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Appl Clin Inform 2024; 15(05): 860-868
DOI: 10.1055/s-0044-1789574
Research Article

Optimizing Decision Support Alerts to Reduce Telemetry Duration: A Multicenter Evaluation

Niloofar Latifi
1   Division of Hospital Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
,
Trent Johnson
2   Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
,
Amy M. Knight
3   Division of Hospital Medicine, Division of General Internal Medicine Biomedical Informatics and Data Science Section, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
,
Laura Prichett
4   Department of Pediatrics, Johns Hopkins University Biostatistics, Epidemiology, and Data Management Core, Baltimore, Maryland, United States
,
Bahareh Modanloo
4   Department of Pediatrics, Johns Hopkins University Biostatistics, Epidemiology, and Data Management Core, Baltimore, Maryland, United States
,
Trushar Dungarani
5   Community Physicians, Johns Hopkins Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
,
Sammy Zakaria
6   Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
,
Amit Pahwa
7   Division of Hospital Medicine, Department of Medicine and Pediatrics, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
› Author Affiliations Funding Funding for this study was obtained from the Division of Hospital Medicine “Hospitalists Scholars Fund,” Johns Hopkins Hospital. The funding agency did not have input on the design or analysis of this study.
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Abstract

Background Telemetry monitoring is crucial for high-risk patients but excessive use beyond practice standards increases costs. Prior studies have shown that electronic health record (EHR) alerts reduce low-value telemetry monitoring. However, specific components of these alerts that contribute to effectiveness are unknown.

Objectives We aimed to revise previously implemented EHR Best Practice Advisories (BPAs) to optimize their effectiveness in reducing telemetry duration. The secondary objective was to assess the impact on clinicians' alert burden.

Methods A multicenter retrospective study was conducted at Johns Hopkins Hospital (JHH), Johns Hopkins Bayview Medical Center (JHBMC), and Howard County General Hospital (HCGH). An EHR alert in the form of a BPA was previously implemented at JHH/JHBMC, firing at 24, 48, or 72 hours based on order indication. HCGH used an alert firing every 24 hours. A revised BPA was implemented at all hospitals optimizing the prior JHH/JHBMC alert by including patient-specific telemetry indications, restricting alerts to daytime hours (8:00 a.m.–6:00 p.m.), and embedding the discontinuation order within the BPA alert. A retrospective analysis from October 2018 to December 2021 was performed. The primary outcome was telemetry duration. The secondary outcome was the mean monthly BPA alerts per patient-day.

Results Compared with the original BPA, the revised BPA reduced telemetry duration by a mean of 6.7 hours (95% CI: 5.2–9.1 hours, p < 0.001) at JHH/JHBMC, with a minimal increase of 0.06 mean monthly BPA alerts per patient-day (p < 0.001). The BPA acceptance rate increased from 7.8 to 31.3% postintervention at JHH/JHBMC (p < 0.0001). At HCGH, the intervention led to a mean monthly reduction of 20.2 hours in telemetry duration per hospitalization (95% CI: 19.1–22.8 hours, p < 0.0001).

Conclusion Optimizing EHR BPAs reduces unnecessary telemetry duration without substantially increasing clinician alert burden. This study highlights the importance of tailoring EHR alerts to enhance effectiveness and promote value-based care.

Keywords

telemetry - clinical decision support - electronic health record - value-based health care

Protection of Human and Animal Subjects

The study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects and was reviewed by the Institutional Review Boards at JHH, JHBMC, and HCGH.




Publication History

Received: 02 April 2024

Accepted: 27 July 2024

Article published online:
23 October 2024

© 2024. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

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