Audit and Feedback for General Practitioners in the Intego Network

Summary

Participation Requirements

Description

Intego is a Belgian general practice-based morbidity registration network at the Department of General Practice of the University of Leuven. Intego collects data on health parameters, incidence and prevalence rates, laboratory results, and prescribed drugs for all relevant subgroups. It is unique in...

Intego is a Belgian general practice-based morbidity registration network at the Department of General Practice of the University of Leuven. Intego collects data on health parameters, incidence and prevalence rates, laboratory results, and prescribed drugs for all relevant subgroups. It is unique in Belgium. These data are used as a basis for teaching, quality improvement interventions, and research, as well as for policy making by both physicians' organizations and governmental bodies. The health ministry of the Flemish government mainly funds the network. Ad hoc research projects serve as an additional funding source. Up until 2017, 97 general practitioners (GP's) of 55 practices evenly spread throughout Flanders, Belgium, collaborated in Intego. GP's applied for inclusion in the registry. Before acceptance of their data, registration performance was audited using algorithms to compare their results with those of all other applicants. Only data of practices with optimal registration performance that met our three quality requirements were included in the database. First, the average number of new diagnoses per patient per year should be higher than one. Second, diagnoses have to be entered in the practice software using keywords. The Intego GP's prospectively and routinely registered all new diagnoses and new drug prescriptions, as well as laboratory test results and patient information. The registration made use of computer-generated keywords internally linked to codes [International Classification of Primary Care (ICPC-2) and International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10) for diagnoses and WHO's Anatomical Therapeutic Chemical (ATC) classification system for drugs]. The percentage of diagnoses recorded without using keywords should be less than 5%. Finally, these parameters must remain stable for at least three years. In 2017, Intego made a transition in data infrastructure and size of the network. Further information technology development for the electronic health record (EHR) 'Medidoc' was terminated, and all its users were urged by the vendor to migrate to a new EHR, called CareConnect (Corilus), a cloud-based EHR. This transition marked the moment to redesign the data collection for this registry, which had not changed since its start. To comply with the new General Data Protection Regulation legislation, the Healthdata.be platform was identified as a partner for this task. Moreover, the number of practices was increased and now counts 107 practices (410 GPs). However, new GP practices might not meet the quality requirements for good registration yet. The data completeness of the EHR is thus an important factor to consider when reusing data stored in the EHR. Other pitfalls and sources of bias when using EHR data have also been identified. In order to improve registration, we want to implement extended electronically delivered feedback and evaluate its effects on correctly registering the diagnosis of chronic diseases and lifestyle habits in the EHR. Audit and feedback is an extensively investigated quality intervention, which according to the last Cochrane review leads to small but potentially important improvements in professional practice. There is some evidence that feedback can improve EHR registration but the effect and important features of feedback are still the subject of debate. Previous work has identified some testable and theory-informed hypotheses for designing an audit and feedback intervention and suggestions to improve the effectiveness of the intervention are available in literature. There are several criteria feedback could meet to have an impact on the registration level of GP's in the EHR. We now want to evaluate if the effort to make an extended feedback intervention has an effect on the registration behavior of the GP. The research question is: Does an audit and extended feedback intervention improves the quality of registration in the EHR of the general physician compared to basic feedback?

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