Health economic analysis can lead to better prioritization in the treatment of eating disorders
In an op-ed in Dagens Medisin, Forhelse researcher Jonas Linkas explains how Markov models and health economic analyses can contribute to improved prioritization in treatment.
Eating disorders place a significant burden on patients, their families, and the healthcare system, and the need for evidence-based prioritization will likely become increasingly important in the future.
In the op-ed, Linkas describes how cost-effectiveness analyses can be used as a supplement to clinical assessments, with the aim of understanding how limited resources can be used in a way that yields the greatest possible health benefit.
Markov models
By using Markov models, the course of a disease is divided into states such as “ill,” “improvement,” and “relapse,” and the probabilities of moving between these states over time are described. Each state in the model has two consequences that accumulate over time: costs and health effects.
When a patient is in a state such as “ill,” this period is typically associated with higher treatment costs, whether for therapy, follow-up care, or hospitalization. When the patient is in better health, these costs decrease. Similarly, health effects are often measured in QALYs (quality-adjusted life years), where one year in perfect health equals 1, while poorer health results in a lower value.
When we follow a patient over several years, both costs and QALYs from each period are summed. In this way, a complete course of illness becomes an accumulated total of both resource use and health benefit.
Link to the chronicle in the health magazine Dagens Medisin (in norwegian):
Can mathematical models improve prioritization in the treatment of eating disorders?
Jonas Linkas also welcomes feedback and reflections from others interested in mental health, prioritization, and health economics. Jonas is affiliated with the UngMeistring project at Forhelse.