Literature DB >> 27664174

Avoiding alert fatigue in pulmonary embolism decision support: a new method to examine 'trigger rates'.

Anne Press1, Sundas Khan1, Lauren McCullagh1, Andy Schachter1, Salvatore Pardo2, Nina Kohn3, Thomas McGinn1.   

Abstract

A clinical decision support system (CDSS) is integrated into the electronic health record (EHR) and allows physicians to easily use a clinical decision support (CDS) tool. However, often CDSSs are integrated into the EHR with poor adoption rates. One reason for this is secondary to 'trigger fatigue'. Therefore, we developed a new and innovative usability process named 'sensitivity and specificity trigger analysis' (SSTA) as part of our larger project around a pulmonary embolism decision support tool. SSTA will enable programmers to examine optimal trigger rates prior to the integration of a CDS tool into the EHR, by using a formal method of analysis. We performed a retrospective chart review. The outcome of interest was physician ordering of a CT angiography (CTA). Phrases that signify common symptoms associated with pulmonary embolism were assessed as possible triggers for the CDSS tool. We then analysed each trigger's ability to predict physician ordering of a CTA. We found that the most sensitive way to trigger the Pulmonary Embolism CDS tool while still maintaining a high specificity was by combining 1 or more pertinent symptoms with 1 or more elements of the Wells criteria. This study explored a unique methodology, SSTA, used to limit inaccurate triggering of a CDS tool prior to integration into the EHR. This methodology can be applied to other studies aiming to decrease triggering rates and increase adoption rates of previously validated CDSS tools. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

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Year:  2016        PMID: 27664174     DOI: 10.1136/ebmed-2016-110440

Source DB:  PubMed          Journal:  Evid Based Med        ISSN: 1356-5524


  6 in total

1.  Development and Validation of a Natural Language Processing Tool to Identify Injuries in Infants Associated With Abuse.

Authors:  Gunjan Tiyyagura; Andrea G Asnes; John M Leventhal; Eugene D Shapiro; Marc Auerbach; Wei Teng; Emily Powers; Amy Thomas; Daniel M Lindberg; Justin McClelland; Carol Kutryb; Thomas Polzin; Karen Daughtridge; Virginia Sevin; Allen L Hsiao
Journal:  Acad Pediatr       Date:  2021-11-12       Impact factor: 2.993

2.  Higher Imaging Yield When Clinical Decision Support Is Used.

Authors:  Safiya Richardson; Stuart Cohen; Sundas Khan; Meng Zhang; Guang Qiu; Michael I Oppenheim; Thomas McGinn
Journal:  J Am Coll Radiol       Date:  2019-12-30       Impact factor: 5.532

3.  Agile Acceptance Test-Driven Development of Clinical Decision Support Advisories: Feasibility of Using Open Source Software.

Authors:  Mujeeb A Basit; Krystal L Baldwin; Vaishnavi Kannan; Emily L Flahaven; Cassandra J Parks; Jason M Ott; Duwayne L Willett
Journal:  JMIR Med Inform       Date:  2018-04-13

4.  Applying A/B Testing to Clinical Decision Support: Rapid Randomized Controlled Trials.

Authors:  Jonathan Austrian; Felicia Mendoza; Adam Szerencsy; Lucille Fenelon; Leora I Horwitz; Simon Jones; Masha Kuznetsova; Devin M Mann
Journal:  J Med Internet Res       Date:  2021-04-09       Impact factor: 5.428

5.  Electronic clinical decision support for children with minor head trauma and intracranial injuries: a sociotechnical analysis.

Authors:  Po-Yin Yen; Randi E Foraker; Jacob K Greenberg; Ayodamola Otun; Azzah Nasraddin; Ross C Brownson; Nathan Kuppermann; David D Limbrick
Journal:  BMC Med Inform Decis Mak       Date:  2021-05-19       Impact factor: 2.796

6.  Acceptance of clinical decision support system to prevent venous thromboembolism among nurses: an extension of the UTAUT model.

Authors:  Huixian Zha; Kouying Liu; Ting Tang; Yue-Heng Yin; Bei Dou; Ling Jiang; Hongyun Yan; Xingyue Tian; Rong Wang; Weiping Xie
Journal:  BMC Med Inform Decis Mak       Date:  2022-08-19       Impact factor: 3.298

  6 in total

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