PROJECT SUMMARY/ABSTRACT For the more than 12 million adults age 65 and older hospitalized each year in the United States (U.S.), the transition out of the hospital is an exceptionally vulnerable time in the care continuum. Post-discharge adverse events are common, and medications are the leading cause of such adverse events, which disproportionately affect older adults owing to greater degrees of comorbidity and polypharmacy, as well as altered pharmacokinetics and pharmacodynamics of drugs. Opioids in particular are consistently among the top medication classes to cause post-discharge adverse drug events (ADEs), and are prescribed to millions of older adults after hospital discharge each year. However, the specific nature of post-discharge opioid-related ADEs and patient- and prescribing-related predictors of such events have not been characterized. The broad goal of the proposed work is to address this knowledge gap by defining the incidence, characteristics, and predictors of post-discharge opioid-related ADEs in older adults. Such knowledge is crucial as a prelude to developing successful, targeted interventions to reduce the adverse consequences of opioid use, particularly for older adults during this highly vulnerable window of care. The Specific Aims of this proposal are: 1) To define the incidence and predictors of adverse events within 30 days of hospital discharge among older adults with an opioid claim in the week after discharge using a large national dataset. Using claims data from Medicare (the largest insurer for U.S. adults age 65+), we will determine the incidence and patient- and prescribing-related risk factors for post-discharge adverse events among older adults discharged on opioids, including death, opioid overdose, hospitalizations, emergency department visits, falls, delirium, nausea, and constipation. 2) To define the severity, functional consequences, and underlying causes of opioid-related clinically important medication errors (including preventable/ameliorable ADEs and potential ADEs) among older adults within 30 days of hospital discharge using prospectively collected clinical data from two large healthcare systems in Massachusetts. Data will be collected through chart review and a 30 day post-discharge telephone interview of patients discharged on opioids. The detailed clinical data will allow us to classify the adverse event as preventable/ameliorable, and identify systems improvements that could have prevented/ameliorated the event. The data sources used for each of these Aims will provide complementary information, allowing for a comprehensive examination of opioid-related post-discharge ADEs at both the “macroscopic” and “microscopic” level. A better understanding of the patient- and prescribing-related factors that place patients at highest risk for opioid-related post-discharge ADEs will inform improvements in healthcare systems to reduce the incidence and consequences of these potentially devastating events ...