Division of Hepatology, Department of Upper GI, Karolinska University Hospital, Stockholm, Sweden.
Clinical Epidemiology Unit, Department of Medicine, Solna, Karolinska Institutet, Stockholm, Sweden.
Hepatology. 2021 Jul;74(1):474-482. doi: 10.1002/hep.31726. Epub 2021 Jun 22.
Electronic health record (EHR)-based research allows the capture of large amounts of data, which is necessary in NAFLD, where the risk of clinical liver outcomes is generally low. The lack of consensus on which International Classification of Diseases (ICD) codes should be used as exposures and outcomes limits comparability and generalizability of results across studies. We aimed to establish consensus among a panel of experts on ICD codes that could become the reference standard and provide guidance around common methodological issues.
Researchers with an interest in EHR-based NAFLD research were invited to collectively define which administrative codes are most appropriate for documenting exposures and outcomes. We used a modified Delphi approach to reach consensus on several commonly encountered methodological challenges in the field. After two rounds of revision, a high level of agreement (>67%) was reached on all items considered. Full consensus was achieved on a comprehensive list of administrative codes to be considered for inclusion and exclusion criteria in defining exposures and outcomes in EHR-based NAFLD research. We also provide suggestions on how to approach commonly encountered methodological issues and identify areas for future research.
This expert panel consensus statement can help harmonize and improve generalizability of EHR-based NAFLD research.
电子健康记录（EHR）为研究提供了大量数据，这在非酒精性脂肪性肝病（NAFLD）的研究中非常重要，因为 NAFLD 的临床肝脏结局风险通常较低。缺乏共识，导致哪些国际疾病分类（ICD）代码应作为暴露和结局使用，限制了研究间结果的可比性和普遍性。我们旨在通过专家小组就可作为参考标准的 ICD 代码达成共识，并就常见的方法学问题提供指导。
我们邀请对 EHR 为基础的 NAFLD 研究有兴趣的研究人员共同定义哪些行政代码最适合记录暴露和结局。我们使用改良 Delphi 方法就该领域中常见的几个方法学挑战达成共识。经过两轮修订，所有被认为相关的项目都达成了>67%的高度一致性。最终达成了共识，确定了一个综合的行政代码列表，用于定义 EHR 为基础的 NAFLD 研究中的纳入和排除标准。我们还就如何处理常见的方法学问题以及确定未来研究领域提出了建议。
该专家小组的共识声明有助于协调和提高 EHR 为基础的 NAFLD 研究的普遍性。
