背景:由全科医生(GP)收集的数据可能为卫生服务研究提供潜力。在这项研究中,我们调查了是否可以通过诊断社区获得性肺炎(CAP)的方式用全科医生的电子病历(EMR)回答临床问题.
方法:诊断为CAP的患者,定义为ICD代码J18.9,于2021年第四季度确定。数据来自德国中部30个一般做法协会的EMR系统(MedicalOffice®),使用三种不同的方法:1.综合统计工具用于记录患者是否被转诊进行放射学诊断确认。2.回顾过去,EMR由熟悉EMR的医生手动评估。3.通过自动导出提取EMR系统的原始数据。比较了通过三种访问获得的信息。对于每个病人病例,根据Mayring,对问题和细节的详细评论进行了记录,并通过定性内容分析(QCA)进行了评估.
结果:总计,确定了164例诊断为CAP的患者。记录的放射诊断确认的数量因数据方法而异:虽然对EMR的手动评估显示有60名转诊的患者,统计工具确定了其中38例。原始数据的输出确定了58个调整后转介给射线照相。根据QCA,应用诊断和诊断时间差异很大.在诊断编码之前和之后都进行了X线照相转诊。在住院的情况下,通常在住院期间进行X射线检查。进行实验室测试以替代放射线照相术。风险因素和诊断确定性的记录也存在很大差异。
结论:集成到EMR系统中的统计工具是一种执行简单查询的快速方法,但被证明对于复杂问题是不切实际的。EMR提供详细信息,但需要手动评估。从原始数据自动导出数据可提供详细信息和对大量数据的访问,但需要复杂的准备和适当的IT专业知识。
结论:基于GP设置的诊断CAP的例子,使用从EMR系统提取的数据似乎可以回答简单的临床问题.然而,有必要调整数据导出,与少量手动评估的案例进行比较对于获得有效的结果很有用。
BACKGROUND: Data collected by general practitioners (GPs) may provide potential for health services research. In this study, we investigated if clinical questions can be answered with GPs\' electronic medical records (EMRs) by means of diagnosing community-acquired pneumonia (CAP).
METHODS: Patients diagnosed with CAP, defined as ICD code J18.9, were identified in the fourth quarter of 2021. The data were derived from the EMR system (Medical Office®) of a central German association of 30 general practices, using three different approaches: 1. The integrated statistic tool was used to record whether patients were referred for radiological diagnostic confirmation. 2. Retrospectively, EMRs were evaluated manually by a doctor familiar with the EMR. 3. The raw data of the EMR system were extracted by automated export. The information obtained through the three types of access was compared. For each patient case, detailed comments on problems and specifics were documented and evaluated by qualitative content analysis (QCA) according to Mayring.
RESULTS: In total, 164 patients diagnosed with CAP were identified. The numbers of documented radiological diagnostic confirmations varied between data approaches: While the manual evaluation of the EMRs revealed 60 referred patients, the statistics tool identified 38 of these cases. The export of the raw data identified 58 referrals to radiography after adjustment. According to QCA, there was a high variation in applied diagnostics and time of diagnosis. Referrals for radiography were made both before and after coding of the diagnosis. In case of hospitalization, X-rays were usually performed during the inpatient stay. Laboratory tests were performed as an alternative to radiography. There was also a high variation in the documentation of risk factors and diagnostic certainty.
CONCLUSIONS: The statistics tool integrated into the EMR system is a quick way to perform simple queries but proved to be impracticable for complex questions. The EMRs provide detailed information but need to be evaluated manually. An automated data export from the raw data offers both detailed information and access to large volumes of data but requires complex preparation and appropriate IT expertise.
CONCLUSIONS: Based on the example of diagnosed CAP in a GP setting, the use of data extracted from an EMR system seems to be feasible to answer simple clinical questions. However, it is necessary to adapt the data export, and a comparison with a small number of manually evaluated cases is useful to achieve valid results.