Nissen Francis, Quint Jennifer K, Wilkinson Samantha, Mullerova Hana, Smeeth Liam, Douglas Ian J
Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
National Heart and Lung Institute, Imperial College, London, UK.
BMJ Open. 2017 May 29;7(5):e014694. doi: 10.1136/bmjopen-2016-014694.
Asthma is a common, heterogeneous disease with significant morbidity and mortality worldwide. It can be difficult to define in epidemiological studies using electronic health records as the diagnosis is based on non-specific respiratory symptoms and spirometry, neither of which are routinely registered. Electronic health records can nonetheless be valuable to study the epidemiology, management, healthcare use and control of asthma. For health databases to be useful sources of information, asthma diagnoses should ideally be validated. The primary objectives are to provide an overview of the methods used to validate asthma diagnoses in electronic health records and summarise the results of the validation studies.
EMBASE and MEDLINE will be systematically searched for appropriate search terms. The searches will cover all studies in these databases up to October 2016 with no start date and will yield studies that have validated algorithms or codes for the diagnosis of asthma in electronic health records. At least one test validation measure (sensitivity, specificity, positive predictive value, negative predictive value or other) is necessary for inclusion. In addition, we require the validated algorithms to be compared with an external golden standard, such as a manual review, a questionnaire or an independent second database. We will summarise key data including author, year of publication, country, time period, date, data source, population, case characteristics, clinical events, algorithms, gold standard and validation statistics in a uniform table.
This study is a synthesis of previously published studies and, therefore, no ethical approval is required. The results will be submitted to a peer-reviewed journal for publication. Results from this systematic review can be used to study outcome research on asthma and can be used to identify case definitions for asthma.
CRD42016041798.
哮喘是一种常见的异质性疾病,在全球范围内具有较高的发病率和死亡率。在流行病学研究中,由于哮喘诊断基于非特异性呼吸道症状和肺功能测定,而这两者均非常规记录,因此使用电子健康记录来定义哮喘可能具有挑战性。尽管如此,电子健康记录对于研究哮喘的流行病学、管理、医疗保健利用和控制仍具有重要价值。为了使健康数据库成为有用的信息来源,理想情况下应对哮喘诊断进行验证。本研究的主要目的是概述用于验证电子健康记录中哮喘诊断的方法,并总结验证研究的结果。
将系统检索EMBASE和MEDLINE以获取适当的检索词。检索将涵盖这些数据库截至2016年10月且无起始日期的所有研究,并将产生已验证电子健康记录中哮喘诊断算法或编码的研究。纳入研究至少需要一项测试验证指标(敏感性、特异性、阳性预测值、阴性预测值或其他)。此外,我们要求将经过验证的算法与外部金标准进行比较,例如人工审核、问卷调查或独立的第二个数据库。我们将在统一表格中总结关键数据,包括作者、发表年份、国家、时间段、日期、数据源、人群、病例特征、临床事件、算法、金标准和验证统计数据。
本研究是对先前发表研究的综合,因此无需伦理批准。研究结果将提交给同行评审期刊发表。该系统评价的结果可用于研究哮喘的结局研究,并可用于确定哮喘的病例定义。
PROSPERO注册号:CRD42016041798。