Privacy-preserving architecture for providing feedback to clinicians on their clinical performance.

ABSTRACT:

Background

Learning from routine healthcare data is important for the improvement of the quality of care. Providing feedback on clinicians' performance in comparison to their peers has been shown to be more efficient for quality improvements. However, the current methods for providing feedback do not fully address the privacy concerns of stakeholders.

Methods

The paper proposes a distributed architecture for providing feedback to clinicians on their clinical performances while protecting their privacy. The indicators for the clinical performance of a clinician are computed within a healthcare institution based on pseudonymized data extracted from the electronic health record (EHR) system. Group-level indicators of clinicians across healthcare institutions are computed using

SUBMITTER: Yigzaw KY 

PROVIDER: S-EPMC7310252 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature