Literature DB >> 31777057

Evaluating the Impact of Interruptive Alerts within a Health System: Use, Response Time, and Cumulative Time Burden.

Pierre Elias1, Eric Peterson2, Bob Wachter3, Cary Ward2, Eric Poon4, Ann Marie Navar2.   

Abstract

BACKGROUND: Health systems often employ interruptive alerts through the electronic health record to improve patient care. However, concerns of "alert fatigue" have been raised, highlighting the importance of understanding the time burden and impact of these alerts on providers.
OBJECTIVES: Our main objective was to determine the total time providers spent on interruptive alerts in both inpatient and outpatient settings. Our secondary objectives were to analyze dwell time for individual alerts and examine both provider and alert-related factors associated with dwell time variance.
METHODS: We retrospectively evaluated use and response to the 75 most common interruptive ("popup") alerts between June 1st, 2015 and November 1st, 2016 in a large academic health care system. Alert "dwell time" was calculated as the time between the alert appearing on a provider's screen until it was closed. The total number of alerts and dwell times per provider per month was calculated for inpatient and outpatient alerts and compared across alert type.
RESULTS: The median number of alerts seen by a provider was 12 per month (IQR 4-34). Overall, 67% of inpatient and 39% of outpatient alerts were closed in under 3 seconds. Alerts related to patient safety and those requiring more than a single click to proceed had significantly longer median dwell times of 5.2 and 6.7 seconds, respectively. The median total monthly time spent by providers viewing alerts was 49 seconds on inpatient alerts and 28 seconds on outpatient alerts.
CONCLUSION: Most alerts were closed in under 3 seconds and a provider's total time spent on alerts was less than 1 min/mo. Alert fatigue may lie in their interruptive and noncritical nature rather than time burden. Monitoring alert interaction time can function as a valuable metric to assess the impact of alerts on workflow and potentially identify routinely ignored alerts. Georg Thieme Verlag KG Stuttgart · New York.

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Mesh:

Year:  2019        PMID: 31777057      PMCID: PMC6881214          DOI: 10.1055/s-0039-1700869

Source DB:  PubMed          Journal:  Appl Clin Inform        ISSN: 1869-0327            Impact factor:   2.342


  20 in total

1.  Alert dwell time: introduction of a measure to evaluate interruptive clinical decision support alerts.

Authors:  Robert B McDaniel; Jonathan D Burlison; Donald K Baker; Murad Hasan; Jennifer Robertson; Christine Hartford; Scott C Howard; Andras Sablauer; James M Hoffman
Journal:  J Am Med Inform Assoc       Date:  2015-10-24       Impact factor: 4.497

2.  The Effects of Medication Alerts on Prescriber Response in a Pediatric Hospital.

Authors:  Judith W Dexheimer; Eric S Kirkendall; Michal Kouril; Philip A Hagedorn; Thomas Minich; Leo L Duan; Monifa Mahdi; Rhonda Szczesniak; S Andrew Spooner
Journal:  Appl Clin Inform       Date:  2017-05-10       Impact factor: 2.342

3.  Evaluation of Clinical Relevance of Drug-Drug Interaction Alerts Prior to Implementation.

Authors:  S M M Meslin; W Y Zheng; R O Day; E M Y Tay; M T Baysari
Journal:  Appl Clin Inform       Date:  2018-11-28       Impact factor: 2.342

4.  The Burden of Inbox Notifications in Commercial Electronic Health Records.

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Journal:  JAMA Intern Med       Date:  2016-04       Impact factor: 21.873

Review 5.  Medication-related clinical decision support in computerized provider order entry systems: a review.

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Journal:  J Am Med Inform Assoc       Date:  2006-10-26       Impact factor: 4.497

6.  Electronic Health Record Alert-Related Workload as a Predictor of Burnout in Primary Care Providers.

Authors:  Megan E Gregory; Elise Russo; Hardeep Singh
Journal:  Appl Clin Inform       Date:  2017-07-05       Impact factor: 2.342

7.  Overrides of medication-related clinical decision support alerts in outpatients.

Authors:  Karen C Nanji; Sarah P Slight; Diane L Seger; Insook Cho; Julie M Fiskio; Lisa M Redden; Lynn A Volk; David W Bates
Journal:  J Am Med Inform Assoc       Date:  2013-10-28       Impact factor: 4.497

8.  Determining Inappropriate Medication Alerts from "Inaccurate Warning" Overrides in the Intensive Care Unit.

Authors:  Christine A Rehr; Adrian Wong; Diane L Seger; David W Bates
Journal:  Appl Clin Inform       Date:  2018-04-25       Impact factor: 2.342

9.  Evaluating alert fatigue over time to EHR-based clinical trial alerts: findings from a randomized controlled study.

Authors:  Peter J Embi; Anthony C Leonard
Journal:  J Am Med Inform Assoc       Date:  2012-04-25       Impact factor: 4.497

10.  Are we heeding the warning signs? Examining providers' overrides of computerized drug-drug interaction alerts in primary care.

Authors:  Sarah P Slight; Diane L Seger; Karen C Nanji; Insook Cho; Nivethietha Maniam; Patricia C Dykes; David W Bates
Journal:  PLoS One       Date:  2013-12-26       Impact factor: 3.240

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Review 2.  Modulators Influencing Medication Alert Acceptance: An Explorative Review.

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Review 3.  Clinical Decision Support Stewardship: Best Practices and Techniques to Monitor and Improve Interruptive Alerts.

Authors:  Juan D Chaparro; Jonathan M Beus; Adam C Dziorny; Philip A Hagedorn; Sean Hernandez; Swaminathan Kandaswamy; Eric S Kirkendall; Allison B McCoy; Naveen Muthu; Evan W Orenstein
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4.  Impact of Kidney Failure Risk Prediction Clinical Decision Support on Monitoring and Referral in Primary Care Management of CKD: A Randomized Pragmatic Clinical Trial.

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Authors:  Denise J van der Nat; Victor J B Huiskes; Aatke van der Maas; Judith Y M N Derijks-Engwegen; Hein A W van Onzenoort; Bart J F van den Bemt
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