164-2013: Using PROC GENMOD to Investigate Drug Interactions: Beta Blockers and Beta Agonists and Their Effect on Hospital Admissions

Every year, more than half a million adverse reactions to drugs are reported to the FDA. This paper is a real-world, large-scale review of beta blockers and beta agonist usage. We use New York City public hospitals’ records to investigate whether interactions of beta blockers and beta agonists are associated with increased hospital inpatient admissions, a common indicator of health care quality. PROC GENMOD in SAS provides a variety of count data models, including Poisson regression and Negative Binomial regression. During clinical trials, many patients are excluded by strict selection criteria. This includes young patients, older patients, and patients with history of multiple illnesses. These patients tend to have higher hospital inpatient admission rates. These patients may be prescribed FDA-approved drugs in combinations they could not have received as part of the clinical trials. We examine whether untested uses of beta blockers and beta agonists are associated with changes in admission rates.