Patient Safety in Guideline-based Decision Support for Hypertension Management: ATHENA DSS
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The Institute of Medicine recently issued a landmark report on medical error.1 In the penumbra of this report, every aspect of health care is subject to new scrutiny regarding patient safety. Informatics technology can support patient safety by correcting problems inherent in older technology; however, new information technology can also contribute to new sources of error. We report here a categorization of possible errors that may arise in deploying a system designed to give guideline-based advice on prescribing drugs, an approach to anticipating these errors in an automated guideline system, and design features to minimize errors and thereby maximize patient safety. Our guideline implementation system, based on the EON architecture, provides a framework for a knowledge base that is sufficiently comprehensive to incorporate safety information, and that is easily reviewed and updated by clinician-experts.
Semantically enabling clinical decision support recommendations.
Seneviratne O, Das A, Chari S, Agu N, Rashid S, McCusker J J Biomed Semantics. 2023; 14(1):8.
PMID: 37464259 PMC: 10353186. DOI: 10.1186/s13326-023-00285-9.
Shahmoradi L, Safdari R, Ahmadi H, Zahmatkeshan M Med J Islam Repub Iran. 2021; 35:27.
PMID: 34169039 PMC: 8214039. DOI: 10.47176/mjiri.35.27.
Usman O, Oshiro C, Chambers J, Tu S, Martins S, Robinson A AMIA Annu Symp Proc. 2019; 2018:1046-1055.
PMID: 31019657 PMC: 6457366.
Bilici E, Despotou G, Arvanitis T Digit Health. 2018; 4:2055207618804927.
PMID: 30302270 PMC: 6172935. DOI: 10.1177/2055207618804927.
Automating Performance Measures and Clinical Practice Guidelines: Differences and Complementarities.
Tu S, Martins S, Oshiro C, Yuen K, Wang D, Robinson A AMIA Annu Symp Proc. 2017; 2016:1199-1208.
PMID: 28269917 PMC: 5333302.