Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain.
Universitat Autònoma de Barcelona, Bellaterra (Cerdanyola del Vallès), Barcelona, Spain.
Pharmacoepidemiol Drug Saf. 2024 Jan;33(1):e5717. doi: 10.1002/pds.5717. Epub 2023 Oct 25.
Real-world data (RWD) offers a valuable resource for generating population-level disease epidemiology metrics. We aimed to develop a well-tested and user-friendly R package to compute incidence rates and prevalence in data mapped to the observational medical outcomes partnership (OMOP) common data model (CDM).
We created IncidencePrevalence, an R package to support the analysis of population-level incidence rates and point- and period-prevalence in OMOP-formatted data. On top of unit testing, we assessed the face validity of the package. To do so, we calculated incidence rates of COVID-19 using RWD from Spain (SIDIAP) and the United Kingdom (CPRD Aurum), and replicated two previously published studies using data from the Netherlands (IPCI) and the United Kingdom (CPRD Gold). We compared the obtained results to those previously published, and measured execution times by running a benchmark analysis across databases.
IncidencePrevalence achieved high agreement to previously published data in CPRD Gold and IPCI, and showed good performance across databases. For COVID-19, incidence calculated by the package was similar to public data after the first-wave of the pandemic.
For data mapped to the OMOP CDM, the IncidencePrevalence R package can support descriptive epidemiological research. It enables reliable estimation of incidence and prevalence from large real-world data sets. It represents a simple, but extendable, analytical framework to generate estimates in a reproducible and timely manner.
真实世界数据（RWD）为生成人群疾病流行病学指标提供了有价值的资源。我们旨在开发一个经过充分测试且用户友好的 R 包，以计算映射到观察性医疗结局伙伴关系（OMOP）通用数据模型（CDM）的数据中的发病率和患病率。
我们创建了 IncidencePrevalence，这是一个 R 包，用于支持分析 OMOP 格式化数据中的人群发病率和时点和期间患病率。除了单元测试外，我们还评估了该软件包的表面有效性。为此，我们使用来自西班牙（SIDIAP）和英国（CPRD Aurum）的 RWD 计算了 COVID-19 的发病率，并使用来自荷兰（IPCI）和英国（CPRD Gold）的数据复制了两项先前发表的研究。我们将获得的结果与先前发表的结果进行了比较，并通过在数据库之间进行基准分析来衡量执行时间。
IncidencePrevalence 在 CPRD Gold 和 IPCI 中与先前发表的数据高度一致，并且在各个数据库中表现良好。对于 COVID-19，该软件包计算的发病率与大流行第一波后的公共数据相似。
对于映射到 OMOP CDM 的数据，IncidencePrevalence R 包可以支持描述性流行病学研究。它能够从大型真实世界数据集可靠地估计发病率和患病率。它代表了一种简单但可扩展的分析框架，可以以可重复和及时的方式生成估计值。
