Developing a Health-Economic Model to Assess Cost-Effectiveness of Preventive Interventions for Children of Parents With Mental Illness or Substance Use Disorder.

OBJECTIVES: Children of parents with a mental illness (COPMI) face a higher risk of developing mental disorders, leading to significant long-term societal and health-related costs. Although preventive interventions exist, few studies assess their cost-effectiveness, and, to our knowledge, none model long-term outcomes. This study aims to develop a Markov model to evaluate the cost-effectiveness of preventive interventions for COPMI in The Netherlands.

METHODS: A decision-analytic model was constructed using data from the Avon Longitudinal Study of Parents and Children. The model simulates COPMI progression over time, with health states including healthy, depression/anxiety, comorbidity, remission, and death. The time horizon spans 28 years, from ages 7 to 35, and outcomes are evaluated from both healthcare and societal perspectives. Results are expressed as total costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios. A group-based cognitive behavioral therapy (GB-CBT) intervention was evaluated against a reference scenario.

RESULTS: The preventive CBT intervention yielded an additional 0.02 QALYs at an additional cost of €188 per patient, resulting in an incremental cost-effectiveness ratio of €9495 per QALY. The intervention had a 74% probability of being cost-effective at a willingness-to-pay threshold of €20 000 per QALY.

CONCLUSIONS: The Markov model provides a flexible tool for evaluating the cost-utility of user-defined COPMI interventions to support informed decision making in mental health care. It is freely available for academic purposes from the authors upon request. Results suggest GB-CBT may be a cost-effective strategy for preventing mental disorders in COPMI.