Evidence map›Paper›PMID 39442537›Full record

ArticleApplied clinical informatics2024

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

Niloofar Latifi, Trent Johnson, Amy M Knight, Laura Prichett, Bahareh Modanloo, Trushar Dungarani, Sammy Zakaria, Amit Pahwa

Abstract readMulticenter Study
In one paragraph

Article in Applied clinical informatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Niloofar LatifiDivision of Hospital Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States.
Trent JohnsonDepartment of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States.
Amy M KnightDivision 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 PrichettDepartment of Pediatrics, Johns Hopkins University Biostatistics, Epidemiology, and Data Management Core, Baltimore, Maryland, United States.
Bahareh ModanlooDepartment of Pediatrics, Johns Hopkins University Biostatistics, Epidemiology, and Data Management Core, Baltimore, Maryland, United States.
Trushar DungaraniCommunity Physicians, Johns Hopkins Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States.
Sammy ZakariaDivision of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States.
Amit PahwaDivision of Hospital Medicine, Department of Medicine and Pediatrics, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTelemetry 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.

objectivesWe 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.

methodsA 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.

resultsCompared with the original BPA, the revised BPA reduced telemetry duration by a mean of 6.7 hours (95% CI: 5.2-9.1 hours,

conclusionOptimizing 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.

Indexed as

Decision Support Systems, ClinicalTelemetryElectronic Health RecordsHumansRetrospective StudiesTime Factors

Identifiers

PMID39442537
PMCPMC11498966

What Socratic holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.