Robust Learning Approaches

Robust Learning Approaches for Assessing Effects and Effect Heterogeneity of Real World Antipsychotic Treatment Regimes in Elderly Persons with Schizophrenia

5R01MH130213-02

12/2022-10/2027

We will develop statistical approaches to extract scientifically robust and valid causal evidence of the effectiveness and adverse outcomes of antipsychotic drugs used by elderly adults with schizophrenia using large, observational, longitudinal databases. Our proposal has high public health relevance because (1) we focus on adults with illnesses associated with a heavy disease burden for whom drug treatments are a critical and often lifetime treatment component; (2) we assess the extent to which patient race/ethinicity and social contextual factors known to influence health behaviors may moderate outcomes; (3) we expand causal inference methodology to characterize the outcome effects of drug exposure and drug regimens, thus providing valuable information to optimize outcomes of long and complex exposures typical of usual care settings; and (4) we develop generalizable approaches to target parameters of general scientific interest.