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

BACKGROUND: The 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 c...

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Autores principales: Van den Bulck, Steve, De Burghgraeve, Tine, Raat, Willem, Mamouris, Pavlos, Coursier, Patrick, Vankrunkelsven, Patrik, Goderis, Geert, Hermens, Rosella, Van Pottelbergh, Gijs, Vaes, Bert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Study Protocol
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8097814/
https://www.ncbi.nlm.nih.gov/pubmed/33947448
http://dx.doi.org/10.1186/s13063-021-05259-9
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author Van den Bulck, Steve
De Burghgraeve, Tine
Raat, Willem
Mamouris, Pavlos
Coursier, Patrick
Vankrunkelsven, Patrik
Goderis, Geert
Hermens, Rosella
Van Pottelbergh, Gijs
Vaes, Bert
author_facet Van den Bulck, Steve
De Burghgraeve, Tine
Raat, Willem
Mamouris, Pavlos
Coursier, Patrick
Vankrunkelsven, Patrik
Goderis, Geert
Hermens, Rosella
Van Pottelbergh, Gijs
Vaes, Bert
author_sort Van den Bulck, Steve
collection PubMed
description BACKGROUND: The 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. METHODS: This 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 REGISTRATION: ClinicalTrials.gov NCT04388228. Registered on May 14, 2020. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13063-021-05259-9.
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spelling pubmed-80978142021-05-05 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 Van den Bulck, Steve De Burghgraeve, Tine Raat, Willem Mamouris, Pavlos Coursier, Patrick Vankrunkelsven, Patrik Goderis, Geert Hermens, Rosella Van Pottelbergh, Gijs Vaes, Bert Trials Study Protocol BACKGROUND: The 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. METHODS: This 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 REGISTRATION: ClinicalTrials.gov NCT04388228. Registered on May 14, 2020. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13063-021-05259-9. BioMed Central 2021-05-04 /pmc/articles/PMC8097814/ /pubmed/33947448 http://dx.doi.org/10.1186/s13063-021-05259-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Study Protocol
Van den Bulck, Steve
De Burghgraeve, Tine
Raat, Willem
Mamouris, Pavlos
Coursier, Patrick
Vankrunkelsven, Patrik
Goderis, Geert
Hermens, Rosella
Van Pottelbergh, Gijs
Vaes, Bert
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
title 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_short 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
title_sort 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
topic Study Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8097814/
https://www.ncbi.nlm.nih.gov/pubmed/33947448
http://dx.doi.org/10.1186/s13063-021-05259-9
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