A pre-implementation simulation framework informed by time-driven activity-based costing for provider-side resource planning in preventive brain MRI screening in Japan

Preventive brain magnetic resonance imaging screening of asymptomatic people has uncertain clinical benefit and can generate incidental findings, downstream healthcare utilisation, psychological effects, and ethical concerns. In Japan, Brain Dock is a self-pay magnetic resonance imaging and magnetic resonance angiography checkup. Facilities considering a programme need a transparent model for provider-side resource planning before launch. We developed a pre-implementation simulation framework informed by time-driven activity-based costing for that purpose. We constructed illustrative tiers from public guideline, price, and time-driven activity-based costing sources. Assumed capacity cost rates, activity times, and direct inputs were used to calculate per-case scenario costs, incremental costs, magnetic resonance imaging minutes, and the monthly volume required to cover specified launch overhead. Structural plausibility and internal consistency were assessed through guideline mapping, public course comparison, transparent input classification, and logic checks; no empirical validation was performed. Cognitive-screening workload, 3-, 6-, and 12-month launch horizons, and computer-aided detection scenarios were examined. Under base-case assumptions, scenario costs were approximately 12.5 thousand Japanese yen for Tier 1a, 15.6 thousand yen for Tier 1b, 23.6 thousand yen for Tier 2 Basic, and 24.1 thousand yen for Tier 2 Cognitive. The 500-yen increment for cognitive screening represented administration only; expanded workflows increased it to 850 yen, 2125 yen, or 4225 yen. At 20 cases per month over the 6-month launch horizon, modelled net monthly contribution was 98.3 thousand yen for Tier 1b priced at 28,000 yen and 197.2 thousand yen for Tier 2 Cognitive priced at 44,000 yen; the corresponding launch-overhead thresholds were 13 and 11 cases per month. Shorter horizons increased these thresholds. Computer-aided detection and input-uncertainty outputs depended on the assumed volume, reading-time change, and parameter distributions. By linking modular service design with activity time, capacity cost rates, launch overhead, and post-launch data requirements, the framework adapts time-driven activity-based costing concepts to the pre-implementation phase. It supports transparent provider-side resource planning and prioritises local measurements for subsequent empirical costing. Clinical appropriateness and the benefit-harm balance of Brain Dock require separate evaluation, followed by local time-study and invoice-based validation after implementation. Not applicable.