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Updated: Dec 18, 2025

Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research
Published on: January 5, 2024
Cost-effectiveness of a collaborative care program for managing major depression and chronic musculoskeletal pain in
Enric Aragonès1, Eduardo Sánchez-Iriso2, Germán López-Cortacans1
1Institut Universitari d'Investigació en Atenció Primària Jordi Gol (IDIAP Jordi Gol), Barcelona, Spain; Atenció Primària Camp de Tarragona, Institut Català de la Salut, Tarragona, Spain.
Background:
We designed a collaborative care program for the integrated management of chronic musculoskeletal pain and depression, which frequently coexist in primary care patients. The aim of this study was to evaluate the cost-effectiveness of this program compared with care as usual.
Methods:
We performed a cost-effectiveness analysis alongside a randomized clinical trial. Results were monitored over a 12-month period. The primary outcome was the incremental cost-effectiveness ratio (ICER). We performed cost-effectiveness analyses from the perspectives of the healthcare system and society using an intention-to-treat approach with imputation of missing values.
Results:
We evaluated 328 patients (167 in the intervention group and 161 in the control group) with chronic musculoskeletal pain and major depression at baseline. From the healthcare system perspective, the mean incremental cost was €234 (p = .17) and the mean incremental effectiveness was 0.009 QALYs (p = .66), resulting in an ICER of €23,989/QALY. Costs from the societal perspective were €235 (p = .16), yielding an ICER of €24,102/QALY. These estimates were associated with a high degree of uncertainty illustrated on the cost-effectiveness plane.
Conclusions:
Contrary to our expectations, the collaborative care program had no significant effects on health status, and although the additional costs of implementing the program compared with care as usual were not high, we were unable to demonstrate a favorable cost-effectiveness ratio, largely due to the high degree of uncertainty surrounding the estimates.
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