Is it possible to optimize costs as scale-up of Choose to Move--an effective health-promoting intervention for older adults--proceeds?

Background Few studies have examined costs of implementing evidence-based interventions (EBIs) as scale-up proceeds. Across four phases, we co-adapted and scaled up an effective EBI designed to promote older adults’ health (Choose to Move; CTM). Following formative evaluation (2015), Phases 1–2 (2016-17) comprised the CTM pilot and early scale-up. For Phase 3 (2018-20), we adapted CTM to establish “best fit” and support broad scale-up. In response to COVID-19 (2020), we adapted CTM for virtual delivery. For Phase 4 (2020-22), we adapted CTM to reduce resource use. Objectives We aimed to 1) identify, measure, and value costs of implementing CTM across four phases (7 years) of scale-up; and 2) analyze change in implementation costs alongside changes in intervention effect sizes to assess cost-consequence trends from Phases 1–2 through Phase 4. Methods We conducted a trial-based cost and cost-consequence analysis of CTM Phases 1–2 through Phase 4 from a program provider perspective. Program costs were identified, measured, and valued using micro-costing techniques; variation in program cost was explored using scenario analyses. We compared Phase 4 intervention effects against those of Phases 1–2 and Phase 3 to examine how changes in implementation costs corresponded with changes in effect size. Results For Phases 1–2, total cost ($CDN, 2024) of CTM implementation was $863,559 for 55 programs (534 participants; $1,617/participant). Phase 3 costs were $1,564,446 for 165 programs (1668 participants; $938/participant). Phase 4 costs were $760,983 for 136 programs (1270 participants; $599/participant), a reduction of 63% and 36% compared with Phases 1–2 and Phase 3, respectively. Compared with Phases 1–2, Phase 4 had a greater positive effect on social isolation but effect sizes for physical activity, mobility and loneliness were reduced. Phase 4 had a greater positive effect on physical activity, mobility, social isolation, and loneliness (for those < 75 years), compared with Phase 3. Conclusion Costs associated with broad scale-up of EBIs are rarely investigated. We sought innovative ways to maximize impact of a health-promoting EBI, while minimizing costs. Our analysis highlights how strategic adaptations can enhance cost efficiency while improving intervention outcomes; this represents an emergent application of economic analysis within scale-up science.