Abernathy Alice, Rodriguez Maria I, Swartz Jonas J
Department of Obstetrics and Gynecology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, United States.
Center for Reproductive Health Equity, Department of Obstetrics and Gynecology, Oregon Health & Sciences University, Portland, OR, United States.
Contraception. 2025 Feb;142:110750. doi: 10.1016/j.contraception.2024.110750. Epub 2024 Nov 15.
Health care insurance claims are an increasingly common data source for health outcomes research. While researchers have successfully used several claims data sources for many obstetric and gynecologic questions, the use of claims data for abortion and contraception research poses a number of challenges. In this update on the state of the science in identifying abortion in claims data, we review claims data generally, describe commonly used claims data sources, and detail specific reasons why abortion may be underestimated in claims even when employing best practices. We provide examples of successful approaches for identifying abortion in claims and importantly, spell out limitations when making comparisons across site of care, states, and policy contexts. As increased attention is turned to identifying abortion across diverse settings, it is critical best practices are applied so that the most appropriate inferences regarding abortion incidence across contexts over time are drawn.
医疗保险理赔数据是健康结果研究中越来越常见的数据源。虽然研究人员已经成功地将多个理赔数据源用于许多妇产科问题，但将理赔数据用于堕胎和避孕研究存在一些挑战。在本次关于在理赔数据中识别堕胎情况的科学现状更新中，我们总体回顾理赔数据，描述常用的理赔数据源，并详细说明即使采用最佳实践，堕胎情况在理赔中仍可能被低估的具体原因。我们提供在理赔中识别堕胎情况的成功方法示例，重要的是，阐明在不同医疗场所、州和政策背景下进行比较时的局限性。随着人们越来越关注在不同环境中识别堕胎情况，应用最佳实践至关重要，以便随着时间的推移，能够就不同背景下的堕胎发生率得出最恰当的推论。
