Over the past 15 years, a major global initiative has been undertaken to develop, disseminate, and implement clinical practice guidelines. The worthy goals of the initiative have been to diminish inappropriate practice, to improve health outcomes, to control the rising costs of health care, and to speed the translation of the fruits of research into practice. Major resource investments.both intellectual and financial.have been dedicated to creating a scientifically based approach to define what constitutes appropriate practice. The initiative has spawned a plethora of guidelines, protocols, algorithms, decision support tools, care paths, and utilization and performance review criteria, and has contributed mightily to the development of evidence-based medicine. At the same time, many practice guidelines have become de facto repositories of the best knowledge about "ideal" clinical practice.
A longstanding informatics challenge has been to develop efficient mechanisms whereby valid medical knowledge.such as that contained in practice guidelines.can be operationalized in systems that support decision making by clinicians. However, a frustrating impediment to the satisfaction of this goal has been the difficulty of translation of guideline knowledge into computable formats. The gulf between guideline authors and the technical personnel responsible for instantiating guideline knowledge in decision support systems is broad.
With funding from the National Library of Medicine, our group has achieved a number of successes in bridging the guideline implementation gap. Our work in creating and standardizing the Guideline Elements Model (GEM), an XML-based representation of guideline knowledge, has provided both insights and tools to address these issues of knowledge acquisition and operationalization. We have also established a working relationship with national professional societies that has allowed us to participate in real world guideline development activities. We propose a research program whose overarching goal is to enable domain experts to transform knowledge about best practices into systems that can influence clinical care.
We plan to:
- Create a library of representative guideline recommendation statements that will be used to better understand and characterize the current corpus of guideline statements and to serve as a resource for modeling and evaluation activities;
- Delineate the range of ambiguous, vague, and underspecified recommendation statements and devise targeted remedies;
- Analyze the terminology of obligation (deontic components) used in guideline recommendation statements to understand how this concept can be applied most effectively;
- Create an ontology of recommendations by integrating an NLP-based semantic analysis of a body of exemplary guideline statements with a domain-oriented recommendation model;
- Apply Attempto Controlled English (ACE) to improve the authoring and the implementation of guideline recommendations;
- Develop and evaluate a controlled language editor with WYSIWYM interface for use by domain experts to facilitate authoring of recommendations that can be translated into decision support tools.
