Raymond Deng

Raymond Deng is advancing healthcare research while pursuing his medical degree at Stanford School of Medicine, building on his strong foundation in health policy from Harvard School of Public Health. His research has made significant contributions to understanding opioid use patterns, particularly through his study of the Veterans Health Administration database where he analyzed opioid prescription data from 1.3 million veterans to identify predictors of opioid discontinuation. His findings showed that 65% of patients continued opioid use after one year, with notable patterns among patients with schizophrenia and dementia. Beyond his academic pursuits, Deng's interest in addiction medicine is driven by personal experience, motivating his focus on prescription drug abuse and its relationship to heroin use. His recent work includes developing machine learning models to predict buprenorphine-naloxone treatment retention, achieving prediction accuracy comparable to clinical experts. As a medical student, he has participated in Stanford's annual Medical Student Research Symposium, where he has presented his findings on addiction medicine and contributed to the scholarly discourse on opioid use patterns and treatment outcomes