Amid soaring health spending, there is growing interest in workplace disease prevention and wellness programs to improve health and lower costs. In a critical meta-analysis of the literature on costs and savings associated with such programs, we found that medical costs fall by about $3.27 for every dollar spent on wellness programs and that absenteeism costs fall by about $2.73 for every dollar spent. Although further exploration of the mechanisms at work and broader applicability of the findings is needed, this return on investment suggests that the wider adoption of such programs could prove beneficial for budgets and productivity as well as health outcomes.

Difference-in-difference (DD) methods are a common strategy for evaluating the effects of policies or programs that are instituted at a particular point in time, such as the implementation of a new law. The DD method compares changes over time in a group unaffected by the policy intervention to the changes over time in a group affected by the policy intervention, and attributes the “difference-in-differences” to the effect of the policy. DD methods provide unbiased effect estimates if the trend over time would have been the same between the intervention and comparison groups in the absence of the intervention. However, a concern with DD models is that the program and intervention groups may differ in ways that would affect their trends over time, or their compositions may change over time. Propensity score methods are commonly used to handle this type of confounding in other non-experimental studies, but the particular considerations when using them in the context of a DD model have not been well investigated. In this paper, we describe the use of propensity scores in conjunction with DD models, in particular investigating a propensity score weighting strategy that weights the four groups (defined by time and intervention status) to be balanced on a set of characteristics. We discuss the conceptual issues associated with this approach, including the need for caution when selecting variables to include in the propensity score model, particularly given the multiple time point nature of the analysis. We illustrate the ideas and method with an application estimating the effects of a new payment and delivery system innovation (an accountable care organization model called the “Alternative Quality Contract” (AQC) implemented by Blue Cross Blue Shield of Massachusetts) on health plan enrollee out-of-pocket mental health service expenditures. We find no evidence that the AQC affected out-of-pocket mental health service expenditures of enrollees.

IMPORTANCE Employers have increasingly invested in workplace wellness programs to improve employee health and decrease health care costs. However, there is little experimental evidence on the effects of these programs. OBJECTIVE To evaluate a multicomponent workplace wellness program resembling programs offered by US employers.

Seven provider organizations in Massachusetts entered the Blue Cross Blue Shield Alternative Quality Contract in 2009, followed by four more organizations in 2010. This contract, based on a global budget and pay-for-performance for achieving certain quality benchmarks, places providers at risk for excessive spending and rewards them for quality, similar to the new Pioneer Accountable Care Organizations in Medicare. We analyzed changes in spending and quality associated with the Alternative Quality Contract and found that the rate of increase in spending slowed compared to control groups. Overall, participation in the contract over two years led to a savings of 3.3% (1.9% in year-1, 3.3% in year-2) compared to spending in groups not participating in the contract. The savings were even higher for groups whose previous experience had been only in fee-for-service contracting. Such groups’ quarterly savings over two years averaged 8.2% (6.3% in year-1, 9.9% in year-2). Quality of care also improved within organizations participating in the Alternative Quality Contract compared to control organizations in both years. Chronic care management, adult preventive care, and pediatric care improved from year 1 to year 2 within the contracting groups. These results suggest that global budgets coupled with pay-for-performance can begin to slow the underlying growth in medical spending while improving quality.