GEM: A proposal for a more comprehensive guideline document model using XML

Citation
Rn. Shiffman et al., GEM: A proposal for a more comprehensive guideline document model using XML, J AM MED IN, 7(5), 2000, pp. 488-498
Citations number
34
Categorie Soggetti
Library & Information Science","General & Internal Medicine
Journal title
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
ISSN journal
10675027 → ACNP
Volume
7
Issue
5
Year of publication
2000
Pages
488 - 498
Database
ISI
SICI code
1067-5027(200009/10)7:5<488:GAPFAM>2.0.ZU;2-#
Abstract
Objective: To develop a guideline document model that includes a sufficient ly broad set of concepts to be useful throughout the guideline life cycle. Design: Current guideline document models are limited in that they reflect the specific orientation of the stakeholder who created them; thus, develop ers and disseminators often provide few constructs for conceptualizing reco mmendations, while implementers de-emphasize concepts related to establishi ng guideline validity. The authors developed the Guideline Elements Model ( GEM) using XML to better represent the heterogeneous knowledge contained in practice guidelines. Core constructs were derived from the Institute of Me dicine's Guideline Appraisal Instrument, the National Guideline Clearinghou se, and the augmented decision table guideline representation. These were s upplemented by additional concepts from a literature review. Results: The GEM hierarchy includes more than 100 elements. Major concepts relate to a guideline's identity, developer, purpose, intended audience, me thod of development, target population, knowledge components, testing, and review plan. Knowledge components in guideline documents include recommenda tions (which in turn comprise conditionals and imperatives), definitions, a nd algorithms. Conclusion: GEM is more comprehensive than existing models and is expressiv ely adequate to represent the heterogeneous information contained in guidel ines. Use of XML contributes to a flexible, comprehensible, shareable, and reusable knowledge representation that is both readable by human beings and processible by computers.