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Improving Diagnosis in Emergency and Acute Care: A Learning Laboratory (IDEA-LL)

Principal Investigator: Prashant Mahajan, M.D., M.P.H., M.B.A., University of Michigan, Ann Arbor, MI
Co-PIs: Kalyan Pasupathy, Ph.D., University of Illinois, Chicago, IL; Hardeep Singh, M.D., M.P.H., Department of Veterans Affairs, Houston, TX
AHRQ Grant No.: HS26622
Project Period: 09/30/18-07/31/24
Description: This learning lab sought to reduce diagnostic errors in emergency departments (EDs) by examining diagnostic decision making, identifying contributing risk factors, and developing codesigned interventions to enhance diagnostic safety for both adult and pediatric populations. Through a transdisciplinary team of clinicians, engineers, human factors experts, informaticians, and patient advisors, IDEA-LL applied a systems-level lens to identify breakdowns in the diagnostic process and implement sociotechnical solutions across four academic and community EDs.

The specific aims were to:

  1. Map diagnostic decision-making processes in the ED and identify contributing patient-, provider-, and system-level factors using mixed methods, including interviews, observations, and electronic health record (EHR) data mining.
  2. Engage stakeholders in codesign of multilevel interventions to reduce diagnostic risks using participatory design methods.
  3. Test and evaluate diagnostic safety interventions using mixed-methods approaches in real-world ED settings.

To address Aim 1, the research team generated a detailed understanding of how diagnostic decisions unfold in real-world ED settings by combining interviews, ethnographic observation, and EHR analysis. Using grounded theory and mixed-methods case study protocols, they mapped cognitive and contextual contributors to diagnostic breakdowns.1 Through interviews with frontline clinicians and patients, the team identified five key areas of vulnerability: team communication, information gathering, ED workflows and organization, patient understanding and followup, and challenges in using the EHR and patient portals to support accurate diagnosis.2

Machine learning models applied to EHR datasets and trigger-based chart reviews revealed that diagnostic safety risks were influenced by factors such as ED crowding, patient complexity, time pressures, and clinician workload.3 This computational work enabled the development of early-stage diagnostic risk surveillance mechanisms. These diverse data streams produced a robust, multilayered understanding of diagnostic risk in academic and community EDs serving both adult and pediatric populations.

Aim 1 Manuscripts

For Aim 2, the team codesigned a series of multilevel interventions through participatory design sessions with ED clinicians and patients.7 These sessions led to the development of novel sociotechnical prototypes that addressed the cognitive, procedural, and organizational challenges identified in Aim 1. Intervention concepts included:

  • Clinician-facing dashboards that visually displayed diagnostic risk signals.
  • Patient-centered education and engagement tools to improve understanding of diagnostic plans and followup steps.
  • Workflow improvements and communication support tools for multidisciplinary ED teams.

These prototypes reflected human-centered, real-world priorities, and were designed with a clear path to testing and future implementation. The interventions addressed diagnostic safety at three levels—patients, care teams, and health systems—demonstrating the PSLL’s ability to translate complex diagnostic challenges into actionable, user-informed solutions.8,9

Aim 2 Manuscripts

  • Seo W, Jain S, Le V, et al. Designing patient-centered interventions for emergency care: participatory design study. JMIR Form Res 2025 Feb 12;9:e63610.
  • Seo W, Li J, Zhang Z, et al. Designing health care provider-centered emergency department interventions: participatory design study. JMIR Form Res 2025 Apr 21;9:e68891.
  • Seo W, Park SY, Zhang Z, et al. Identifying interventions to improve diagnostic safety in emergency departments: protocol for a participatory design study. JMIR Res Protoc 2024 Jun 21;13:e55357.

Throughout the project, the IDEA-LL team leveraged its unique physician–engineer partnership and broad interdisciplinary expertise to explore diagnostic complexity in the ED. Project findings have informed the broader fields of diagnostic safety, emergency medicine, and systems-based patient safety research. 

To date, this PSLL’s work has resulted in at least 11 peer-reviewed publications, with at least 77 citations in other publications. 

Publications

2025

2024

2021

2020

2019

 

Other Products (Presentations, Posters, and Abstracts)

Aim 1

  • Enayati E, Mahajan P, Bellolio F, et al. Iterative Refinement of Electronic Triggers To Improve the Identification of Diagnostic Errors (oral presentation). Society for Academic Emergency Medicine, Virtual, 2021.
  • Huschka T, Khalili M, Patel S, et al. Investigating Factors Influencing Diagnostic Safety in Emergency Department Patients Using Decision Trees. American College of Emergency Physicians (ACEP), Philadelphia, PA, Oct 2023.
  • Khalili A, Patel S, Huschka T, et al. Data-Driven Strategies To Enhance Identification of Diagnostic Errors in the Emergency Department (poster). Mayo Clinic Quality Conference, Rochester, MN, June 2023.
  • Khalili M, Patel S, Huschka T, et al. Identification of Diagnostic Errors in the Emergency Department Using Data-Driven Strategies. American College of Emergency Physicians (ACEP), Philadelphia, PA, Oct 2023.
  • Mahajan P, Bellolio F, Cabrera D, et al. Electronic Triggers To Identify Potential Diagnostic Errors in Emergency Departments: Feasibility Study Results (poster). Society for Academic Emergency Medicine, Virtual, 2021.
  • Mahajan P, Chandanabhumma PP, Daniel M, et al. Investigating the Emergency Department Diagnostic Process: Insights From Frontline Providers (poster). Society for Academic Emergency Medicine, Virtual, 2021.
  • Mahajan P, Manojlovich M, Cassady C, et al. Investigating Emergency Department Diagnostic Processes: Video Ethnography Methodology Development (poster). Diagnostic Error in Medicine Conference, Minneapolis, MN, Oct 2022.
  • Mangus C, James TG, Parker S, et al. A Qualitative Investigation of Providers’ and Patients’ Perspectives on Potential Interventions To Improve Diagnostic Safety in the Emergency Department. Pediatric Academic Society (PAS), Washington, DC, April 2023.
  • Manojlovich M, Cassady C, Davis E, et al. Investigating Emergency Department Physicians Diagnostic Decision Making by In-situ Video Ethnography. Pediatric Academic Society (PAS), Washington, DC, April 2023.
  • Manojlovich M, Cassady C, Parker S, et al. Using Video Ethnography and Stimulated Recall Interviews To Describe the Diagnostic Process in the Emergency Department (poster). AcademyHealth, Minneapolis, MN, June 2025.
  • Manojlovich M, Cassady C, Parker S, et al. Video-Based Ethnography as a Method To Capture Elements of Distributed Cognition and Promote Diagnostic Safety in the Emergency Department (poster). AcademyHealth, Baltimore, MD, June 2024.
  • Patel S, Khalili M, Huschka T, et al. Mining Electronic Health Records To Identify Key Factors Influencing Diagnostic Errors in the Emergency Department. American College of Emergency Physicians (ACEP), Philadelphia, PA, Oct 2023. 

Aim 2 

  • Mahajan P, Mangus M, Parker S, et al. Co-Designing Interventions To Improve Diagnosis in the Emergency Department. Diagnostic Error in Medicine Conference, Minneapolis, MN, Oct 2022. 

References 

  1. Daniel M, Park S, Seifert CM, et al. Understanding diagnostic processes in emergency departments: a mixed methods case study protocol. BMJ Open 2021 Sep 24;11(9):e044194. 2
  2. Mangus CW, James TG, Parker SJ, et al. Frontline providers’ and patients’ perspectives on improving diagnostic safety in the emergency department: a qualitative study. Jt Comm J Qual Patient Saf 2024;50(7):480-491.
  3. Enayati M, Sir M, Zhang X, et al. Monitoring diagnostic safety risks in emergency departments: protocol for a machine learning study. JMIR Res Protoc 2021 Jun 14;10(6):e24642.
  4. Kapoor A, Enayati M, Chaudhry A, et al. Estimating physical work-load on ED clinicians and staff using real-time location systems. IEEE J Radio Freq ID 2021 Jun 30;5(3):331-334.  
  5. Enayati M, Farahani NZ, Chaudhry AP, et al. Incorporating RTLS-based spatiotemporal information in studying physical activities of clinical staff. Annu Int Conf IEEE Eng Med Biol Soc 2021 Nov;2021:2386-2391.
  6. Michelson KA, Williams DN, Dart AH, et al. Development of a rubric for assessing delayed diagnosis of appendicitis, diabetic ketoacidosis and sepsis. Diagnosis (Berl) 2020 Jun 26;8(2):219-225.
  7. James TG, Mangus CW, Parker SJ, et al. “Everything is electronic health record-driven”: the role of the electronic health record in the emergency department diagnostic process. JAMIA Open 2025 Apr;8(2):ooaf029.
  8. Seo W, Park SY, Zhang Z, et al. Identifying interventions to improve diagnostic safety in emergency departments: protocol for a participatory design study. JMIR Res Protoc 2024 Jun 21;13:e55357.
  9. Seo W, Li J, Zhang Z, et al. Designing health care provider-centered emergency department interventions: participatory design study. JMIR Form Res 2025 Apr 21;9:e68891.
Page last reviewed August 2025
Page originally created August 2025

Internet Citation: Improving Diagnosis in Emergency and Acute Care: A Learning Laboratory (IDEA-LL). Content last reviewed August 2025. Agency for Healthcare Research and Quality, Rockville, MD.
https://www.ahrq.gov/patient-safety/resources/learning-lab/idea-ll-long-desc.html

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