Basu Sanjay, Kiernan Michaela
Prevention Research Center, Stanford University, Stanford, CA (SB, MK).
Med Decis Making. 2016 Jan;36(1):48-58. doi: 10.1177/0272989X15585984. Epub 2015 May 14.
While increasingly popular among mid- to large-size employers, using financial incentives to induce health behavior change among employees has been controversial, in part due to poor quality and generalizability of studies to date. Thus, fundamental questions have been left unanswered: To generate positive economic returns on investment, what level of incentive should be offered for any given type of incentive program and among which employees?
We constructed a novel modeling framework that systematically identifies how to optimize marginal return on investment from programs incentivizing behavior change by integrating commonly collected data on health behaviors and associated costs. We integrated "demand curves" capturing individual differences in response to any given incentive with employee demographic and risk factor data. We also estimated the degree of self-selection that could be tolerated: that is, the maximum percentage of already-healthy employees who could enroll in a wellness program while still maintaining positive absolute return on investment. In a demonstration analysis, the modeling framework was applied to data from 3000 worksite physical activity programs across the nation.
For physical activity programs, the incentive levels that would optimize marginal return on investment ($367/employee/year) were higher than average incentive levels currently offered ($143/employee/year). Yet a high degree of self-selection could undermine the economic benefits of the program; if more than 17% of participants came from the top 10% of the physical activity distribution, the cost of the program would be expected to always be greater than its benefits.
Our generalizable framework integrates individual differences in behavior and risk to systematically estimate the incentive level that optimizes marginal return on investment.
虽然在大中型雇主中越来越受欢迎，但利用经济激励措施促使员工改变健康行为一直存在争议，部分原因是迄今为止研究的质量较差且缺乏普遍适用性。因此，一些基本问题仍未得到解答：为了产生积极的投资经济回报，对于任何给定类型的激励计划以及哪些员工，应该提供何种水平的激励？
我们构建了一个新颖的建模框架，通过整合关于健康行为和相关成本的常见收集数据，系统地确定如何优化激励行为改变计划的投资边际回报。我们将反映个体对任何给定激励措施反应差异的“需求曲线”与员工人口统计和风险因素数据相结合。我们还估计了可以容忍的自我选择程度：也就是说，在仍保持正的绝对投资回报的情况下，能够参加健康计划的健康员工的最大百分比。在一项示范分析中，该建模框架应用于来自全国3000个工作场所体育活动计划的数据。
对于体育活动计划，优化投资边际回报的激励水平（367美元/员工/年）高于目前提供的平均激励水平（143美元/员工/年）。然而，高度的自我选择可能会破坏该计划的经济效益；如果超过17%的参与者来自体育活动分布前10%的人群，预计该计划的成本将始终大于其收益。
我们的通用框架整合了行为和风险方面的个体差异，以系统地估计优化投资边际回报的激励水平。
