Objective. Screening has an essential role in preventive medicine. Ideally, screening tools detect patients early enough to manage the disease and reduce symptoms. We aimed to determine the cost-effectiveness of routine screening schedules. Methods. We used a discrete-time nonstationary Markov model to simulate the progression of depression. We adopted annual transition probabilities, which were dependent on patient histories, such as the number of previous episodes, treatment status, and time spent without treatment state based on the available data. We used Monte Carlo techniques to simulate the stochastic model for 20 years or during the lifetime of individuals. Baseline and screening scenario models with screening frequencies of annual, 2-year, and 5-year were compared based on incremental cost-effectiveness ratios (ICER). Results. In the general population, all screening strategies were cost-effective compared to the baseline. However, male and female populations differed based on cost over quality-adjusted life years (QALY). Females had lower ICERs, and annual screening had the highest ICER for females, with 11,134 $/QALY gained. In contrast, males had around three times higher ICER, with annual screening costs of 34,065$/QALY gained. Conclusions. Considering the high lifetime prevalence and recurrence rates of depression, detection and prevention efforts can be one critical cornerstone to support required care. Our analysis combined the expected benefits and costs of screening and assessed the effectiveness of screening scenarios. We conclude that routine screening is cost-effective for all age groups of females and young, middle-aged males. Male population results are sensitive to the higher costs of screening.
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