Economic impact of reducing treatment gaps in depression

Abstract

Abstract Background Major depressive disorder (MDD) is highly prevalent across Europe. While evidence-based treatments exist, many people with MDD have their condition undetected and/or untreated. This study aimed to assess the cost-effectiveness of reducing treatment gaps using a modeling approach. Methods A decision-tree model covering a 27-month time horizon was used. This followed a care pathway where MDD could be detected or not, and where different forms of treatment could be provided. Expected costs pertaining to Germany, Hungary, Italy, Portugal, Sweden, and the UK were calculated and quality-adjusted life years (QALYs) were estimated. The incremental costs per QALY of reducing detection and treatment gaps were estimated. Results The expected costs with a detection gap of 69% and treatment gap of 50% were €1236 in Germany, €476 in Hungary, €1413 in Italy, €938 in Portugal, €2093 in Sweden, and €1496 in the UK. The incremental costs per QALY of reducing the detection gap to 50% ranged from €2429 in Hungary to €10,686 in Sweden. The figures for reducing the treatment gap to 25% ranged from €3146 in Hungary to €13,843 in Sweden. Conclusions Reducing detection and treatment gaps, and maintaining current patterns of care, is likely to increase healthcare costs in the short term. However, outcomes are improved, and reducing these gaps to 50 and 25%, respectively, appears to be a cost-effective use of resources.

Keywords

• cost
• depression
• economics
• treatment
• gaps