Evaluating an insurance -sponsored weight management mprogram using the RE-AIM model.

Determining the public health impact of behavioral obesity treatment programs and industries with whom to ally in disseminating successful programs is critical to our nation\u27s health. In a recent report the National Institute for Health Care Management (NIHCM) Foundation (2005) recognized the leverage that health plans might have by establishing incentives for member participation in obesity treatment programs (i.e., weight management). The RE-AIM model (reach, effectiveness, adoption, implementation, maintenance; Glasgow, Vogt, & Boles, 1999) is designed to summarize the public health impact of health promotion programs and assist decision makers in understanding the ability of programs to: (a) reach large numbers of people representative of the target population, (b) be effective in promoting the targeted health outcome (c) be widely adopted by different and representative settings; (d) be consistently implemented by staff members of various levels of training and expertise; and (e) promote long-term maintenance of health outcomes in individuals and implementation in various sites (Glasgow, Klesges, Dzewaltowski, Estabrooks, & Vogt, 2006). The study used the RE-AIM model to evaluate the public health impact of a 12-week insurance-sponsored behavioral weight management program conducted throughout the state of West Virginia. Phase I (12 weeks) and Phase II (1 year) completion rates (77.5% and 45.7%, respectively) were lower than behavioral programs of similar length (Brownell & Wadden, 1992). Average weight loss of Phase I completers (M = 14.8, SD = 12.3) was comparable to, and Phase II completers (M = 20.9, SD = 22.3) higher than, behavioral programs of similar length (Brownell & Wadden, 1992). Using RE-AIM summary indices ranging from zero to 100, findings indicate the program has low reach and adoption (5.4 and 8.8), moderate short-term effectiveness (43.8), high component implementation (91.4), low to moderate long-term individual maintenance (21.2), and moderate to high site maintenance (77.8). Reasons for these index values, including site and individual performance barriers and facilitators, and six suggestions for improvement are explained using supporting data from index component calculations, site surveys, and focus groups to offer a comprehensive look at what works and potential explanations why