A quantitative assessment of a methodology for collaborative specification and evaluation of clinical guidelines

Erez Shalom, Yuval Shahar, Meirav Taieb-Maimon, Guy Bar, Avi Yarkoni, Ohad Young, Susana B. Martins, Laszlo Vaszar, Mary K. Goldstein, Yair Liel, Akiva Leibowitz, Tal Marom, Eitan Lunenfeld

Research output: Contribution to journalArticlepeer-review

38 Scopus citations


We introduce a three-phase, nine-step methodology for specification of clinical guidelines (GLs) by expert physicians, clinical editors, and knowledge engineers and for quantitative evaluation of the specification's quality. We applied this methodology to a particular framework for incremental GL structuring (mark-up) and to GLs in three clinical domains. A gold-standard mark-up was created, including 196 plans and subplans, and 326 instances of ontological knowledge roles (KRs). A completeness measure of the acquired knowledge revealed that 97% of the plans and 91% of the KR instances of the GLs were recreated by the clinical editors. A correctness measure often revealed high variability within clinical editor pairs structuring each GL, but for all GLs and clinical editors the specification quality was significantly higher than random (p < 0.01). Procedural KRs were more difficult to mark-up than declarative KRs. We conclude that given an ontology-specific consensus, clinical editors with mark-up training can structure GL knowledge with high completeness, whereas the main demand for correct structuring is training in the ontology's semantics.

Original languageEnglish
Pages (from-to)889-903
Number of pages15
JournalJournal of Biomedical Informatics
Issue number6
StatePublished - Dec 2008
Externally publishedYes


  • Clinical decision support systems
  • Clinical guidelines
  • Completeness
  • Correctness
  • Evaluation
  • Knowledge acquisition
  • Knowledge bases
  • Mark-up
  • Ontologies
  • Structuring


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