Evidence map›Paper›PMID 40179954›Full record

ArticleApplied clinical informatics2025

The Burden of a Highly Targeted Alert.

Tatyan Clarke, Tyler Kotarski, Marc Tobias

Abstract read
In one paragraph

Article in Applied clinical informatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

3 authors.

Tatyan ClarkeDepartment of Surgery, Temple University Health System, Philadelphia, Pennsylvania, United States.
Tyler KotarskiPhrase Health, Inc., Philadelphia, Pennsylvania, United States.
Marc TobiasPhrase Health, Inc., Philadelphia, Pennsylvania, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Interruptive alerts in clinical decision support (CDS) systems are intended to guide clinicians in making informed decisions and adhering to best practices. However, these alerts can often become a source of frustration, contributing to alert fatigue and clinician burnout. Traditionally, an alert's burden is often assessed by evaluating the total number of times it is seen by end-users, which can overlook the true impact of highly interruptive workflows. This study demonstrates how an alert burden metric was employed to pinpoint an ineffective and burdensome alert, ultimately leading to its deactivation.This study aimed to evaluate the effectiveness of a burden metric in identifying high-impact, low-value alerts and prioritizing improvement efforts for a CDS governance team.A clinical informatics team employed Phrase Health's "Phrase Burden Index" (PBI) to assess alert burden and identify areas requiring intervention within the alert library.The team used the PBI to identify a breast cancer survivorship alert that fired 3,550 times in 2023, with the desired alert action chosen in only 0.00056% of alert firings. An investigation identified that this alert targeted a single clinician over the span of several years, and the CDS governance team promptly decommissioned the alert.This case highlights the value of continuous CDS monitoring, effective governance, and advanced analytics to identify and mitigate alert fatigue. Insights from this failure provide guidance for enhancing future CDS design, evaluation, and clinician engagement.

Indexed as

Decision Support Systems, ClinicalBreast NeoplasmsHumans

Identifiers

PMID40179954
PMCPMC12310297

What OpenQuestion holds

Textmetadata
Read underepoch 390

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 OpenQuestion graph.