Deriving a Standardised Recommended Respiratory Disease Codelist Repository for Future Research.

IF 2.3 Q2 MEDICINE, GENERAL & INTERNAL Pragmatic and Observational Research Pub Date : 2022-02-16 eCollection Date: 2022-01-01 DOI:10.2147/POR.S353400
Clare MacRae, Hannah Whittaker, Mome Mukherjee, Luke Daines, Ann Morgan, Chukwuma Iwundu, Mohammed Alsallakh, Eleftheria Vasileiou, Eimear O'Rourke, Alexander T Williams, Philip W Stone, Aziz Sheikh, Jennifer K Quint
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引用次数: 2

Abstract

Background: Electronic health record (EHR) databases provide rich, longitudinal data on interactions with healthcare providers and can be used to advance research into respiratory conditions. However, since these data are primarily collected to support health care delivery, clinical coding can be inconsistent, resulting in inherent challenges in using these data for research purposes.

Methods: We systematically searched existing international literature and UK code repositories to find respiratory disease codelists for asthma from January 2018, and chronic obstructive pulmonary disease and respiratory tract infections from January 2020, based on prior searches. Medline searches using key terms provided in article lists. Full-text articles, supplementary files, and reference lists were examined for codelists, and codelists repositories were searched. A reproducible methodology for codelists creation was developed with recommended lists for each disease created based on multidisciplinary expert opinion and previously published literature.

Results: Medline searches returned 1126 asthma articles, 70 COPD articles, and 90 respiratory infection articles, with 3%, 22% and 5% including codelists, respectively. Repository searching returned 12 asthma, 23 COPD, and 64 respiratory infection codelists. We have systematically compiled respiratory disease codelists and from these derived recommended lists for use by researchers to find the most up-to-date and relevant respiratory disease codelists that can be tailored to individual research questions.

Conclusion: Few published papers include codelists, and where published diverse codelists were used, even when answering similar research questions. Whilst some advances have been made, greater consistency and transparency across studies using routine data to study respiratory diseases are needed.

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为未来研究建立一个标准化的推荐呼吸系统疾病代码库。
背景:电子健康记录(EHR)数据库提供了与医疗保健提供者互动的丰富的纵向数据,可用于推进呼吸疾病的研究。然而,由于收集这些数据主要是为了支持卫生保健服务,因此临床编码可能不一致,从而导致在将这些数据用于研究目的方面存在固有挑战。方法:我们系统地检索现有的国际文献和英国代码库,以查找2018年1月的哮喘和2020年1月的慢性阻塞性肺疾病和呼吸道感染的呼吸道疾病代码库。Medline使用文章列表中提供的关键字进行搜索。全文文章、补充文件和参考文献列表被检查以查找代码列表,并搜索代码列表存储库。根据多学科专家意见和以前发表的文献,制定了一种可重复的清单编制方法,并为每种疾病编制了推荐清单。结果:Medline检索返回1126篇哮喘文章,70篇COPD文章和90篇呼吸道感染文章,分别有3%,22%和5%包含codelists。信息库检索得到12名哮喘、23名慢性阻塞性肺病和64名呼吸道感染病例。我们系统地编制了呼吸系统疾病编码清单,并从这些衍生出的推荐清单中,供研究人员使用,以找到最新和相关的呼吸系统疾病编码清单,这些清单可以针对个别研究问题进行定制。结论:很少有已发表的论文包含codelist,并且即使在回答类似的研究问题时,也使用了不同的codelist。虽然取得了一些进展,但需要在使用常规数据研究呼吸系统疾病的研究中提高一致性和透明度。
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Pragmatic and Observational Research
Pragmatic and Observational Research MEDICINE, GENERAL & INTERNAL-
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期刊介绍: Pragmatic and Observational Research is an international, peer-reviewed, open-access journal that publishes data from studies designed to closely reflect medical interventions in real-world clinical practice, providing insights beyond classical randomized controlled trials (RCTs). While RCTs maximize internal validity for cause-and-effect relationships, they often represent only specific patient groups. This journal aims to complement such studies by providing data that better mirrors real-world patients and the usage of medicines, thus informing guidelines and enhancing the applicability of research findings across diverse patient populations encountered in everyday clinical practice.
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