Evidence map›Paper›PMID 31197358›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2019

Integration of physical abuse clinical decision support at 2 general emergency departments.

Bruce Rosenthal, Janet Skrbin, Janet Fromkin, Emily Heineman, Tom McGinn, Rudolph Richichi, Rachel P Berger

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 3 pooled it
–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

19 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. The role of information systems in emergency department decision-making-a literature review.Journal of the American Medical Informatics Association : JAMIA · 2024
    Pooled it
  2. Guideline
  3. Pooled it
  4. Article
  5. Article
  6. Observational
  7. Stressful life events in electronic health records: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2024
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Combining text mining with clinical decision support in clinical practice: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2023
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Combatting human trafficking in the United States: how can medical informatics help?Journal of the American Medical Informatics Association : JAMIA · 2021
    Article
  18. Article
  19. Article
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

7 authors.

Bruce RosenthalDepartment of Pediatrics, UPMC Children's Hospital of Pittsburgh of University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.
Janet SkrbinDepartment of Pediatrics, UPMC Children's Hospital of Pittsburgh of University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.
Janet FromkinDepartment of Pediatrics, UPMC Children's Hospital of Pittsburgh of University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.
Emily HeinemanDepartment of Pediatrics, UPMC Children's Hospital of Pittsburgh of University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.
Tom McGinnDepartment of Medicine, Hofstra Northwell School of Medicine, Manhasset, New York, USA.
Rudolph RichichiStatistical Analysis and Measurement Consultants, Lanexa, VA.
Rachel P BergerDepartment of Pediatrics, UPMC Children's Hospital of Pittsburgh of University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.

Funding

Patient-Centered Outcomes Research Institute AD-12-11-4956
6 · The paper itself

Abstract

objectiveThe study sought to develop and evaluate an electronic health record-based child abuse clinical decision support system in 2 general emergency departments. MATERIALS AND

methodsA combination of a child abuse screen, natural language processing, physician orders, and discharge diagnoses were used to identify children <2 years of age with injuries suspicious for physical abuse. Providers received an alert and were referred to a physical abuse order set whenever a child triggered the system. Physician compliance with clinical guidelines was compared before and during the intervention.

resultsA total of 242 children triggered the system, 86 during the preintervention and 156 during the intervention. The number of children identified with suspicious injuries increased 4-fold during the intervention (P < .001). Compliance was 70% (7 of 10) in the preintervention period vs 50% (22 of 44) in the intervention, a change that was not statistically different (P = .55). Fifty-two percent of providers said that receiving the alert changed their clinical decision making. There was no relationship between compliance and provider or patient demographics.

conclusionsA multifaceted child abuse clinical decision support system resulted in a marked increase in the number of young children identified as having injuries suspicious for physical abuse in 2 general emergency departments. Compliance with published guidelines did not change; we hypothesize that this is related to the increased number of children identified with suspicious, but less serious injuries. These injuries were likely missed preintervention. Tracking compliance with guidelines over time will be important to assess whether compliance increases as physician comfort with evaluation of suspected physical abuse in young children improves.

Indexed as

Decision Support Systems, ClinicalElectronic Health RecordsEmergency Service, HospitalChild AbuseData DisplayHumansInfantPennsylvaniaPhysical Abusechild maltreatmentelectronic health recordpediatric

Identifiers

PMID31197358
PMCPMC7647214

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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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.