A Digital Behavioral Weight Gain Prevention Intervention in Primary Care Practice: Cost and Cost-Effectiveness Analysis.
Obesity is one of the largest drivers of health care spending but nearly half of the population with obesity demonstrate suboptimal readiness for weight loss treatment. Black women are disproportionately likely to have both obesity and limited weight loss readiness. However, they have been shown to be receptive to strategies that prevent weight gain.
The aim of this study was to evaluate the costs and cost-effectiveness of a digital weight gain prevention intervention (Shape) for black women. Shape consisted of adaptive telephone-based coaching by health system personnel, a tailored skills training curriculum, and patient self-monitoring delivered via a fully automated interactive voice response system.
A cost and cost-effectiveness analysis based on a randomized clinical trial of the Shape intervention was conducted from the payer perspective. Costs included those of delivering the program to 91 intervention participants in the trial and were summarized by program elements: self-monitoring, skills training, coaching, and administration. Effectiveness was measured in quality-adjusted life years (QALYs). The primary outcome was the incremental cost per QALY of Shape relative to usual care.
Shape cost an average of US $758 per participant. The base-case model in which quality of life benefits decay linearly to zero 5 years post intervention cessation, generated an incremental cost-effectiveness ratio (ICER) of US $55,264 per QALY. Probabilistic sensitivity analyses suggest an ICER below US $50,000 per QALY and US $100,000 per QALY in 39% and 98% of simulations, respectively. Results are highly sensitive to durability of benefits, rising to US $165,730 if benefits end 6 months post intervention.
Results suggest that the Shape intervention is cost-effective based on established benchmarks, indicating that it can be a part of a successful strategy to address the nation's growing obesity epidemic in low-income at-risk communities.
Krishnan, A; Finkelstein, EA; Levine, E; Foley, P; Askew, S; Steinberg, D; Bennett, GG
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