Evidence map›Paper›PMID 38876466›Full record

ArticleApplied clinical informatics2024

A Discount Approach to Reducing Nursing Alert Burden.

Sarah A Thompson, Swaminathan Kandaswamy, Evan Orenstein

Abstract read
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. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Sarah A ThompsonInformation Services and Technology, Children's Healthcare of Atlanta, Atlanta, Georgia, United States.
Swaminathan KandaswamyDepartment of Pediatrics, Emory University School of Medicine, Atlanta, Georgia, United States.
Evan OrensteinInformation Services and Technology, Children's Healthcare of Atlanta, Atlanta, Georgia, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNumerous programs have arisen to address interruptive clinical decision support (CDS) with the goals of reducing alert burden and alert fatigue. These programs often have standing committees with broad stakeholder representation, significant governance efforts, and substantial analyst hours to achieve reductions in alert burden which can be difficult for hospital systems to replicate.

objectiveThis study aimed to reduce nursing alert burden with a primary nurse informaticist and small support team through a quality-improvement approach focusing on high-volume alerts.

methodsTarget alerts were identified from the period of January 2022 to April 2022 and four of the highest firing alerts were chosen initially, which accounted for 43% of all interruptive nursing alerts and an estimated 86 hours per month of time across all nurses occupied resolving these alerts per month. Work was done concurrently for each alert with design changes based on the Five Rights of CDS and following a quality-improvement framework. Priority for work was based on operational engagement for design review and approval. Once initial design changes were approved, alerts were taken for in situ usability testing and additional changes were made as needed. Final designs were presented to stakeholders for approval prior to implementation.

resultsThe total number of interruptive nursing alert firings decreased by 58% from preintervention period (1 January 2022-30 June 2022) to postintervention period (July 1, 2022-December 31, 2022). Action taken on alerts increased from 8.1 to 17.3%. The estimated time spent resolving interruptive alerts summed across all nurses in the system decreased from 197 hours/month to 114 hours/month.

conclusionWhile CDS may improve use of evidence-based practices, implementation without a clear framework for evaluation and monitoring often results in alert burden and fatigue without clear benefits. An alert burden reduction effort spearheaded by a single empowered nurse informaticist efficiently reduced nursing alert burden substantially.

Indexed as

Decision Support Systems, ClinicalHumansNurses

Identifiers

PMID38876466
PMCPMC11374459

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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.