Resource Pack: Mental Health and Modeling
2018
This resource pack, curated by the Center for Health Decision Science, features resources on modeling approaches applied to mental health. We aim to provide an overview of different techniques to guide researchers and practitioners in applying decision science and economic modeling to this public health challenge.
More specifically, this resource pack contains review articles comparing different modeling techniques in the evaluation of treatments for depression, bipolar disorder and schizophrenia. The majority of articles in this pack however are applied modeling techniques (i.e., decision trees, Markov [cohort and microsimulation] models, and discrete event simulation models) over a broad range of mental health disorders. Some examples of applied modeling approaches are: 1) a Markov cohort model developed to compare the cost-effectiveness of different modalities of psychotherapy for cluster B personality disorders, 2) a discrete event simulation model used to compare atypical antipsychotics to conventional antipsychotics for the treatment of schizophrenia, and 3) a decision tree model built to compare antidepressants, psychological therapy and a combination of the two in treating moderate to severe depression in secondary care in the UK.
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Source:
Resource Pack: Mental Health and Modeling. Center for Health Decision Science, Harvard T.H. Chan School of Public Health 2018. http://repository.chds.hsph.harvard.edu/repository/collection/resource-pack-mental-health-and-modeling