Diagnostic Safety Center for Advancing E-triggers and Rapid Feedback Implementation (DISCOVERI)

NIH RePORTER · AHRQ · R18 · $999,956 · view on reporter.nih.gov ↗

Abstract

Progress in reducing diagnostic errors is slow partly due to poorly defined methods to identify and learn from them. Methods to provide diagnostic safety data to clinicians and leaders can enable them to act upon these data to prevent diagnostic harm. Health care organizations (HCOs) now have an opportunity to explore their increasing stores of electronic health record (EHR) data for learning, research, and quality improvement related to diagnosis. Electronic trigger (e-trigger) tools, which mine vast amounts of clinical and administrative data to identify signals for likely adverse events, offer a promising method to do so. Our work shows e-trigger algorithms can efficiently identify patterns of care suggestive of missed or delayed diagnoses in primary care, emergency care and inpatient settings. Robust review and analysis methods can then uncover safety concerns and provide information on breakdowns related to the diagnostic process, including contributory factors. This information can generate learning and feedback that could be used for improvement by individuals and teams. However, despite their potential use for measurement and improvement of diagnostic safety, e-triggers are still largely confined to research and not yet translated into practice. We thus propose developing the “Diagnostic Safety Center for Advancing E-triggers and Rapid Feedback Implementation (DISCOVERI)” with a goal of implementing surveillance and feedback systems for diagnostic safety in HCOs. Our long-term goal is to accelerate uptake of e-triggers for measurement of diagnostic safety across the US in organizations that value Learning and Exploration of Diagnostic Excellence (LEDE organizations). DISCOVERI will help create generalizable knowledge, tools, strategies and methods for an e-trigger based learning and feedback system for improving diagnostic safety within LEDE organizations. Specific aims are: Aim 1: Create tools, strategies, and methods to implement e-trigger algorithms for diagnostic error surveillance and prevention in LEDE organizations. Aim 2: Develop and evaluate Safety-I and Safety-II related methods for providing clinicians and health care organizations with rapid diagnostic performance feedback. Aim 3: Synthesize implementation experiences to develop a safety surveillance system “Safer Dx e-Watch” to facilitate large-scale implementation efforts in US health systems. We will work with 3 health systems and use multiple qualitative and quantitative methods involving hybrid in- person and virtual participatory approaches. We will define processes for how e-trigger data can be gathered from EHRs and delivered as feedback for learning and improvement to organizational leaders and clinicians. We will leverage our experience in translating research to improve practice and disseminating and implementing interventions. Knowledge and methods generated by DISCOVERI will accelerate implementation of an e-trigger based learning and feedback system to prevent ha...

Key facts

NIH application ID
10918176
Project number
5R18HS029347-03
Recipient
BAYLOR COLLEGE OF MEDICINE
Principal Investigator
HARDEEP SINGH
Activity code
R18
Funding institute
AHRQ
Fiscal year
2024
Award amount
$999,956
Award type
5
Project period
2022-09-30 → 2026-09-29