MedStar Authors catalog › Details for: Informatics and interaction: Applying human factors principles to optimize the design of clinical decision support for sepsis.
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Informatics and interaction: Applying human factors principles to optimize the design of clinical decision support for sepsis.

by Schubel, Laura; Mosby, Danielle L; Blumenthal, Joseph; Kowalski, Rebecca; Franklin, Ella; Littlejohn, Robin; Miller, Kristen.
Citation: Health Informatics Journal. :1460458219839623, 2019 May 13.Journal: Health informatics journal.Published: ; 2019ISSN: 1460-4582.Full author list: Schubel L; Mosby DL; Blumenthal J; Capan M; Arnold R; Kowalski R; Seagull FJ; Catchpole K; Schwartz JS; Franklin E; Littlejohn R; Miller KE.UI/PMID: 31081460.Subject(s): IN PROCESS -- NOT YET INDEXEDInstitution(s): MedStar Health Research Institute | MedStar Institute for InnovationDepartment(s): National Center for Human Factors in HealthcareActivity type: Journal Article.Medline article type(s): Journal ArticleDigital Object Identifier: https://dx.doi.org/10.1177/1460458219839623 (Click here) Abbreviated citation: HEALTH INFORM J. :1460458219839623, 2019 May 13.Abstract: In caring for patients with sepsis, the current structure of electronic health record systems allows clinical providers access to raw patient data without imputation of its significance. There are a wide range of sepsis alerts in clinical care that act as clinical decision support tools to assist in early recognition of sepsis; however, there are serious shortcomings in existing health information technology for alerting providers in a meaningful way. Little work has been done to evaluate and assess existing alerts using implementation and process outcomes associated with health information technology displays, specifically evaluating clinician preference and performance. We developed graphical model displays of two popular sepsis scoring systems, quick Sepsis Related Organ Failure Assessment and Predisposition, Infection, Response, Organ Failure, using human factors principles grounded in user-centered and interaction design. Models will be evaluated in a larger research effort to optimize alert design to improve the collective awareness of high-risk populations and develop a relevant point-of-care clinical decision support system for sepsis.

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