Development and early implementation of automated audit and feedback monitoring instruments in Belgian primary care: lessons for scalable systems

Abstract

Background Electronic health records (EHRs) can potentially revolutionize primary care by enhancing data storage, communication, and quality measure reporting. The COVID-19 pandemic accelerated the adoption of digital tools in Belgium, highlighting the potential of EHR data in audit and feedback (A&F) strategies. This study aims to outline the design and national implementation process of automated A&F monitoring instruments (locally known as barometers), in Belgian primary care.Methods Using Clinical Performance Feedback Intervention Theory, we developed three monitoring instruments for primary care: COVID-19 vaccination coverage, type 2 diabetes management, and appropriate antibiotic use. Quality indicators were selected at the national level using a Rand-modified Delphi method and validated by the Flemish Institute for Quality of Health Care (VIKZ). Data were collected from general practitioners' EHR systems, aggregated at the practice level, and analyzed using the Healthdata.be platform. Feedback was provided through the Healthstat.be interface, incorporating local and regional benchmarks and evidence-based recommendations.Results The COVID-19 vaccination monitoring instrument included 5223 GPs from 2269 practices, the type 2 diabetes monitoring instrument involved 9373 GPs from 3596 practices, and the antibiotics monitoring instrument covered 10 486 GPs from 3724 practices. These monitoring instruments collectively covered approximately eight million patients. Feedback reports were designed to be low in cognitive load, frequent, and benchmarked against the best-performing decile of practices. Integration of active, in-EHR delivery and formal evaluation of use are planned for future phases.Conclusion The implementation of automated A&F instruments in Belgian primary care demonstrated the feasibility and scalability of such systems. These monitoring instruments can provide valuable insights for quality improvement and support the transition toward a Learning Health System. Future work will focus on expanding the range of monitoring instruments and integrating active feedback mechanisms within EHR systems.