Economic impact of reducing treatment gaps in depression.

BackgroundMajor 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. MethodsA 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. ResultsThe expected costs with a detection gap of 69% and treatment gap of 50% were euro1236 in Germany, euro476 in Hungary, euro1413 in Italy, euro938 in Portugal, euro2093 in Sweden, and euro1496 in the UK. The incremental costs per QALY of reducing the detection gap to 50% ranged from euro2429 in Hungary to euro10,686 in Sweden. The figures for reducing the treatment gap to 25% ranged from euro3146 in Hungary to euro13,843 in Sweden. ConclusionsReducing 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.