二级使用常规收集的行政卫生数据进行流行病学研究:使用为不同目的收集的数据回答研究问题。

IF 1.6 Q3 HEALTH CARE SCIENCES & SERVICES International Journal of Population Data Science Pub Date : 2024-11-19 eCollection Date: 2024-01-01 DOI:10.23889/ijpds.v9i1.2407
Scott D Emerson, Taylor McLinden, Paul Sereda, Amanda M Yonkman, Jason Trigg, Sandra Peterson, Robert S Hogg, Kate A Salters, Viviane D Lima, Rolando Barrios
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引用次数: 0

摘要

使用常规收集的行政卫生数据进行研究可以提供独特的见解,为决策提供信息,并最终支持更好的公共卫生成果。然而,由于收集这些数据主要是为了管理医疗保健服务的提供,因此在将这些数据用于次要目的(即流行病学研究)时存在挑战。许多这些挑战源于研究人员缺乏对数据收集的质量和一致性的控制,而且-进一步-对正在分析的数据的理解减少。也就是说,我们断言,通过在流行病学研究中仔细、系统地使用这些数据,可以部分减轻这些挑战。本文介绍了从分析加拿大不列颠哥伦比亚省(2024年人口超过500万)的行政卫生数据(例如,医疗保健从业者的账单、住院和处方药数据)的经验中得出的考虑,尽管我们认为基本原则适用于该地区以外的地区。主要考虑因素围绕四个主题进行组织:1)了解数据及其主要用途(了解其范围和局限性);2)了解分类和编码系统(了解分类系统、版本、它们在数据的主要用途中如何使用以及查询值方面的细微差别);3)将数据转换为有意义的形式(必要时处理数据并应用识别算法);4)在定义分析变量时认识到有效性的重要性(根据数据/算法做出有意义的推断)。虽然本文不是所有考虑因素的详尽列表,但我们相信它将为那些对利用行政卫生数据进行流行病学研究感兴趣的人提供实用的见解。
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Secondary use of routinely collected administrative health data for epidemiologic research: Answering research questions using data collected for a different purpose.

The use of routinely collected administrative health data for research can provide unique insights to inform decision-making and, ultimately, support better public health outcomes. Yet, since these data are primarily collected to administer healthcare service delivery, challenges exist when using such data for secondary purposes, namely epidemiologic research. Many of these challenges stem from the researcher's lack of control over the quality and consistency of data collection, and - furthermore - a lessened understanding of the data being analyzed. That said, we assert that these challenges can be partly mitigated through careful, systematic use of these data in epidemiologic research. This article presents considerations derived from experiences analyzing administrative health data (e.g., healthcare practitioner billings, hospitalizations, and prescription medication data) in the Canadian province of British Columbia (population of over 5 million in 2024), though we believe the underlying principles generalize beyond this region. Key considerations were organized around four themes: 1) Know the data and their primary use (understand their scope and limitations); 2) Understand classification and coding systems (appreciate the nuances regarding classification systems, versions, how they are employed in the primary uses of the data, and querying the values); 3) Transform data into meaningful forms (process data and apply identification algorithms, when necessary); 4) Recognize the importance of validity when defining analytic variables (make meaningful inferences based on data/algorithms). Although this article is not an exhaustive list of all considerations, we believe that it will provide pragmatic insights for those interested in leveraging administrative health data for epidemiologic research.

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来源期刊
CiteScore
2.50
自引率
0.00%
发文量
386
审稿时长
20 weeks
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