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

NIH RePORTER · AHRQ · R18 · $601,412 · view on reporter.nih.gov ↗

Abstract

Project Summary/Abstract Despite the recognition that diagnostic errors and delays are a major contributor to preventable deaths in the USA, little progress has been made to reduce mortality outcomes from this known killer. Although there is a considerable body of literature outlining contributing causes, an effective strategy leading to a meaningful reduction in diagnostic error and delay rates has not made its way into practice. This has, at least in part, been due to ineffective implementation that has focused on the healthcare team's role and has failed to incorporate the complexity of the organizational and systems processes within the clinical environment. This proposal is unique and novel and combines mixed-methods research approaches with systems engineering research approaches to understand the interplay of the multiple factors contributing to diagnostic error and delay. The knowledge gained from this holistic approach will then be used within the learning laboratory to inform the design, development, evaluation, and refinement of the solutions to diagnostic error and delay. “Control Tower” will be the staging ground for the in situ learning laboratory and will be built on top of a well-established clinical informatics infrastructure and hospital environment open to innovation and practice change. Specifically, using this innovative approach we will evaluate the effectiveness of learning laboratory interventions on the rate of diagnostic error and delay in patients with emerging critical illness. The interventions developed through “Control Tower” have the potential to be shared with multiple practices and adapted to a variety of clinical environments.

Key facts

NIH application ID
10216339
Project number
5R18HS026609-04
Recipient
MAYO CLINIC ROCHESTER
Principal Investigator
Brian W Pickering
Activity code
R18
Funding institute
AHRQ
Fiscal year
2021
Award amount
$601,412
Award type
5
Project period
2018-09-30 → 2022-11-30