Literature DB >> 33853395

The appropriateness of clinical decision support systems alerts in supporting clinical workflows: A systematic review.

Olufisayo Olusegun Olakotan1, Maryati Mohd Yusof1.   

Abstract

A CDSS generates a high number of inappropriate alerts that interrupt the clinical workflow. As a result, clinicians silence, disable, or ignore alerts, thereby undermining patient safety. Therefore, the effectiveness and appropriateness of CDSS alerts need to be evaluated. A systematic review was carried out to identify the factors that affect CDSS alert appropriateness in supporting clinical workflow. Seven electronic databases (PubMed, Scopus, ACM, Science Direct, IEEE, Ovid Medline, and Ebscohost) were searched for English language articles published between 1997 and 2018. Seventy six papers met the inclusion criteria, of which 26, 24, 15, and 11 papers are retrospective cohort, qualitative, quantitative, and mixed-method studies, respectively. The review highlights various factors influencing the appropriateness and efficiencies of CDSS alerts. These factors are categorized into technology, human, organization, and process aspects using a combination of approaches, including socio-technical framework, five rights of CDSS, and Lean. Most CDSS alerts were not properly designed based on human factor methods and principles, explaining high alert overrides in clinical practices. The identified factors and recommendations from the review may offer valuable insights into how CDSS alerts can be designed appropriately to support clinical workflow.

Entities:  

Keywords:  Lean; alert fatigue; appropriateness; clinical decision support systems; clinical workflow

Year:  2021        PMID: 33853395     DOI: 10.1177/14604582211007536

Source DB:  PubMed          Journal:  Health Informatics J        ISSN: 1460-4582            Impact factor:   2.681


  8 in total

Review 1.  Modulators Influencing Medication Alert Acceptance: An Explorative Review.

Authors:  Janina A Bittmann; Walter E Haefeli; Hanna M Seidling
Journal:  Appl Clin Inform       Date:  2022-08-18       Impact factor: 2.762

2.  Guidelines: innovation needed to overcome barriers to use.

Authors:  Jo-Anne Manski-Nankervis
Journal:  Aust Prescr       Date:  2022-06-01

Review 3.  Electronic Health Records and Heart Failure.

Authors:  David P Kao
Journal:  Heart Fail Clin       Date:  2022-03-04       Impact factor: 2.828

4.  Alerts in Clinical Decision Support Systems (CDSS): A Bibliometric Review and Content Analysis.

Authors:  Shuo-Chen Chien; Ya-Lin Chen; Chia-Hui Chien; Yen-Po Chin; Chang Ho Yoon; Chun-You Chen; Hsuan-Chia Yang; Yu-Chuan Jack Li
Journal:  Healthcare (Basel)       Date:  2022-03-23

Review 5.  Barriers and enablers to implementing and using clinical decision support systems for chronic diseases: a qualitative systematic review and meta-aggregation.

Authors:  Winnie Chen; Claire Maree O'Bryan; Gillian Gorham; Kirsten Howard; Bhavya Balasubramanya; Patrick Coffey; Asanga Abeyaratne; Alan Cass
Journal:  Implement Sci Commun       Date:  2022-07-28

6.  Design, effectiveness, and economic outcomes of contemporary chronic disease clinical decision support systems: a systematic review and meta-analysis.

Authors:  Winnie Chen; Kirsten Howard; Gillian Gorham; Claire Maree O'Bryan; Patrick Coffey; Bhavya Balasubramanya; Asanga Abeyaratne; Alan Cass
Journal:  J Am Med Inform Assoc       Date:  2022-09-12       Impact factor: 7.942

7.  Impact of interactive computerised decision support for hospital antibiotic use (COMPASS): an open-label, cluster-randomised trial in three Swiss hospitals.

Authors:  Gaud Catho; Julien Sauser; Valentina Coray; Serge Da Silva; Luigia Elzi; Stephan Harbarth; Laurent Kaiser; Christophe Marti; Rodolphe Meyer; Francesco Pagnamenta; Javier Portela; Virginie Prendki; Alice Ranzani; Nicolò Saverio Centemero; Jerome Stirnemann; Roberta Valotti; Nathalie Vernaz; Brigitte Waldispuehl Suter; Enos Bernasconi; Benedikt D Huttner
Journal:  Lancet Infect Dis       Date:  2022-07-20       Impact factor: 71.421

8.  Assessing Data Adequacy for High Blood Pressure Clinical Decision Support: A Quantitative Analysis.

Authors:  David A Dorr; Christopher D'Autremont; Christie Pizzimenti; Nicole Weiskopf; Robert Rope; Steven Kassakian; Joshua E Richardson; Rob McClure; Floyd Eisenberg
Journal:  Appl Clin Inform       Date:  2021-08-04       Impact factor: 2.762

  8 in total

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