Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany.
Data Integration Center, University Medicine Greifswald, Greifswald, Germany.
Stud Health Technol Inform. 2022 Jun 6;290:130-134. doi: 10.3233/SHTI220046.
Automated identification of eligible patients for clinical trials is an evident secondary use for electronic health records (EHR) data accumulated during routine care. This task requires relevant data elements to be both available in the EHR and in a structured form. This work analyzes these data quality dimensions of EHR data elements corresponding to a selection of frequent eligibility criteria over a total of 436 patient records at 10 university hospitals within the MIRACUM consortium. Data elements from demographics, diagnosis and laboratory findings are typically structured with a completeness of 73 % to 88 % while medication as well as procedures are rather untructured with a completeness of only 44 %. The results can be used to derive suggestions for data quality improvement measures with respect to patient recruitment as well as to serve as a baseline to quantify future developments.
电子健康记录（EHR）在常规护理期间积累的数据的明显二次使用是为临床试验自动识别合格患者。此任务要求相关数据元素不仅在 EHR 中可用，而且还以结构化形式可用。这项工作分析了 MIRACUM 联盟 10 家大学医院的 436 份患者记录中与一系列常见资格标准相对应的 EHR 数据元素的这些数据质量维度。来自人口统计学、诊断和实验室结果的数据元素通常具有 73%至 88%的完整性，而药物和程序则相对没有结构，只有 44%的完整性。结果可用于针对患者招募提出数据质量改进措施的建议，并作为量化未来发展的基线。
