title: Analysis of guideline compliance--a data mining approach.
abstract: While guideline-based decision support is safety-critical and typically requires human interaction, offline analysis of guideline compliance can be performed to large extent automatically. We examine the possibility of automatic detection of potential non-compliance followed up with (statistical) association mining. Only frequent associations of non-compliance patterns with various patient data are submitted to medical expert for interpretation. The initial experiment was carried out in the domain of hypertension management.
authors.affiliation: European Centre for Medical Informatics, Statistics and Epidemiology-Cardio, Czech Republic. svatek@vze.cz
authors.forename: Vojtech
authors.initials: V
authors.lastname: Svátek
authors.forename: Antonín
authors.initials: A
authors.lastname: Ríha
authors.forename: Jan
authors.initials: J
authors.lastname: Peleska
authors.forename: Jan
authors.initials: J
authors.lastname: Rauch
mesh_terms: D003658:Decision Making, Computer-Assisted; D020000:Decision Support Systems, Clinical; D019317:Evidence-Based Medicine; D019983:Guideline Adherence; D006801:Humans; D017410:Practice Guidelines as Topic; D010818:Practice Patterns, Physicians'; D012984:Software