自动化审计和反馈对一般医生电子健康记录中数据完整性的影响：一项群组随机对照试验方案。
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.
机构信息
Academic Center for General Practice, KU Leuven, Kapucijnenvoer 33 blok J, 3000, Leuven, Belgium.
IQ Healthcare, Radboud University Medical Center Nijmegen, PO Box 9101, 6500, HB, Nijmegen, The Netherlands.
出版信息
Trials. 2021 May 4;22(1):325. doi: 10.1186/s13063-021-05259-9.
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.
背景
全科医生（GP）的电子健康记录（EHR）是评估和提高医疗保健质量的重要工具。然而，在将 EHR 中收集的数据用于质量评估时，存在一些问题。一个问题是 EHR 中数据的完整性不足。审核和反馈（A&F）是一种众所周知的质量干预措施，可以提高医疗保健质量。我们假设可以对自动化的 A&F 干预措施进行调整，以提高 GP 的 EHR 数据的完整性，更具体地说，提高 2 型糖尿病和慢性肾脏病的正确登记诊断数量。
方法
这是一项具有干预措施在全科医生诊所层面的实用集群随机对照试验。该干预措施包括审核和多次扩展的电子传递反馈，这些内容将在 12 个月内分 4 次向全科医生诊所电子传递。数据将在聚合水平上（按每位全科医生诊所）进行分析。主要结局是 2 型糖尿病正确登记诊断的百分比。关键次要结局是慢性肾脏病的登记。探索性次要结局是心力衰竭、生物计量数据和生活方式习惯的登记，以及 4 个不同的 EHR 可提取质量指标的演变。
讨论
这项集群随机对照试验旨在主要提高 GP 的 EHR 中 2 型糖尿病的登记，其次是提高慢性肾脏病的登记。此外，还将一起探索心力衰竭、生活方式参数和 GP 的 EHR 中的生物计量数据，以及 4 个 EHR 可提取的质量指标。通过这样做，本研究旨在提高 EHR 的数据完整性，为未来的质量评估铺平道路。
试验注册
ClinicalTrials.gov NCT04388228。于 2020 年 5 月 14 日注册。
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