Evidence map›Paper›PMID 38551639›Full record

ArticleJournal of medical Internet research2024

Developing and Testing the Usability of a Novel Child Abuse Clinical Decision Support System: Mixed Methods Study.

Amy Thomas, Andrea Asnes, Kyle Libby, Allen Hsiao, Gunjan Tiyyagura

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
4.4field-weighted citation impact, top 7% of its field
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, 4 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Amy ThomasDepartment of Pediatrics, Yale University School of Medicine, New Haven, CT, United States.ORCID 0000-0002-8704-7797
Andrea AsnesDepartment of Pediatrics, Yale University School of Medicine, New Haven, CT, United States.ORCID 0000-0002-6769-5252
Kyle Libby3M | M*Modal, 3M Health Information Systems, 3M Company, Maplewood, MN, United States.ORCID 0009-0009-4835-8988
Allen HsiaoDepartment of Pediatrics, Yale University School of Medicine, New Haven, CT, United States.ORCID 0000-0002-8080-0002
Gunjan TiyyaguraDepartment of Pediatrics, Yale University School of Medicine, New Haven, CT, United States.ORCID 0000-0003-0342-0919
Yale University · US3M (United States) · US

Funding

Short-Term Reserch Training: Students in Health SchoolsT35HL007649 · NHLBI · YALE UNIVERSITY · PI Sarwat I Chaudhry, Erica L Herzog · 1987 to 2026
$5.7M
A Family Centered Approach to Intimate Partner ViolenceK23HD107178 · NICHD · YALE UNIVERSITY · PI TIYYAGURA, GUNJAN · 2022 to 2025
$664k
NHLBI NIH HHS T35 HL007649NICHD NIH HHS K23 HD107178
6 · The paper itself

Abstract

backgroundDespite the impact of physical abuse on children, it is often underdiagnosed, especially among children evaluated in emergency departments (EDs). Electronic clinical decision support (CDS) can improve the recognition of child physical abuse.

objectiveWe aimed to develop and test the usability of a natural language processing-based child abuse CDS system, known as the Child Abuse Clinical Decision Support (CA-CDS), to alert ED clinicians about high-risk injuries suggestive of abuse in infants' charts.

methodsInformed by available evidence, a multidisciplinary team, including an expert in user design, developed the CA-CDS prototype that provided evidence-based recommendations for the evaluation and management of suspected child abuse when triggered by documentation of a high-risk injury. Content was customized for medical versus nursing providers and initial versus subsequent exposure to the alert. To assess the usability of and refine the CA-CDS, we interviewed 24 clinicians from 4 EDs about their interactions with the prototype. Interview transcripts were coded and analyzed using conventional content analysis.

resultsOverall, 5 main categories of themes emerged from the study. CA-CDS benefits included providing an extra layer of protection, providing evidence-based recommendations, and alerting the entire clinical ED team. The user-centered, workflow-compatible design included soft-stop alert configuration, editable and automatic documentation, and attention-grabbing formatting. Recommendations for improvement included consolidating content, clearer design elements, and adding a hyperlink with additional resources. Barriers to future implementation included alert fatigue, hesitancy to change, and concerns regarding documentation. Facilitators of future implementation included stakeholder buy-in, provider education, and sharing the test characteristics. On the basis of user feedback, iterative modifications were made to the prototype.

conclusionsWith its user-centered design and evidence-based content, the CA-CDS can aid providers in the real-time recognition and evaluation of infant physical abuse and has the potential to reduce the number of missed cases.

Indexed as

Child AbuseDecision Support Systems, ClinicalChildElectronic Health RecordsEthnicityHumansInfantMinority GroupsCDSchildchild abusechildrenclinical decision supportclinical decision support systemnatural language processingpediatricsphysical abuseusability

Identifiers

PMID38551639
PMCPMC11015363
OpenAlexW4392839219

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.