Evidence map›Paper›PMID 40123719›Full record

ArticleAEM education and training2025

Design and implementation of an automated patient-care dashboard to provide individualized patient care data and quality metrics to emergency medicine residents.

Danielle T Miller, Sean S Michael, Sarah H Michael, Kelly Bookman, Cody Brevik, William Dewispelaere, Christopher Johns, Bonnie Kaplan, Dong Nguyen, Daniel Owens and 2 more

Abstract read
In one paragraph

Article in AEM education and training, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

12 authors.

Danielle T MillerDepartment of Emergency Medicine University of Colorado School of Medicine Aurora Colorado USA.ORCID https://orcid.org/0000-0003-3933-2355
Sean S MichaelDepartment of Emergency Medicine University of Colorado School of Medicine Aurora Colorado USA.ORCID https://orcid.org/0000-0001-7496-8389
Sarah H MichaelDepartment of Emergency Medicine University of Colorado School of Medicine Aurora Colorado USA.
Kelly BookmanDepartment of Emergency Medicine University of Colorado School of Medicine Aurora Colorado USA.
Cody BrevikDepartment of Emergency Medicine University of Colorado School of Medicine Aurora Colorado USA.ORCID https://orcid.org/0000-0002-8048-4708
William DewispelaereDepartment of Emergency Medicine University of Colorado School of Medicine and Denver Health Medical Center Aurora Colorado USA.ORCID https://orcid.org/0009-0002-2609-6373
Christopher JohnsDepartment of Emergency Medicine University of Colorado School of Medicine and Denver Health Medical Center Aurora Colorado USA.
Bonnie KaplanDepartment of Emergency Medicine University of Colorado School of Medicine Aurora Colorado USA.
Dong NguyenAcute Care and Business Analytics Team CU Anschutz Aurora Colorado USA.
Daniel OwensDepartment of Emergency Medicine Virginia Commonwealth University Richmond Virginia USA.
Gannon SungarDepartment of Emergency Medicine University of Colorado School of Medicine Aurora Colorado USA.
John KendallDepartment of Emergency Medicine Stanford School of Medicine Palo Alto California USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The emergency department (ED) is a high-stakes training environment for emergency medicine (EM) residents and residents' ability to reflect and self-evaluate patient care is of critical importance. Patient care dashboards have been shown to increase adherence to quality guidelines and improve patient outcomes. The objectives of this study were: (1) to create a comprehensive list of evidence-based, psychologically safe patient care and quality metrics to include in a patient care dashboard for EM residents; (2) to design an EM patient care residency dashboard in a secure, cloud-based environment integrated with the electronic health record (EHR); and (3) to pilot the usability and acceptability of the dashboard among EM residents. Methods: We created a list of potential EM resident patient care metrics using ACGME Emergency Medicine Defined Key Index Procedure Minimums, leading EM quality indicators, and current EM dashboard literature. We surveyed PGY-1 to -4 EM residents at a single residency program for their recommendations about inclusion, exclusion, and the psychological safety of each metric. We then developed a dashboard utilizing Power BI software integrated with Epic EHR. After development, we conducted a 2-month pilot evaluation for usability and acceptability among EM residents utilizing a mixed-methods approach. Results: We identified 41 metrics within five domains (productivity metrics, patient safety and leading quality indicators, key procedures, complex/high-acuity cases, and uncertain diagnosis) to consider for inclusion in the dashboard. Residents ( Conclusions: Our dashboard provides individualized patient care data to EM residents related to productivity, patient safety and quality, key procedures, complex/high-acuity cases, and uncertain diagnoses. A pilot group of EM residents found the dashboard acceptable and useable. Continued research is needed to explore ideal implementation and integration of patient care dashboards in residency training.

Identifiers

PMID40123719
PMCPMC11924277

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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.