Swansea University Medical School, Swansea, UK
Asthma UK Centre for Applied Research, UK.
Eur Respir J. 2017 Jun 15;49(6). doi: 10.1183/13993003.00204-2017. Print 2017 Jun.
There is currently no consensus on approaches to defining asthma or assessing asthma outcomes using electronic health record-derived data. We explored these approaches in the recent literature and examined the clarity of reporting.We systematically searched for asthma-related articles published between January 1, 2014 and December 31, 2015, extracted the algorithms used to identify asthma patients and assess severity, control and exacerbations, and examined how the validity of these outcomes was justified.From 113 eligible articles, we found significant heterogeneity in the algorithms used to define asthma (n=66 different algorithms), severity (n=18), control (n=9) and exacerbations (n=24). For the majority of algorithms (n=106), validity was not justified. In the remaining cases, approaches ranged from using algorithms validated in the same databases to using nonvalidated algorithms that were based on clinical judgement or clinical guidelines. The implementation of these algorithms was suboptimally described overall.Although electronic health record-derived data are now widely used to study asthma, the approaches being used are significantly varied and are often underdescribed, rendering it difficult to assess the validity of studies and compare their findings. Given the substantial growth in this body of literature, it is crucial that scientific consensus is reached on the underlying definitions and algorithms.
目前,对于使用电子健康记录数据定义哮喘或评估哮喘结果的方法,尚未达成共识。我们在最近的文献中探讨了这些方法,并检查了报告的清晰度。我们系统地搜索了 2014 年 1 月 1 日至 2015 年 12 月 31 日期间发表的与哮喘相关的文章,提取了用于识别哮喘患者和评估严重程度、控制和加重的算法,并检查了这些结果的有效性是如何证明的。在 113 篇合格的文章中,我们发现用于定义哮喘(n=66 种不同的算法)、严重程度(n=18)、控制(n=9)和加重(n=24)的算法存在显著的异质性。对于大多数算法(n=106),其有效性未得到证明。在其余情况下,方法范围从在同一数据库中验证的算法到基于临床判断或临床指南的未经验证的算法。总体而言,这些算法的实施情况描述得并不理想。尽管电子健康记录数据现在已广泛用于研究哮喘,但所使用的方法差异很大,而且往往描述不足,这使得难以评估研究的有效性并比较其结果。鉴于这方面文献的大量增长,就基础定义和算法达成科学共识至关重要。