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用于提高电子健康记录(EHR)数据质量的结构化数据质量报告。

Structured data quality reports to improve EHR data quality.

作者信息

Taggart Jane, Liaw Siaw-Teng, Yu Hairong

机构信息

Centre for Primary Health Care& Equity, UNSW Australia, Sydney, Australia.

Centre for Primary Health Care& Equity, UNSW Australia, Sydney, Australia; School of Public Health & Community Medicine, UNSW Australia, Sydney, Australia; General Practice Unit, South Western Sydney Local Health District, NSW, Australia.

出版信息

Int J Med Inform. 2015 Dec;84(12):1094-8. doi: 10.1016/j.ijmedinf.2015.09.008. Epub 2015 Oct 9.

Abstract

OBJECTIVE

To examine whether a structured data quality report (SDQR) and feedback sessions with practice principals and managers improve the quality of routinely collected data in EHRs.

METHODS

The intervention was conducted in four general practices participating in the Fairfield neighborhood electronic Practice Based Research Network (ePBRN). Data were extracted from their clinical information systems and summarised as a SDQR to guide feedback to practice principals and managers at 0, 4, 8 and 12 months. Data quality (DQ) metrics included completeness, correctness, consistency and duplication of patient records. Information on data recording practices, data quality improvement, and utility of SDQRs was collected at the feedback sessions at the practices. The main outcome measure was change in the recording of clinical information and level of meeting Royal Australian College of General Practice (RACGP) targets.

RESULTS

Birth date was 100% and gender 99% complete at baseline and maintained. DQ of all variables measured improved significantly (p<0.01) over 12 months, but was not sufficient to comply with RACGP standards. Improvement was greatest with allergies. There was no significant change in duplicate records.

CONCLUSIONS

SDQRs and feedback sessions support general practitioners and practice managers to focus on improving the recording of patient information. However, improved practice DQ, was not sufficient to meet RACGP targets. Randomised controlled studies are required to evaluate strategies to improve data quality and any associated improved safety and quality of care.

摘要

目的

研究结构化数据质量报告(SDQR)以及与执业负责人和管理人员的反馈会议是否能提高电子健康记录(EHR)中常规收集数据的质量。

方法

干预措施在参与费尔菲尔德社区基于实践的电子研究网络(ePBRN)的四个普通诊所中实施。从其临床信息系统中提取数据,并汇总为一份SDQR,以指导在0、4、8和12个月时向执业负责人和管理人员提供反馈。数据质量(DQ)指标包括患者记录的完整性、正确性、一致性和重复性。在诊所的反馈会议上收集了有关数据记录实践、数据质量改进以及SDQR实用性的信息。主要结局指标是临床信息记录的变化以及达到澳大利亚皇家全科医师学院(RACGP)目标的水平。

结果

基线时出生日期的完整性为100%,性别为99%,且保持不变。在12个月内,所有测量变量的DQ均有显著改善(p<0.01),但仍不足以符合RACGP标准。过敏方面的改善最为显著。重复记录没有显著变化。

结论

SDQR和反馈会议有助于全科医生和诊所管理人员专注于改善患者信息的记录。然而,诊所DQ的改善仍不足以达到RACGP的目标。需要进行随机对照研究来评估提高数据质量的策略以及任何相关的护理安全性和质量的改善。

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