Evidence map›Paper›PMID 40258269›Full record

ArticleJMIR formative research2025

Designing Health Care Provider-Centered Emergency Department Interventions: Participatory Design Study.

Woosuk Seo, Jiaqi Li, Zhan Zhang, Chuxuan Zheng, Hardeep Singh, Kalyan Pasupathy, Prashant Mahajan, Sun Young Park

Abstract read
In one paragraph

Article in JMIR formative research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Woosuk Seo *School of Information, University of Michigan, Ann Arbor, MI, United States.ORCID 0000-0002-1316-4341
Jiaqi Li *School of Information, University of Michigan, Ann Arbor, MI, United States.ORCID 0000-0003-0758-4101
Zhan ZhangSeidenberg School of Computer Science and Information Systems, Pace University, New York, NY, United States.ORCID 0000-0001-6973-6903
Chuxuan ZhengDepartment of Human Centered Design & Engineering, University of Washington, Seattle, WA, United States.ORCID 0009-0006-8887-8927
Hardeep SinghCenter for Innovations in Quality, Effectiveness and Safety (IQuESt), Michael E. DeBakey Veterans Affairs Medical Center and Baylor College of Medicine, Houston, TX, United States.ORCID 0000-0002-4419-8974
Kalyan PasupathyBiomedical and Health Information Sciences, University of Illinois Chicago, Chicago, IL, United States.ORCID 0000-0002-4760-2805
Prashant MahajanDepartment of Emergency Medicine, University of Michigan Medical School, Ann Arbor, MI, United States.ORCID 0000-0003-4278-3560
Sun Young ParkSchool of Information, Stamps School of Art and Design, University of Michigan, Ann Arbor, MI, United States.ORCID 0000-0001-8666-1800

Funding

AHRQ HHS R01 HS028595AHRQ HHS R01 HS029318AHRQ HHS R18 HS026622AHRQ HHS R18 HS029347HSRD VA CIN 13-410
6 · The paper itself

Abstract

backgroundIn the emergency department (ED), health care providers face extraordinary pressures in delivering accurate diagnoses and care, often working with fragmented or inaccessible patient histories while managing severe time constraints and constant interruptions. These challenges and pressures may lead to potential errors in the ED diagnostic process and risks to patient safety. With advances in technology, interventions have been developed to support ED providers in such pressured settings. However, these interventions may not align with the current practices of ED providers. To better design ED provider-centered interventions, identifying their needs in the diagnostic process is critical.

objectiveThis study aimed to identify ED providers' needs in the diagnostic process through participatory design sessions and to propose design guidelines for provider‑centered technological interventions that support decision‑making and reduce errors.

methodsWe conducted a participatory design study with ED providers to validate their needs and identify considerations for designing ED provider-centered interventions to improve diagnostic safety. We used 9 technological intervention ideas as storyboards to address the study participants' needs. We had participants discuss the use cases of each intervention idea to assess their needs during the ED care process and facilitated co-design activities with the participants to improve the technological intervention designs. We audio- and video-recorded the design sessions. We then analyzed session transcripts, field notes, and design sketches. In total, we conducted 6 design sessions with 17 ED frontline providers.

resultsThrough design sessions with ED providers, we identified 4 key needs in the diagnostic process: information integration, patient prioritization, ED provider-patient communication, and care coordination. We interpreted them as insights for designing technological interventions for ED patients. Hence, we discussed the design implications for technological interventions in four key areas: (1) enhancing ED provider-ED provider communication, (2) enhancing ED provider-patient communication, (3) optimizing the integration of advanced technology, and (4) unleashing the potential of artificial intelligence tools in the ED to improve diagnosis. This work offers evidence-based technology design suggestions for improving diagnostic processes.

conclusionsThis study provides unique insights for designing technological interventions to support ED diagnostic processes. By inviting ED providers into the design process, we present unique insights into the diagnostic process and design considerations for designing novel technological interventions that meet ED providers' needs in the diagnostic process. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/55357.

Indexed as

Emergency Service, HospitalHealth PersonnelFemaleHumansMalePatient-Centered Careartificial intelligenceemergency departmentshealth care providersinterventionsparticipatory designtechnology

Identifiers

PMID40258269
PMCPMC12053276

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.