Report Number: CS-TR-98-1609
Institution: Stanford University, Department of Computer Science
Title: Automated creation of clinical-practice guidelines from decision models
Author: Sanders, Gillian D.
Date: July 1998
Abstract: I developed an approach that allows clinical-practice guideline (CPG) developers to create, disseminate, and tailor CPGs, using decision models (DMs). I propose that guideline developers can use computer-based DMs that reflect global and site-specific data to generate CPGs. Such CPGs are high quality, can be tailored to specific settings, and can be modified automatically as the DM or evidence evolves. I defined conceptual models for representing CPGs and DMs, and formalized a method for mapping between these two representations. I designed a DM annotation editor that queries the decision analyst for missing knowledge. I implemented the ALCHEMIST system that encompasses the conceptual models, mapping algorithm, and the resulting tailoring abilities. I evaluated the design of both conceptual models, and the accuracy of the mapping algorithm. To show that ALCHEMIST produces high-quality CPGs, I had users rate the quality of produced CPGs using a guideline-rating key, and evaluate ALCHEMIST's tailoring abilities. ALCHEMIST automates the DM-to-CPG process and distributes the CPG over the web to allow local developers to apply, tailor, and maintain a global CPG. I argue that my framework is a method for guideline developers to create and maintain automated CPGs, and it thus promotes high-quality and cost-effective health care.