the quality of data, of standards, of plans, and of treatments. For these issues in the field of medical quality management interesting data mining results were discovered in this project . 1 INTRODUCTION Reforms in the healthcare sector have caused a continuously rising cost pressure during...