Leeds Liver Unit, Leeds Teaching Hospitals NHS Trust, Leeds, UK.
Leeds Institute for Data Analytics, University of Leeds, Leeds, UK.
Aliment Pharmacol Ther. 2022 Mar;55(6):645-657. doi: 10.1111/apt.16806. Epub 2022 Feb 15.
Electronic health records (EHRs) collate longitudinal data that can be used to facilitate large-scale research in patients with cirrhosis. However, there is no consensus code set to define the presence of cirrhosis in EHR. This systematic review aims to evaluate the validity of diagnostic coding in cirrhosis and to synthesise a comprehensive set of ICD-10 codes for future EHR research.
MEDLINE and EMBASE databases were searched for studies that used EHR to identify cirrhosis and cirrhosis-related complications. Validated code sets were summarised, and the performance characteristics were extracted. Citation analysis was done to inform development of a consensus code set. This was then validated in a cohort of patients.
One thousand six hundred twenty-six records were screened, and 18 studies were identified. The positive predictive value (PPV) was the most frequently reported statistical estimate and was ≥80% in 17/18 studies. Citation analyses showed continued variation in those used in contemporary research practice. Nine codes were identified as those most frequently used in the literature and these formed the consensus code set. This was validated in diverse patient populations from Europe and North America and showed high PPV (83%-89%) and greater sensitivity for the identification of cirrhosis than the most often used code set in the recent literature.
There is variation in code sets used to identify cirrhosis in contemporary research practice. A consensus set has been developed and validated, showing improved performance, and is proposed to align EHR study designs in cirrhosis to facilitate international collaboration and comparisons.
电子健康记录 (EHR) 可以整理出纵向数据，这些数据可用于促进肝硬化患者的大规模研究。然而，目前还没有共识的编码集来定义 EHR 中肝硬化的存在。本系统综述旨在评估肝硬化诊断编码的有效性，并为未来的 EHR 研究综合一套全面的 ICD-10 编码。
在 MEDLINE 和 EMBASE 数据库中搜索使用 EHR 来识别肝硬化和肝硬化相关并发症的研究。总结了经过验证的编码集，并提取了性能特征。引文分析有助于制定共识编码集。然后在一组患者中验证了该编码集。
共筛选出 1626 条记录，确定了 18 项研究。阳性预测值 (PPV) 是最常报告的统计估计值，在 17/18 项研究中≥80%。引文分析表明，目前研究实践中仍存在差异。确定了 9 个最常被文献使用的代码，这些代码构成了共识编码集。该编码集在来自欧洲和北美的不同患者群体中进行了验证，其阳性预测值 (83%-89%) 和肝硬化识别的敏感性均高于最近文献中最常用的编码集。
目前在当代研究实践中，用于识别肝硬化的编码集存在差异。已经制定并验证了一套共识编码集，其性能有所提高，并建议用于肝硬化的 EHR 研究设计，以促进国际合作和比较。
