Application of human factors to improve usability of clinical decision support for diagnostic decision-making: a scenario-based simulation study.
decision making
decision support, clinical
diagnostic errors
emergency department
human factors
Journal
BMJ quality & safety
ISSN: 2044-5423
Titre abrégé: BMJ Qual Saf
Pays: England
ID NLM: 101546984
Informations de publication
Date de publication:
04 2020
04 2020
Historique:
received:
28
05
2019
revised:
11
10
2019
accepted:
05
11
2019
pubmed:
30
11
2019
medline:
16
1
2021
entrez:
29
11
2019
Statut:
ppublish
Résumé
In this study, we used human factors (HF) methods and principles to design a clinical decision support (CDS) that provides cognitive support to the pulmonary embolism (PE) diagnostic decision-making process in the emergency department. We hypothesised that the application of HF methods and principles will produce a more usable CDS that improves PE diagnostic decision-making, in particular decision about appropriate clinical pathway. We conducted a scenario-based simulation study to compare a HF-based CDS (the so-called CDS for PE diagnosis (PE-Dx CDS)) with a web-based CDS (MDCalc); 32 emergency physicians performed various tasks using both CDS. PE-Dx integrated HF design principles such as automating information acquisition and analysis, and minimising workload. We assessed all three dimensions of usability using both objective and subjective measures: effectiveness (eg, appropriate decision regarding the PE diagnostic pathway), efficiency (eg, time spent, perceived workload) and satisfaction (perceived usability of CDS). Emergency physicians made more appropriate diagnostic decisions (94% with PE-Dx; 84% with web-based CDS; p<0.01) and performed experimental tasks faster with the PE-Dx CDS (on average 96 s per scenario with PE-Dx; 117 s with web-based CDS; p<0.001). They also reported lower workload (p<0.001) and higher satisfaction (p<0.001) with PE-Dx. This simulation study shows that HF methods and principles can improve usability of CDS and diagnostic decision-making. Aspects of the HF-based CDS that provided cognitive support to emergency physicians and improved diagnostic performance included automation of information acquisition (eg, auto-populating risk scoring algorithms), minimisation of workload and support of decision selection (eg, recommending a clinical pathway). These HF design principles can be applied to the design of other CDS technologies to improve diagnostic safety.
Identifiants
pubmed: 31776197
pii: bmjqs-2019-009857
doi: 10.1136/bmjqs-2019-009857
pmc: PMC7490974
mid: NIHMS1606646
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, P.H.S.
Langues
eng
Pagination
329-340Subventions
Organisme : NLM NIH HHS
ID : T15 LM007450
Pays : United States
Organisme : AHRQ HHS
ID : K08 HS024342
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR002373
Pays : United States
Organisme : AHRQ HHS
ID : K08 HS024558
Pays : United States
Organisme : AHRQ HHS
ID : R01 HS022086
Pays : United States
Informations de copyright
© Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.
Déclaration de conflit d'intérêts
Competing interests: None declared.
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