Formalising medical quality indicators to improve guidelines

Authors:
Marjolein van Gendt;Annette ten Teije;Radu Serban;Frank van Harmelen
Affiliations:
Dept. of Artificial Intelligence, Vrije Universiteit Amsterdam, Amsterdam, Netherlands;Dept. of Artificial Intelligence, Vrije Universiteit Amsterdam, Amsterdam, Netherlands;Dept. of Artificial Intelligence, Vrije Universiteit Amsterdam, Amsterdam, Netherlands;Dept. of Artificial Intelligence, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
Venue:
AIME'05 Proceedings of the 10th conference on Artificial Intelligence in Medicine
Year:
2005

Citing 0
Cited 3

Position paper: Temporal representation and reasoning in medicine: Research directions and challenges

Artificial Intelligence in Medicine
Combining task execution and background knowledge for the verification of medical guidelines

Knowledge-Based Systems
Authoring and verification of clinical guidelines: A model driven approach

Journal of Biomedical Informatics

Quantified Score

Hi-index	0.00

Visualization

Abstract

Medical guidelines can significantly improve quality of medical care and reduce costs. But how do we get sound and well-structured guidelines? This paper investigates the use of quality indicators that are formulated by medical institutions to evaluate medical care. The main research questions are (i) whether it is possible to formalise those indicators in a specific knowledge representation language for medical guidelines, and (ii) whether it is possible to verify whether such guidelines do indeed satisfy these indicators. In a case study on two real-life guidelines (Diabetes and Jaundice) we have studied 35 indicators, that were developped independently from these guidelines. Of these 25 (71%!) suggested anomalies in one of the guidelines in our case study.