Cost-effectiveness of a collaborative care model among patients with type 2 diabetes and depression in India
To assess the cost-effectiveness of collaborative versus usual care in adults with poorly-controlled type 2 diabetes and depression in India.
Research Design and Methods
We performed a within-trial cost-effectiveness analysis of a 24-month parallel, open-label, pragmatic randomized clinical trial at four urban clinics in India from multipayer and societal perspectives. The trial randomized 404 patients with poorly-controlled type 2 diabetes (HbA1c≥8.0% or systolic BP≥140mmHg or LDL-c≥130mg/dl) and depressive symptoms (PHQ-9≥10) to collaborative care (support from non-physician care coordinators, electronic registers, and specialist-supported case review) for 12 months, followed by 12 months usual care or 24 months usual care. We calculated incremental cost-effectiveness ratios (ICER) in Indian rupees (INR) and international dollars (Int’l) and the probability of cost-effectiveness using quality-adjusted life years (QALYs) and depression-free days (DFDs).
From a multipayer perspective, collaborative care costed additional INR309,558 (Int’l-$15,344) per QALY and additional INR290.2 (Int’l-$14.4) per DFD gained compared to usual care. The probability of cost-effectiveness was 56.4% using a willingness-to-pay of INR336,000 (Int’l-$16,654) per QALY (~3-times per-capita GDP). The willingness-to-pay per DFD to achieve a probability of cost-effectiveness >95% was INR401.6 (Int’l-$ 19.9). From a societal perspective, cost-effectiveness was marginally lower. In sensitivity analyses, integrating collaborative care in clinical workflows reduced incremental costs by ~47% (ICER: 162,689/QALY; cost-effectiveness probability: 89.4%) but cost-effectiveness decreased when adjusting for baseline values.
Collaborative care for patients with type 2 diabetes and depression in urban India can be cost-effective, especially when integrated in clinical workflows. Long-term cost-effectiveness might be more favorable. Scalability across lower- and middle-income country settings depends on heterogeneous contextual factors.