JMIR Publications

ABSTRACT

Background:

Health care delivery organizations lack evidence-based strategies for using quality measurement data to improve performance. Audit and feedback (A&F), the delivery of clinical performance summaries to providers, demonstrates potential for large effects on clinical practice, but is currently implemented as a blunt, “one size fits most” intervention. Each provider in a care setting typically receives their performance summary about identical metrics in a common format, despite a growing recognition that “precisionizing” interventions holds significant promise to improve their impact. A precision approach to A&F would prioritize display of information in the single metric that, for each recipient, carries the highest value for improving performance, such as when the metric’s level drops below a peer benchmark or minimum standard for the first time, revealing an actionable performance gap. Furthermore, precision A&F would employ an optimal message format (including framing and visual displays), based on what is known about the recipient and the intended gist meaning being communicated, to improve message interpretation while reducing cognitive processing burden. Well-established psychological principles, frameworks, and theories form a knowledge base to achieve precision A&F. From an informatics perspective, precision A&F requires a knowledge-based system that enables mass customization by representing knowledge that is configurable at the group and individual levels.

Objective:

We aim to implement and evaluate a demonstration system for precision A&F in anesthesia care, and to assess the effect of precision feedback emails on care quality and outcomes in a national quality improvement consortium.

Methods:

We propose to achieve our aims by conducting three studies: 1) a requirements analysis and preferences elicitation study using human-centered design and conjoint analysis methods, 2) a software service development and implementation study, and 3) a cluster-randomized controlled trial of a precision audit and feedback service with a concurrent process evaluation. This study will be conducted with the Multicenter Perioperative Outcomes Group (MPOG), a national anesthesia quality improvement consortium with more than 60 member hospitals in more than 20 US states. This study will extend the MPOG quality improvement infrastructure, using existing data and performance measurement processes.

Results:

The proposal was funded in September, 2021 with a 4-year timeline. We plan for a 24 month trial timeline.

Conclusions:

The proposed aims will collectively demonstrate a precision feedback service developed using an open-source technical infrastructure for computable knowledge management. By implementing systems for deploying computable knowledge at large scale, we create the potential to observe system-level learning about the conditions under which feedback interventions are effective.