Economic Evaluation of Tandem Mass Spectrometry Screening in California

Abstract

OBJECTIVE. On the basis of California’s experience implementing a pilot tandem mass spectrometry (MS/MS) screening program, an economic evaluation was conducted to determine the economic benefits and costs of a statewide MS/MS screening program. METHODS. Cost-effectiveness, benefit/cost, and cost-utility analyses were conducted with a base-case set of assumptions. The base-case assumptions were varied by using a set of more-favorable and less-favorable assumptions to test the robustness of the analysis findings. RESULTS. The total estimated, annualized, incremental costs of MS/MS screening of 540000 births in California were nearly $5.7 million; 83 affected newborns would be identified. Screening would reduce the expected lifetime costs of medical care for affected newborns by $7.2 million ($9.0 million in the best-case scenario and $1.8 million in the worst-case scenario). When all program costs and savings were considered, screening saved $1.5 million ($3.4 million saved in the best-case scenario and $3.8 million additional costs in the worst-case scenario). With only incremental program costs, the cost per life saved was $708000 and the cost per case detected was $68000. With consideration of the projected lifetime medical care costs, the total cost per case detected was $132000. MS/MS screening produced a benefit/cost ratio of $9.32 ($11.67 with the best-case set of assumptions and $4.34 with the worst-case set of assumptions). In this analysis, the benefits of screening exceeded total program costs by $47.1 million (the net incremental benefit). In the worst-case scenario, the net incremental benefit of screening was $18.9 million. Screening saved 949 quality-adjusted life-years (QALYs) and saved $1628 per QALY in the base case analysis. Under the worst-case scenario, the cost per QALY was $14922. CONCLUSIONS. We found that the benefits of MS/MS screening outweighed the costs and that the net benefits were significant and robust in various scenarios with various conservative underlying assumptions.