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How are ontologies implemented to represent clinical practice guidelines in clinical decision support systems: protocol for a systematic review.
Sadeghi-Ghyassi, Fatemeh; Damanabi, Shahla; Kalankesh, Leila R; Van de Velde, Stijn; Feizi-Derakhshi, Mohammad-Reza; Hajebrahimi, Sakineh.
Affiliation
  • Sadeghi-Ghyassi F; Department of Health Information Technology, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran.
  • Damanabi S; Research Center for Evidence Based-Medicine, Iranian EBM Center: A Joanna Briggs Institute Center of Excellence, Tabriz University of Medical Sciences, Tabriz, Iran.
  • Kalankesh LR; Department of Health Information Technology, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran. damanabish@tbzmed.ac.ir.
  • Van de Velde S; Health Services Management Research Center, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran.
  • Feizi-Derakhshi MR; Norwegian Institute of Public Health, Oslo, Norway.
  • Hajebrahimi S; ComInSys Lab., Department of Computer Engineering, University of Tabriz, Tabriz, Iran.
Syst Rev ; 11(1): 183, 2022 08 31.
Article in En | MEDLINE | ID: mdl-36042520
ABSTRACT

BACKGROUND:

Clinical practice guidelines are statements which are based on the best available evidence, and their goal is to improve the quality of patient care. Integrating clinical practice guidelines into computer systems can help physicians reduce medical errors and help them to have the best possible practice. Guideline-based clinical decision support systems play a significant role in supporting physicians in their decisions. Meantime, system errors are the most critical concerns in designing decision support systems that can affect their performance and efficacy. A well-developed ontology can be helpful in this matter. The proposed systematic review will specify the methods, components, language of rules, and evaluation methods of current ontology-driven guideline-based clinical decision support systems.

METHODS:

This review will identify literature through searching MEDLINE (via Ovid), PubMed, EMBASE, Cochrane Library, CINAHL, ScienceDirect, IEEEXplore, and ACM Digital Library. Gray literature, reference lists, and citing articles of the included studies will be searched. The quality of the included studies will be assessed by the mixed methods appraisal tool (MMAT-version 2018). At least two independent reviewers will perform the screening, quality assessment, and data extraction. A third reviewer will resolve any disagreements. Proper data analysis will be performed based on the type of system and ontology engineering evaluation data.

DISCUSSION:

The study will provide evidence regarding applying ontologies in guideline-based clinical decision support systems. The findings of this systematic review will be a guide for decision support system designers and developers, technologists, system providers, policymakers, and stakeholders. Ontology builders can use the information in this review to build well-structured ontologies for personalized medicine. SYSTEMATIC REVIEW REGISTRATION PROSPERO CRD42018106501.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Decision Support Systems, Clinical Type of study: Guideline / Prognostic_studies / Qualitative_research / Systematic_reviews Limits: Humans Language: En Journal: Syst Rev Year: 2022 Document type: Article Affiliation country: Iran

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Decision Support Systems, Clinical Type of study: Guideline / Prognostic_studies / Qualitative_research / Systematic_reviews Limits: Humans Language: En Journal: Syst Rev Year: 2022 Document type: Article Affiliation country: Iran