U.S. flag

An official website of the Department of Health and Human Services

SHARE:

FacebookXEmail AHRQPrintShare

Acute Care Learning Laboratory—Reducing Threats to Diagnostic Fidelity in Critical Illness

Principal Investigator: Brian Pickering, M.B., B.Ch., M.Sc., Mayo Clinic, Rochester, MN
AHRQ Grant No.: HS26609
Project Period: 09/30/18-11/30/22

Description: The overall goal of this learning lab was to reduce the rate of diagnostic error or delay (DEOD) in acutely ill patients by establishing and using an in situ acute-hospital learning lab.1-2 Researchers engaged key stakeholders to identify threats to the diagnostic process and guide the design, development, testing, implementation, and evaluation of interventions targeting system vulnerabilities.

The specific aims were to:

  1. Develop and validate automated phenotypes of DEOD that can be applied in near-real time to medical record data.
  2. Engage stakeholders using mixed methods and systems engineering approaches to identify factors that contribute to DEOD, then design and develop applicable system-based interventions.
  3. Evaluate the feasibility and preliminary effectiveness of learning lab interventions on the rate of DEOD in patients with emerging critical illness.

This PSLL developed a unique clinical informatics platform, Acute Care Multi-Patient Platform (Control Tower/AMP), that enables health information technology (IT) innovations to be developed with stakeholder input and implemented within the hospital. The resulting applications are built and supported locally, using agile methodologies and user-centered design principles.3

A pilot study was conducted to determine if the Control Tower/AMP could reduce the time to clinical decision of 10 pairs of clinicians caring for acutely ill patients. Results showed that it significantly reduced the time to clinical task completion and clinician task load compared with the standard electronic medical record (EMR). While the Control Tower/AMP is not available for use by other organizations/institutions, it may be in the future.

Additional research is needed to determine clinicians’ performance while using the Control Tower/AMP in the “live” intensive care unit (ICU) setting. But this project highlights the complex sociotechnical system within which individual clinicians operate and the contributions of systems, processes, and institutional factors to DEOD. Researchers conducted 10 studies, with some of the findings3-6 showing that:

  • Twenty percent of patients were considered to have experienced DEOD as a primary contributor to the deterioration event. A similar percentage (20%) could have benefited from earlier engagement of a specialist in diagnostic evaluation and treatment planning.
  • Four types of factors interact in complex ways to impede diagnostic performance:
    • Organizational (e.g., infrastructure, workload, tools, processes).
    • Interactional (e.g., communication, coordination, roles, power).
    • Individual clinician (e.g., bias, experience, ego).
    • Individual patient (e.g., health literacy, medical complexity, acuity of illness).
  • ICU operational conditions may contribute to cognitive overload and affect clinical decision making. ICU operational factors, such as admission rates and patient severity of illness, may affect the critical care team’s cognitive function and result in changes in the production of medication orders.
  • EMR manual review is of limited reliability in the real-time identification of DEOD in hospitalized patients.
  • Health IT for early detection of patient deterioration in acute care settings was not significantly associated with improved mortality or length of stay in a meta-analysis of randomized controlled trials.

The lab is collaborating with institutional clinical, administrative, and technology leadership to further develop AMP as a resource for the real-time identification of patient vulnerability to physiologic deterioration resulting from DEOD. Taking advantage of institutional data resources, real-time data processing capabilities, and patient clinical data, the laboratory is testing novel approaches to the detection of diagnostic error within the context of a complex social-technical system.

As it prepares for pilot testing, the lab plans to apply for funding to evaluate the preliminary effectiveness of AMP to positively affect the diagnostic performance of rapid response systems that have access to AMP interventions in clinical practice. The lab is ideally placed to capture lessons learned from the resulting work system reorganization before, during, and after implementation.

To date, this PSLL’s work has resulted in more than 20 peer-reviewed journal publications related to diagnostic error (selected articles presented below), with more than 300 citations in other publications. The work has directly contributed to the team’s increased understanding of the role technology can play in the identification of patients vulnerable to diagnostic error and informed proposals that have been funded by the institution to improve patient care.

Publications

2023

2022

2021

2020

2019

2018

References

  1. AFYA, PSLL Learning Network Webinar #12 Report. [Internal Communication]: AHRQ; 2020.
  2. Pickering BW. Research Plan: Acute Care Learning Laboratory - Reducing Threats to Diagnostic Fidelity in Critical Illness. Rochester, MN: Mayo Clinic; 2018.
  3. Pickering B. Final Report: Acute Care Learning Laboratory - Reducing Threats to Diagnostic Fidelity in Critical Illness. AHRQ, ed. Rochester, MN: Mayo Clinic; 2023.
  4. Soleimani J, et al. Feasibility and reliability testing of manual electronic health record reviews as a tool for timely identification of diagnostic error in patients at risk. Appl Clin Inform 2020;11(3):474-82.
  5. Redmond S, et al. Contributors to diagnostic error or delay in the acute care setting: a survey of clinical stakeholders. Health Serv Insights 2022;15:11786329221123540.
  6. Park J, et al. Investigating the cognitive capacity constraints of an ICU care team using a systems engineering approach. BMC Anesthesiol 2022;22(1):10.

 

Page last reviewed February 2024
Page originally created January 2024

Internet Citation: Acute Care Learning Laboratory—Reducing Threats to Diagnostic Fidelity in Critical Illness. Content last reviewed February 2024. Agency for Healthcare Research and Quality, Rockville, MD.
https://www.ahrq.gov/patient-safety/resources/learning-lab/acute-care-threats-long-desc.html

Click to copy citation