Development of an Ethico-Legal Framework for Quality Improvement and Performance Management in Health Care: Protocol...

The growing digitization of health data has expanded opportunities for professional learning and performance improvement. While they provide new means for improving the quality and safety of health care, these new capabilities for data analysis and performance monitoring come with risks and may exacerbate existing ethico-legal concerns about fairness, accountability, privacy, and more.

This study aims to develop an ethico-legal framework for the evaluation of professional performance that is cognizant of these concerns and addresses the needs of relevant stakeholders. The study will assess the acceptability, comprehensiveness, and potential utility of the framework from the perspective of end users and subject matter experts.

This study will use existing evidence on ethico-legal considerations surrounding secondary uses of health data for performance improvement and management to draft the framework. We will conduct 2 focus groups with end users (eg, health professionals and administrators) and subject matter experts (eg, clinical ethicists and legal practitioners). These focus groups will ask participants to reflect on the framework's structure and comprehension, intended audience, comprehensiveness and relevance regarding ethical and legal principles, limitations, and utility and acceptability as a step-by-step guide. Study participants may also opt for one-on-one interviews for any reason. This feedback will be thematically analyzed using open coding and verified by an independent reviewer at the focus groups, followed by constant comparisons of feedback from this study to concepts and interrelationships in data previously collected.

Recruitment for this study is scheduled from August to December 2025. The analysis, compilation, and dissemination of higher-order themes, concepts, and outcomes is planned for after publication of this protocol, after each interview or focus group has been transcribed and coded line by line.

This study seeks to create an actionable tool that is readily translatable to clinical practice in collaboration with end users and subject matter experts. The proposed methodology is a low-resource coapproach that could be iteratively refined to ensure that the proposed framework continues to support robust and efficient use of performance data while respecting the different contexts in which practice analytics may be delivered. This systematic approach to principle-led evaluation of performance and conduct could inform technology-neutral governance capable of addressing perennial concerns about fairness, privacy, and transparency when using health data for professional learning and performance management.