Value in health regional issues · 2026
Cost-Effectiveness of Pharmaceutical Care in Reducing Type 2 Diabetes Complication Risks: A Biomarker-Based Economic Model.
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Price Price U, Paganelli Maria O, Silveira de Almeida Campos Marilia, Leira Pereira Leonardo R
Аннотация
OBJECTIVES: Type 2 diabetes mellitus imposes substantial clinical and economic burdens in Brazil. Pharmaceutical care (PC), as an adjunct to usual care (UC), may improve clinical outcomes and optimize healthcare resource use. This study evaluated the cost-effectiveness of PC versus UC using biomarker-based outcomes.
METHODS: A cost-utility analysis was conducted from the healthcare system perspective over a 10-year time horizon, applying a 5% annual discount rate. Health outcomes were expressed in quality-adjusted life-years (QALYs), derived from changes in glycated hemoglobin (HbA1c), fasting glucose, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol (LDL-c). Incremental cost-effectiveness ratios were calculated for each biomarker. Probabilistic sensitivity analysis using 1000 Monte Carlo simulations assessed uncertainty, and cost-effectiveness acceptability curves were generated across willingness-to-pay thresholds of $16 000 (Brazilian threshold), $100 000, and $150 000 per QALY.
RESULTS: Ten-year incremental costs and QALYs between PC and UC were $1077.80 for 0.04, $7643.97 for 0.14, $9182.90 for 0.12, and $1530.49 for 0.70, for HbA1c, fasting glucose, high-density lipoprotein cholesterol, and LDL-c biomarkers, respectively. Probabilistic sensitivity analysis mean incremental cost-effectiveness ratios ranged from $5592.37 (LDL-c) to $37 620.32 (HbA1c), exceeding the $16 000 per QALY willingness-to-pay threshold. At this threshold, PC was cost-effective in 54% to 68% of iterations, rising to over 96% at $150 000 per QALY.
CONCLUSIONS: PC improved glycemic and lipid outcomes and demonstrated moderate to high cost-effectiveness across biomarkers, particularly for LDL-c. These findings suggest that integrating PC into routine diabetes management can deliver meaningful health gains at acceptable costs in Brazil. Although based on a single municipality, nationally standardized healthcare treatment protocols support broader applicability.
METHODS: A cost-utility analysis was conducted from the healthcare system perspective over a 10-year time horizon, applying a 5% annual discount rate. Health outcomes were expressed in quality-adjusted life-years (QALYs), derived from changes in glycated hemoglobin (HbA1c), fasting glucose, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol (LDL-c). Incremental cost-effectiveness ratios were calculated for each biomarker. Probabilistic sensitivity analysis using 1000 Monte Carlo simulations assessed uncertainty, and cost-effectiveness acceptability curves were generated across willingness-to-pay thresholds of $16 000 (Brazilian threshold), $100 000, and $150 000 per QALY.
RESULTS: Ten-year incremental costs and QALYs between PC and UC were $1077.80 for 0.04, $7643.97 for 0.14, $9182.90 for 0.12, and $1530.49 for 0.70, for HbA1c, fasting glucose, high-density lipoprotein cholesterol, and LDL-c biomarkers, respectively. Probabilistic sensitivity analysis mean incremental cost-effectiveness ratios ranged from $5592.37 (LDL-c) to $37 620.32 (HbA1c), exceeding the $16 000 per QALY willingness-to-pay threshold. At this threshold, PC was cost-effective in 54% to 68% of iterations, rising to over 96% at $150 000 per QALY.
CONCLUSIONS: PC improved glycemic and lipid outcomes and demonstrated moderate to high cost-effectiveness across biomarkers, particularly for LDL-c. These findings suggest that integrating PC into routine diabetes management can deliver meaningful health gains at acceptable costs in Brazil. Although based on a single municipality, nationally standardized healthcare treatment protocols support broader applicability.