A HARMONIZED APPROACH TO MENTAL HEALTH REFERENCE UNIT COST DEVELOPMENT USING PROVIDER-REPORTED PRIMARY DATA: EVIDENCE FROM THE STREAMLINE PROJECT
Author(s)
Susanne Mayer1, Sophie Diexer, Dr.2, Lazo Ilic, Dr.med.2, Michael Berger, Dr.2, Matthew Boersig McPhillips, BA, MSc2, Florian Bachner, Dr.3, Christoph Strohmaier, MSc4, Judit Simon, BA, BSc, MSc, DPhil, MD2.
1Vienna, Austria, 2Department of Health Economics, Center for Public Health, Medical University of Vienna, Vienna, Austria, 3Austrian National Public Health Institute / GÖG, Vienna, Austria, 4Austrian Institute for Health Technology Assessment, Vienna, Austria.
1Vienna, Austria, 2Department of Health Economics, Center for Public Health, Medical University of Vienna, Vienna, Austria, 3Austrian National Public Health Institute / GÖG, Vienna, Austria, 4Austrian Institute for Health Technology Assessment, Vienna, Austria.
OBJECTIVES: Evidence-based healthcare evaluation and service-delivery optimization require comprehensive and valid resource and cost data. While some European countries have developed unit cost lists, many still lack such data sources. To address Austria’s limited availability of robust secondary cost data, the STREAMLINE project aimed to collect primary cost data from service providers, using Vienna as a case study to develop methodologically harmonized reference unit costs (RUCs) for mental health services across sectors.
METHODS: An online survey was conducted in 2025 among all mental health service providers in Vienna (N=7293). Providers reported details on their services, patient contact volume, resources, and annual full costs. The costing section comprised two versions: one for organizations, based on the validated PECUNIA RUC Templates for service costs using organizational cost accounting data, and one for self-employed providers. The latter, a newly developed tool reviewed by methods experts, estimated economic costs using income tax returns, and alternatively, imputed provider salary and expenses. RUCs were calculated and externally validated using expert feedback and reimbursement data.
RESULTS: Of the 415 self-employed providers and 103 organizations that agreed to participate, 111 (26.7%) and 19 (18.4%), respectively, provided cost data. Based on these data, we developed 20 aggregated RUCs in the health and social care, justice and informal sector, complemented by taxonomy-based service descriptions. For self-employed providers, the imputed-salary-plus-expenses costing approach yielded robust estimates that were positively validated. The RUCs will be included in publicly accessible unit cost databases.
CONCLUSIONS: This study estimated new RUCs for multi-sectoral mental health services using existing and newly developed costing tools, filling critical gaps where reliable secondary cost data were lacking. Despite low response rates and survey distribution challenges, the primary data collection with its harmonized costing approaches and service descriptions provide a promising foundation for future evidence-informed healthcare policy-making in Austria and beyond.
METHODS: An online survey was conducted in 2025 among all mental health service providers in Vienna (N=7293). Providers reported details on their services, patient contact volume, resources, and annual full costs. The costing section comprised two versions: one for organizations, based on the validated PECUNIA RUC Templates for service costs using organizational cost accounting data, and one for self-employed providers. The latter, a newly developed tool reviewed by methods experts, estimated economic costs using income tax returns, and alternatively, imputed provider salary and expenses. RUCs were calculated and externally validated using expert feedback and reimbursement data.
RESULTS: Of the 415 self-employed providers and 103 organizations that agreed to participate, 111 (26.7%) and 19 (18.4%), respectively, provided cost data. Based on these data, we developed 20 aggregated RUCs in the health and social care, justice and informal sector, complemented by taxonomy-based service descriptions. For self-employed providers, the imputed-salary-plus-expenses costing approach yielded robust estimates that were positively validated. The RUCs will be included in publicly accessible unit cost databases.
CONCLUSIONS: This study estimated new RUCs for multi-sectoral mental health services using existing and newly developed costing tools, filling critical gaps where reliable secondary cost data were lacking. Despite low response rates and survey distribution challenges, the primary data collection with its harmonized costing approaches and service descriptions provide a promising foundation for future evidence-informed healthcare policy-making in Austria and beyond.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
EE47
Topic
Economic Evaluation, Health Technology Assessment, Methodological & Statistical Research
Topic Subcategory
Cost/Cost of Illness/Resource Use Studies
Disease
Mental Health (including addiction), No Additional Disease & Conditions/Specialized Treatment Areas