ArticleTrials2021
The effect of automated audit and feedback on data completeness in the electronic health record of the general physician: protocol for a cluster randomized controlled trial.
Article in Trials, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04388228 (Audit and Feedback for General Practitioners in the Intego Network), which is not on this map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Audit and Feedback for General Practitioners in the Intego Network
Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- From quality indicator to quality measurement: design and implementation of an automated audit and feedback tool for chronic kidney disease in Belgian primary care.BMJ health & care informatics · 2026Article
- Enhancing Data Completeness in Early Detection Pathway of Prostate Cancer: Integration of a Dashboard-Driven Feedback Tool to Improve Quality of Care.Journal of clinical medicine · 2024Article
- The Impact of the COVID-19 Pandemic on the Registration and Care Provision of Mental Health Problems in General Practice: Registry-Based Study.JMIR public health and surveillance · 2023Article
- Article
- The impact of the Covid-19 pandemic on the incidence of diseases and the provision of primary care: A registry-based study.PloS one · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe electronic health record (EHR) of the general physician (GP) is an important tool that can be used to assess and improve the quality of healthcare. However, there are some problems when (re) using the data gathered in the EHR for quality assessments. One problem is the lack of data completeness in the EHR. Audit and feedback (A&F) is a well-known quality intervention that can improve the quality of healthcare. We hypothesize that an automated A&F intervention can be adapted to improve the data completeness of the EHR of the GP, more specifically, the number of correctly registered diagnoses of type 2 diabetes and chronic kidney disease.
methodsThis study is a pragmatic cluster randomized controlled trial with an intervention at the level of GP practice. The intervention consists of an audit and extended electronically delivered feedback with multiple components that will be delivered 4 times electronically to general practices over 12 months. The data will be analyzed on an aggregated level (per GP practice). The primary outcome is the percentage of correctly registered diagnoses of type 2 diabetes. The key secondary outcome is the registration of chronic kidney disease. Exploratory secondary outcomes are the registration of heart failure, biometric data and lifestyle habits, and the evolution of 4 different EHR-extractable quality indicators. DISCUSSION: This cluster randomized controlled trial intends to primarily improve the registration of type 2 diabetes in the EHR of the GP and to secondarily improve the registration of chronic kidney disease. In addition, the registration of heart failure, lifestyle parameters, and biometric data in the EHR of the GP are explored together with 4 EHR-extractable quality indicators. By doing so, this study aims to improve the data completeness of the EHR, paving the way for future quality assessments.
trial registrationClinicalTrials.gov NCT04388228 . Registered on May 14, 2020.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.