Bayesian network analysis of antidepressant treatment trajectories.

ABSTRACT: It is currently difficult to successfully choose the correct type of antidepressant for individual patients. To discover patterns in patient characteristics, treatment choices and outcomes, we performed retrospective Bayesian network analysis combined with natural language processing (NLP). This study was conducted at two mental healthcare facilities in the Netherlands. Adult patients admitted and treated with antidepressants between 2014 and 2020 were included. Outcome measures were antidepressant continuation, prescription duration and four treatment outcome topics: core complaints, social functioning, general well-being and patient experience, extracted through NLP of clinical notes. Combined with patient and treatment characteristics, Bayesian networks were constructed at both faciliti

SUBMITTER: Turner RJ 

PROVIDER: S-EPMC10209137 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature