Towards Symbiosis in Knowledge Representation and Natural Language Processing for Structuring Clinical Practice Guidelines

The successful adoption by clinicians of evidence-based clinical practice guidelines (CPGs) contained in clinical information systems requires efficient translation of free-text guidelines into computable formats. Natural language processing (NLP) has the potential to improve the efficiency of such translation. However, it is laborious to develop NLP to structure free-text CPGs using existing formal knowledge representations (KR). In response to this challenge, this vision paper discusses the value and feasibility of supporting symbiosis in text-based knowledge acquisition (KA) and KR. We compare two ontologies: (1) an ontology manually created by domain experts for CPG eligibility criteria and (2) an upper-level ontology derived from a semantic pattern-based approach for automatic KA from CPG eligibility criteria text. Then we discuss the strengths and limitations of interweaving KA and NLP for KR purposes and important considerations for achieving the symbiosis of KR and NLP for structuring CPGs to achieve evidence-based clinical practice.

[1]  Hongfang Liu,et al.  Generality and reuse in a common type system for clinical natural language processing , 2011, MIXHS '11.

[2]  Cui Tao,et al.  Managing interoperability and compleXity in health systems - MIXHS'12 , 2012, CIKM.

[3]  Elena Beisswanger,et al.  BioTop: An upper domain ontology for the life sciencesA description of its current structure, contents and interfaces to OBO ontologies , 2008, Appl. Ontology.

[4]  R Serban,et al.  Exploiting thesauri knowledge in medical guideline formalization. , 2009, Methods of information in medicine.

[5]  Peter D. Stetson,et al.  Model Formulation: An Electronic Health Record Based on Structured Narrative , 2008, J. Am. Medical Informatics Assoc..

[6]  Michael Krauthammer,et al.  Writing Clinical Practice Guidelines in Controlled Natural Language , 2009, CNL.

[7]  Stephen B. Johnson,et al.  Conceptual knowledge acquisition in biomedicine: A methodological review , 2007, J. Biomed. Informatics.

[8]  Alexa T. McCray,et al.  An Upper-Level Ontology for the Biomedical Domain , 2003, Comparative and functional genomics.

[9]  Frank van Harmelen,et al.  Extraction and use of linguistic patterns for modelling medical guidelines , 2007, Artif. Intell. Medicine.

[10]  Xiaoying Wu,et al.  EliXR: an approach to eligibility criteria extraction and representation , 2011, J. Am. Medical Informatics Assoc..

[11]  Yaron Denekamp,et al.  Mapping computerized clinical guidelines to electronic medical records: Knowledge-data ontological mapper (KDOM) , 2008, J. Biomed. Informatics.

[12]  Robert Arp,et al.  Function, Role and Disposition in Basic Formal Ontology , 2008 .

[13]  Mor Peleg,et al.  A practical method for transforming free-text eligibility criteria into computable criteria , 2011, J. Biomed. Informatics.