Endorsement, Prior Action, and Language: Modeling Trusted Advice in Computerized Clinical Alerts

dc.contributor.authorChattopadhyay, Debaleena
dc.contributor.authorDuke, Jon
dc.contributor.authorBolchini, Davide
dc.contributor.departmentHuman-Centered Computing, School of Informatics and Computingen_US
dc.date.accessioned2017-12-01T18:37:30Z
dc.date.available2017-12-01T18:37:30Z
dc.date.issued2016-05
dc.description.abstractThe safe prescribing of medications via computerized physician order entry routinely relies on clinical alerts. Alert compliance, however, remains surprisingly low, with up to 95% often ignored. Prior approaches, such as improving presentational factors in alert design, had limited success, mainly due to physicians' lack of trust in computerized advice. While designing trustworthy alert is key, actionable design principles to embody elements of trust in alerts remain little explored. To mitigate this gap, we introduce a model to guide the design of trust-based clinical alerts-based on what physicians value when trusting advice from peers in clinical activities. We discuss three key dimensions to craft trusted alerts: using colleagues' endorsement, foregrounding physicians' prior actions, and adopting a suitable language. We exemplify our approach with emerging alert designs from our ongoing research with physicians and contribute to the current debate on how to design effective alerts to improve patient safety.en_US
dc.eprint.versionAuthor's manuscripten_US
dc.identifier.citationChattopadhyay, D., Duke, J. D., & Bolchini, D. (2016, May). Endorsement, Prior Action, and Language: Modeling Trusted Advice in Computerized Clinical Alerts. In Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems (pp. 2027-2033). ACM. https://doi.org/10.1145/2851581.2892315en_US
dc.identifier.urihttps://hdl.handle.net/1805/14698
dc.language.isoenen_US
dc.publisherACMen_US
dc.relation.isversionof10.1145/2851581.2892315en_US
dc.relation.journal2016 CHI Conference Extended Abstracts on Human Factors in Computing Systemsen_US
dc.rightsPublisher Policyen_US
dc.sourceAuthoren_US
dc.subjectclinical alertsen_US
dc.subjecthealthen_US
dc.subjecthealth informaticsen_US
dc.titleEndorsement, Prior Action, and Language: Modeling Trusted Advice in Computerized Clinical Alertsen_US
dc.typeConference proceedingsen_US
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