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基于验证的行政数据的 ICD-10 算法用于慢性疾病:系统评价。

Validated administrative data based ICD-10 algorithms for chronic conditions: A systematic review.

机构信息

Centre for Health Informatics, Cumming School of Medicine, University of Calgary, AB, Canada.

Centre for Health Informatics, Cumming School of Medicine, University of Calgary, AB, Canada; Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.

出版信息

J Epidemiol Popul Health. 2024 Aug;72(4):202744. doi: 10.1016/j.jeph.2024.202744. Epub 2024 Jul 5.

Abstract

OBJECTIVE

This systematic review aimed to identify ICD-10 based validated algorithms for chronic conditions using health administrative data.

METHODS

A comprehensive systematic literature search using Ovid MEDLINE, Embase, PsycINFO, Web of Science and CINAHL was performed to identify studies, published between 1983 and May 2023, on validated algorithms for chronic conditions using administrative health data. Two reviewers independently screened titles and abstracts and reviewed full text of selected studies to complete data extraction. A third reviewer resolved conflicts arising at the screening or study selection stages. The primary outcome was validated studies of ICD-10 based algorithms with both sensitivity and PPV of ≥70 %. Studies with either sensitivity or PPV <70 % were included as secondary outcomes.

RESULTS

Overall, the search identified 1686 studies of which 54 met the inclusion criteria. Combining a previously published literature search, a total of 61 studies were included for data extraction. The study identified 40 chronic conditions with high validity and 22 conditions with moderate validity. The validated algorithms were based on administrative data from different countries including Canada, USA, Australia, Japan, France, South Korea, and Taiwan. The algorithms identified included several types of cancers, cardiovascular conditions, kidney diseases, gastrointestinal disorders, and peripheral vascular diseases, amongst others.

CONCLUSION

With ICD-10 prominently used across the world, this up-to-date systematic review can prove to be a helpful resource for research and surveillance initiatives using administrative health data for identifying chronic conditions.

摘要

目的

本系统评价旨在利用健康管理数据确定基于 ICD-10 的慢性疾病验证算法。

方法

通过 Ovid MEDLINE、Embase、PsycINFO、Web of Science 和 CINAHL 进行全面的系统文献检索,以确定 1983 年至 2023 年 5 月期间使用健康管理数据确定慢性疾病验证算法的研究。两名审查员独立筛选标题和摘要,并审查选定研究的全文以完成数据提取。第三位审查员解决筛选或研究选择阶段出现的冲突。主要结果是基于 ICD-10 的算法具有≥70%的灵敏度和 PPV 的验证研究。灵敏度或 PPV<70%的研究作为次要结果纳入。

结果

总体而言,该搜索共确定了 1686 项研究,其中 54 项符合纳入标准。结合之前的文献搜索,共有 61 项研究纳入数据提取。该研究确定了 40 种具有高有效性的慢性疾病和 22 种具有中度有效性的慢性疾病。验证算法基于来自不同国家的管理数据,包括加拿大、美国、澳大利亚、日本、法国、韩国和中国台湾。确定的算法包括多种癌症、心血管疾病、肾脏疾病、胃肠道疾病和外周血管疾病等。

结论

鉴于 ICD-10 在全球范围内广泛使用,本最新系统评价可以为使用健康管理数据识别慢性疾病的研究和监测计划提供有价值的资源。

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