Evidence map›Paper›PMID 36589162›Full record

ArticleFrontiers in pediatrics2022

Effect of clinical decision support systems on emergency medicine physicians' decision-making: A pilot scenario-based simulation study.

Azadeh Assadi, Peter C Laussen, Gabrielle Freire, Marzyeh Ghassemi, Patricia C Trbovich

Abstract read
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Article in Frontiers in pediatrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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

5 authors.

Azadeh AssadiLabatt Family Heart Centre, Department of Critical Care Medicine, Hospital for Sick Children, Toronto, ON, Canada.
Peter C LaussenInstitute of Medical Sciences, University of Toronto, Toronto, ON, Canada.
Gabrielle FreireDivision of Emergency Medicine, Department of Pediatrics, University of Toronto, Toronto, ON, Canada.
Marzyeh GhassemiElectrical Engineering and Computer Science, Massachusetts Institute of Technology, Boston, MA, United States.
Patricia C TrbovichHumanEra, Institute of Biomaterials and Biomedical Engineering, Department of Engineering and Applied Sciences, University of Toronto, Toronto, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and objectives: Children with congenital heart disease (CHD) are predisposed to rapid deterioration in the face of common childhood illnesses. When they present to their local emergency departments (ED) with acute illness, rapid and accurate diagnosis and treatment is crucial to recovery and survival. Previous studies have shown that ED physicians are uncomfortable caring for patients with CHD and there is a lack of actionable guidance to aid in their decision making. To support ED physicians' key decision components (sensemaking, anticipation, and managing complexity) when managing CHD patients, a Clinical Decision Support System (CDSS) was previously designed. This pilot study evaluates the effect of this CDSS on ED physicians' decision making compared to usual care without clinical decision support. Methods: In a pilot scenario-based simulation study with repeated measures, ED physicians managed mock CHD patients with and without the CDSS. We compared ED physicians' CHD-specific and general decision-making processes (e.g., recognizing sepsis, starting antibiotics, and managing symptoms) with and without the use of CDSS. The frequency of participants' utterances related to each key decision components of Results: Across all decision-making components, the CDSS significantly increased ED physicians' frequency of "CHD specific utterances" (Mean = 5.43, 95%CI: 3.7-7.2) compared to the without CDSS condition (Mean = 2.05, 95%CI: 0.3-3.8) whereas there was no significant difference in frequencies of "general utterances" when using CDSS (Mean = 4.62, 95%CI: 3.1-6.1) compared to without CDSS (Mean = 5.14 95%CI: 4.4-5.9). Conclusion: A CDSS that integrates key decision-making components (sensemaking, anticipation, and managing complexity) can trigger and enrich communication between clinicians and enhance the clinical management of CHD patients. For patients with complex and subspecialized diseases such as CHD, a well-designed CDSS can become part of a multifaceted solution that includes knowledge translation, broader communication around interpretation of information, and access to additional expertise to support CHD specific decision-making.

Indexed as

clinical decision support (CDSS)congenital heart diseasedecision makingdigital healthemergency medicinemacrocognitionpediatric

Identifiers

PMID36589162
PMCPMC9798305

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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.