UCI researchers have developed recommended practices for evaluating evidence generated by adverse drug event studies that use electronic health record databases. Their findings are published online in the Journal of the American College of Clinical Pharmacy. The availability of large EHR databases offers opportunities for big data analytics and machine learning to be applied in precision medicine, disease risk prediction and clinical decision support research, but there are associated limitations and caveats. The team conducted a systematic review of current practices for conducting adverse drug event studies utilizing EHR databases and developed a set of recommended practices to help improve quality. “Our recommendations will be useful to evaluate the evidence generated from adverse drug event studies,” said lead author Quinton Ng, a Ph.D. student in UCI’s pharmacological sciences program. “Our review caters to a wide audience, including clinicians, health informaticians and other nonclinician scientists, to improve their knowledge in using EHR data for research studies with an aim to improve patient outcomes.” Other UCI School of Pharmacy & Pharmaceutical Sciences team members were undergraduate students Emily Dang, Lijie Chen, Mary Nguyen, Michael Nguyen, Sarah Samman and Tiffany Nguyen; Christine Cadiz, Pharm.D., corresponding author and assistant clinical professor of health sciences; Lee Nguyen, Pharm.D., associate clinical professor of health sciences; and Alexandre Chan, Pharm.D., corresponding author and founding chair and professor of clinical pharmacy practice.