M Valenstein1, S Vijan, J E Zeber, K Boehm, A Buttar. 1. Health Services Research and Development, Department of Veterans Affairs Medical Center, Box 130170, Ann Arbor, MI 48113-0170, USA.
Abstract
BACKGROUND: Depressive disorders are common in primary care and cause substantial disability, but they often remain undiagnosed. Screening is a frequently proposed strategy for increasing detection of depression. OBJECTIVE: To examine the cost-utility of screening for depression compared with no screening. DESIGN: Nonstationary Markov model. DATA SOURCES: The published literature. TARGET POPULATION: Hypothetical cohort of 40-year-old primary care patients. TIME HORIZON: Lifetime. PERSPECTIVE: Health care payer and societal. INTERVENTIONS: Self-administered questionnaire followed by provider assessment. OUTCOME MEASURES: Costs and quality-adjusted life-years (QALYs). RESULTS OF BASE-CASE ANALYSIS: Compared with no screening, the cost to society of annual screening for depression in primary care patients is $192 444/QALY. Screening every 5 years and one-time screening cost $50 988/QALY and $32 053/QALY, respectively, compared with no screening. From the payer perspective, the cost of annual screening is $225 467. RESULTS OF SENSITIVITY ANALYSES: Cost-utility ratios are most sensitive to the prevalence of major depression, the costs of screening, rates of treatment initiation, and remission rates with treatment. In Monte Carlo sensitivity analyses, the cost-utility of annual screening is less than $50 000/QALY only 2.2% of the time. In multiway analyses, four model variables must be changed to extreme values for the cost-utility of annual screening to fall below $50 000/QALY, but a change in only one variable increases the cost-utility of one-time screening to more than $50 000/QALY. One-time screening is more robustly cost-effective if screening costs are low and effective treatments are being given. CONCLUSIONS: Annual and periodic screening for depression cost more than $50 000/QALY, but one-time screening is cost-effective. The cost-effectiveness of screening is likely to improve if treatment becomes more effective.
BACKGROUND:Depressive disorders are common in primary care and cause substantial disability, but they often remain undiagnosed. Screening is a frequently proposed strategy for increasing detection of depression. OBJECTIVE: To examine the cost-utility of screening for depression compared with no screening. DESIGN: Nonstationary Markov model. DATA SOURCES: The published literature. TARGET POPULATION: Hypothetical cohort of 40-year-old primary care patients. TIME HORIZON: Lifetime. PERSPECTIVE: Health care payer and societal. INTERVENTIONS: Self-administered questionnaire followed by provider assessment. OUTCOME MEASURES: Costs and quality-adjusted life-years (QALYs). RESULTS OF BASE-CASE ANALYSIS: Compared with no screening, the cost to society of annual screening for depression in primary care patients is $192 444/QALY. Screening every 5 years and one-time screening cost $50 988/QALY and $32 053/QALY, respectively, compared with no screening. From the payer perspective, the cost of annual screening is $225 467. RESULTS OF SENSITIVITY ANALYSES: Cost-utility ratios are most sensitive to the prevalence of major depression, the costs of screening, rates of treatment initiation, and remission rates with treatment. In Monte Carlo sensitivity analyses, the cost-utility of annual screening is less than $50 000/QALY only 2.2% of the time. In multiway analyses, four model variables must be changed to extreme values for the cost-utility of annual screening to fall below $50 000/QALY, but a change in only one variable increases the cost-utility of one-time screening to more than $50 000/QALY. One-time screening is more robustly cost-effective if screening costs are low and effective treatments are being given. CONCLUSIONS: Annual and periodic screening for depression cost more than $50 000/QALY, but one-time screening is cost-effective. The cost-effectiveness of screening is likely to improve if treatment becomes more effective.
Authors: Michel Joffres; Alejandra Jaramillo; James Dickinson; Gabriela Lewin; Kevin Pottie; Elizabeth Shaw; Sarah Connor Gorber; Marcello Tonelli Journal: CMAJ Date: 2013-05-13 Impact factor: 8.262