Stephanie Nobis1, David Daniel Ebert2, Dirk Lehr3, Filip Smit4, Claudia Buntrock5, Matthias Berking6, Harald Baumeister7, Frank Snoek8, Burkhardt Funk9, Heleen Riper10. 1. Division of Online Health Training,Innovation Incubator,Leuphana University of Lueneburg and Department for Gerontology,University of Vechta,Germany. 2. Division of Online Health Training,Innovation Incubator,Leuphana University of Lueneburg,Germany,Department for Health Care Policy,Harvard University,Boston,USAandDepartment of Clinical Psychology and Psychotherapy,University of Erlangen-Nuernberg,Germany. 3. Division of Online Health Training, Innovation Incubator,Leuphana University of Lueneburg,Germany. 4. Department of Public Mental Health,Trimbos-instituut (Netherlands Institute of Mental Health and Addiction),Utrecht,Department of Epidemiology and Biostatistics,EMGO+ Institute for Health and Care Research,VU University Amsterdam Medical Centre and Department of Clinical Psychology,VU University Amsterdam,The Netherlands. 5. Division of Online Health Training,Innovation Incubator,Leuphana University of Lueneburg,GermanyandDepartment of Clinical Psychology,VU University Amsterdam,The Netherlands. 6. Division of Online Health Training,Innovation Incubator,Leuphana University of Lueneburg and Department of Clinical Psychology and Psychotherapy,University of Erlangen-Nuernberg,Germany. 7. Department of Clinical Psychology and Psychotherapy,Institute of Psychology and Education,University of Ulm,Germany. 8. Department of Medical Psychology,VU University Medical Center Amsterdam and Department of Medical Psychology,Academic Medical Center,Amsterdam,The Netherlands. 9. Division of Online Health Training,Innovation Incubator,Leuphana University of Lueneburg,Germany. 10. Division of Online Health Training,Innovation Incubator,Leuphana University of Lueneburg,Germany,Department of Clinical Psychology,VU University Amsterdam,The NetherlandsandInstitute of Telepsychiatry,University of Southern Denmark,Odense,Denmark.
Abstract
BACKGROUND: Web-based interventions are effective in reducing depression. However, the evidence for the cost-effectiveness of these interventions is scarce.AimsThe aim is to assess the cost-effectiveness of a web-based intervention (GET.ON M.E.D.) for individuals with diabetes and comorbid depression compared with anactive control group receiving web-based psychoeducation. METHOD: We conducted a cost-effectiveness analysis with treatment response as the outcome and a cost-utility analysis with quality-adjusted life-years (QALYs) alongside a randomised controlled trial with 260 participants. RESULTS: At a willingness-to-pay ceiling of €5000 for a treatment response, the intervention has a 97% probability of being regarded as cost-effective compared with the active control group. If society is willing to pay €14 000 for an additional QALY, the intervention has a 51% probability of being cost-effective. CONCLUSIONS: This web-based intervention for individuals with diabetes and comorbid depression demonstrated a high probability of being cost-effective compared with an active control group.Declaration of interestS.N., D.D.E., D.L., M.B. and B.F. are stakeholders of the Institute for Online Health Trainings, which aims to transfer scientific knowledge related to this research into routine healthcare.
RCT Entities:
BACKGROUND: Web-based interventions are effective in reducing depression. However, the evidence for the cost-effectiveness of these interventions is scarce.AimsThe aim is to assess the cost-effectiveness of a web-based intervention (GET.ON M.E.D.) for individuals with diabetes and comorbid depression compared with an active control group receiving web-based psychoeducation. METHOD: We conducted a cost-effectiveness analysis with treatment response as the outcome and a cost-utility analysis with quality-adjusted life-years (QALYs) alongside a randomised controlled trial with 260 participants. RESULTS: At a willingness-to-pay ceiling of €5000 for a treatment response, the intervention has a 97% probability of being regarded as cost-effective compared with the active control group. If society is willing to pay €14 000 for an additional QALY, the intervention has a 51% probability of being cost-effective. CONCLUSIONS: This web-based intervention for individuals with diabetes and comorbid depression demonstrated a high probability of being cost-effective compared with an active control group.Declaration of interestS.N., D.D.E., D.L., M.B. and B.F. are stakeholders of the Institute for Online Health Trainings, which aims to transfer scientific knowledge related to this research into routine healthcare.
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