Spyros Kolovos1, Robin M F Kenter2, Judith E Bosmans3, Aartjan T F Beekman4, Pim Cuijpers2, Robin N Kok5, Annemieke van Straten2. 1. Department of Health Sciences and the EMGO Institute for Health and Care Research, Faculty of Earth and Life Sciences, VU University, Amsterdam, The Netherlands. Electronic address: s.kolovos@vu.nl. 2. Department of Clinical Psychology and the EMGO Institute for Health and Care Research, Faculty of Earth and Life Sciences, VU University, Amsterdam, The Netherlands. 3. Department of Health Sciences and the EMGO Institute for Health and Care Research, Faculty of Earth and Life Sciences, VU University, Amsterdam, The Netherlands. 4. Department of Psychiatry and the EMGO Institute for Health and Care Research, VU Medical Center and GGZ inGeest, Amsterdam, The Netherlands. 5. Department of Clinical Psychology and the EMGO Institute for Health and Care Research, Faculty of Earth and Life Sciences, VU University, Amsterdam, The Netherlands; National Institute for Mental Health Research, The Australian National University, Australia.
Abstract
BACKGROUND: Previous studies have demonstrated the effectiveness of Internet-based interventions for depression in comparison with usual care. However, evidence on the cost-effectiveness of these interventions when delivered in outpatient clinics is lacking. The aim of this study was to estimate the cost-effectiveness of an Internet-based problem-solving guided self-help intervention in comparison with enhanced usual care for outpatients on a waiting list for face-to-face treatment for major depression. After the waiting list period, participants from both groups received the same treatment at outpatient clinics. METHODS: An economic evaluation was performed alongside a randomized controlled trial with 12 months follow-up. Outcomes were improvement in depressive symptom severity (measured by CES-D), response to treatment and Quality-Adjusted Life-Years (QALYs). Statistical uncertainty around cost differences and incremental cost-effectiveness ratios were estimated using bootstrapping. RESULTS:Mean societal costs for the intervention group were €1579 higher than in usual care, but this was not statistically significant (95% CI - 1395 to 4382). Cost-effectiveness acceptability curves showed that the maximum probability of the intervention being cost-effective in comparison with usual care was 0.57 at a ceiling ratio of €15,000/additional point of improvement in CES-D, and 0.25 and 0.30 for an additional response to treatment and an extra QALY respectively, at a ceiling ratio of €30,000. Sensitivity analysis showed that from a mental healthcare provider perspective the probability of the intervention being cost-effective was 0.68 for a ceiling ratio of 0 €/additional unit of effect for the CES-D score, response to treatment and QALYs. As the ceiling ratio increased this probability decreased, because the mean costs in the intervention group were lower than the mean costs in the usual care group. LIMITATIONS: The patients in the intervention group showed low adherence to the Internet-based treatment. It is possible that greater adherence would have led to larger clinical effects. CONCLUSIONS: Offering an Internet-based intervention to depressed outpatients on waiting list for face-to-face treatment was not considered cost-effective in comparison with enhanced usual care from a societal perspective. There was a high probability of the intervention being cost-effective in comparison with enhanced usual care from the perspective of the mental healthcare provider.
RCT Entities:
BACKGROUND: Previous studies have demonstrated the effectiveness of Internet-based interventions for depression in comparison with usual care. However, evidence on the cost-effectiveness of these interventions when delivered in outpatient clinics is lacking. The aim of this study was to estimate the cost-effectiveness of an Internet-based problem-solving guided self-help intervention in comparison with enhanced usual care for outpatients on a waiting list for face-to-face treatment for major depression. After the waiting list period, participants from both groups received the same treatment at outpatient clinics. METHODS: An economic evaluation was performed alongside a randomized controlled trial with 12 months follow-up. Outcomes were improvement in depressive symptom severity (measured by CES-D), response to treatment and Quality-Adjusted Life-Years (QALYs). Statistical uncertainty around cost differences and incremental cost-effectiveness ratios were estimated using bootstrapping. RESULTS: Mean societal costs for the intervention group were €1579 higher than in usual care, but this was not statistically significant (95% CI - 1395 to 4382). Cost-effectiveness acceptability curves showed that the maximum probability of the intervention being cost-effective in comparison with usual care was 0.57 at a ceiling ratio of €15,000/additional point of improvement in CES-D, and 0.25 and 0.30 for an additional response to treatment and an extra QALY respectively, at a ceiling ratio of €30,000. Sensitivity analysis showed that from a mental healthcare provider perspective the probability of the intervention being cost-effective was 0.68 for a ceiling ratio of 0 €/additional unit of effect for the CES-D score, response to treatment and QALYs. As the ceiling ratio increased this probability decreased, because the mean costs in the intervention group were lower than the mean costs in the usual care group. LIMITATIONS: The patients in the intervention group showed low adherence to the Internet-based treatment. It is possible that greater adherence would have led to larger clinical effects. CONCLUSIONS: Offering an Internet-based intervention to depressed outpatients on waiting list for face-to-face treatment was not considered cost-effective in comparison with enhanced usual care from a societal perspective. There was a high probability of the intervention being cost-effective in comparison with enhanced usual care from the perspective of the mental healthcare provider.
Authors: Lina Gega; Dina Jankovic; Pedro Saramago; David Marshall; Sarah Dawson; Sally Brabyn; Georgios F Nikolaidis; Hollie Melton; Rachel Churchill; Laura Bojke Journal: Health Technol Assess Date: 2022-01 Impact factor: 4.014
Authors: Spyros Kolovos; Johanna M van Dongen; Heleen Riper; Claudia Buntrock; Pim Cuijpers; David D Ebert; Anna S Geraedts; Robin M Kenter; Stephanie Nobis; Andrea Smith; Lisanne Warmerdam; Jill A Hayden; Maurits W van Tulder; Judith E Bosmans Journal: Depress Anxiety Date: 2018-01-12 Impact factor: 6.505