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通过可扩展的电子健康数据关联分析来提高人群健康管理的参与度。

Improving uptake of population health management through scalable analysis of linked electronic health data.

机构信息

Modelling and Analytics (BNSSG ICB), UK National Health Service, Bristol, UK.

Centre for Healthcare Innovation and Improvement, School of Management, University of Bath, Bath, UK.

出版信息

Health Informatics J. 2024 Jul-Sep;30(3):14604582241259344. doi: 10.1177/14604582241259344.

Abstract

Population Health Management - often abbreviated to PHM - is a relatively new approach for healthcare planning, requiring the application of analytical techniques to linked patient level data. Despite expectations for greater uptake of PHM, there is a deficit of available solutions to help health services embed it into routine use. This paper concerns the development, application and use of an interactive tool which can be linked to a healthcare system's data warehouse and employed to readily perform key PHM tasks such as population segmentation, risk stratification, and deriving various performance metrics and descriptive summaries. Developed through open-source code in a large healthcare system in South West England, and used by others around the country, this paper demonstrates the importance of a scalable, purpose-built solution for improving the uptake of PHM in health services.

摘要

人群健康管理——通常缩写为 PHM——是一种相对较新的医疗保健规划方法,需要将分析技术应用于关联的患者级数据。尽管人们期望更广泛地采用 PHM,但可用的解决方案却不足以帮助医疗服务机构将其纳入常规使用。本文介绍了一种交互式工具的开发、应用和使用,该工具可以与医疗保健系统的数据仓库相链接,并用于方便地执行关键的 PHM 任务,如人群细分、风险分层,以及得出各种绩效指标和描述性摘要。该工具是在英格兰西南部的一个大型医疗保健系统中使用开源代码开发的,并在全国范围内被其他机构使用,本文展示了为提高医疗服务机构 PHM 采用率而开发可扩展、专用解决方案的重要性。

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