School of Social Work, Rutgers University, New Brunswick, New Jersey, USA.
Department of Dental Public Health and Professional Practice, West Virginia University, Morgantown, West Virginia, USA.
Popul Health Manag. 2023 Feb;26(1):22-28. doi: 10.1089/pop.2022.0197.
The Whole Health model is a holistic approach to facilitate whole health practices by addressing (1) the physical, mental, and social health of individuals and (2) associated support systems. Several national organizations such as the Institute for Healthcare Improvement's (IHI) Age-Friendly Health Systems (AFHS) movement and, the U.S. Department of Veterans Affairs have implemented whole health frameworks with many common elements and promoted whole health practice and skills. However, implementing a Whole Health model across communities and health systems will require evidence of effectiveness. Generating evidence on the effectiveness of the Whole Health model's effect on health outcomes requires data-driven intelligence. We identified the national public-use data sets that are most often used in health research with a machine-assisted literature search of PubMed and Scopus for peer-reviewed journal articles published from 2010 through the end of 2021, including preprints, using Python [3.7]. We then assessed if the 8 most commonly used datasets include variables associated with whole health. The number of publications examining whole health has increased annually in the last decade, with more than 2800 publications in 2020 alone. Since 2010, 24,811 articles have been published using 1 of these data sets. However, we also found a lack of data (ie, data set includes all of the whole health variables) to examine whole health in national data sets. We support a call to expand data collection and standardization of critical measures of whole health.
整体健康模式是一种整体方法，通过解决（1）个人的身体、心理和社会健康以及（2）相关支持系统，促进整体健康实践。一些国家组织，如医疗改善研究所（IHI）的老年友好型健康系统（AFHS）运动和美国退伍军人事务部，已经实施了具有许多共同要素的整体健康框架，并促进了整体健康实践和技能。然而，要在社区和卫生系统中实施整体健康模式，就需要有效性的证据。要生成关于整体健康模式对健康结果的有效性的证据，需要数据驱动的情报。我们确定了在健康研究中最常使用的国家公共使用数据集，使用 Python [3.7]对 PubMed 和 Scopus 中的同行评审期刊文章进行了机器辅助文献搜索，搜索范围从 2010 年到 2021 年底，包括预印本。然后，我们评估了 8 个最常用的数据集是否包含与整体健康相关的变量。在过去十年中，每年检查整体健康的出版物数量都在增加，仅 2020 年就有超过 2800 篇出版物。自 2010 年以来，已经使用其中一个数据集发表了 24811 篇文章。然而，我们还发现缺乏数据（即，数据集包括所有整体健康变量）来检查国家数据集中的整体健康。我们支持扩大数据收集和整体健康关键措施标准化的呼吁。
