The well-being valuation model: a method for monetizing the nonmarket good of individual well-being

详细信息    查看全文

• 作者：James A. Sidney ; Ashlin Jones…
• 关键词：Health and well ; being improvement ; Health and well ; being monetization ; Exact matching ; Medical cost minimization
• 刊名：Health Services and Outcomes Research Methodology
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：17
• 期：1
• 页码：84-100
• 全文大小：416KB
• 刊物类别：Medicine
• 刊物主题：Public Health; Statistics, general; Economics, general; Methodology of the Social Sciences; Health Administration;
• 出版者：Springer US
• ISSN：1572-9400
• 卷排序：17

文摘

The objective of this research is to advance the evaluation and monetization of well-being improvement programs, offered by population health management companies, by presenting a novel method that robustly monetizes the entirety of well-being improvement within a population. This was achieved by utilizing two employers’ well-being assessments with medical and pharmacy administrative claims (2010–2011) across a large national employer (n = 50,647) and regional employer (n = 6170) data sets. This retrospective study sought to monetize both direct and indirect value of well-being improvement across a population whose medical costs are covered by an employer, insurer, and/or government entity. Logistic regression models were employed to estimate disease incidence rates and input–output modelling was used to measure indirect effects of well-being improvement. These methodological components removed the burden of specifying an exhaustive number of regression models, which would be difficult in small populations. Members who improved their well-being were less likely to become diseased. This reduction saved, per avoided occurrence, US$3060 of total annual health care costs. Of the members who were diseased, improvement in well-being equated to annual savings of US$62 while non-diseased members saved US$26. The method established here demonstrates the linkage between improved well-being and improved outcomes while maintaining applicability in varying populations.