Presentation (CTI)

OBJECTIVES: Economic evaluations of digital behavioral interventions commonly give detailed attention to clinical endpoints, while the implementation inputs that drive cost, scalability, and sustained use are specified less consistently. Using an insomnia intervention protocol for older adults as an index case, this methodological study aimed to develop a measurable resource-use and implementation parameter set for future trial-based and model-based economic evaluations.
METHODS: We used a protocol-guided approach to map parameters from prespecified study and implementation materials, including the intervention schedule, participant pathway, comparator specification, electronic case report form domains, app-log structure, and safety-monitoring plan. Candidate items were entered into a mapping matrix and grouped by HEOR function: costing, adherence measurement, outcome ascertainment, safety management, dropout handling, or scalability assessment. Parameters were retained when they could be measured prospectively, interpreted operationally, and used in trial-based or model-based economic evaluation.
RESULTS: The mapping yielded a six-domain parameter set for economic evaluation: intervention delivery, participant support, digital adherence, outcome ascertainment, safety management, and scalability. Delivery and support parameters included onboarding requirements, reminder intensity, content exposure, and investigator contact frequency. Digital adherence was defined using module completion, sleep-diary completion, and weekly app-activity logs. Outcome and safety parameters included post-assessment completion, missingness, adverse-event reporting, symptom-deterioration contacts, and discontinuation triggers. This structure distinguished adherence measures observed at the participant level from resource inputs borne by staff and health systems, and separated procedures specific to the trial from resources that may be needed in routine implementation.
CONCLUSIONS: This protocol-driven parameter set targets a recurring weakness in economic evaluations of digital behavioral interventions: implementation inputs that affect cost, adherence, and scalability are often insufficiently specified. Collecting these parameters prospectively may allow for more transparent costing, more rigorous interpretation of adherence-dependent outcomes, and better transferability of future economic evaluations in older-adult insomnia care.