Dr. Weihsuan “Jenny” Lo-Ciganic wins UF College of Pharmacy Outstanding Publication in Clinical Science Research Award

The University of Florida College of Pharmacy has honored Weihsuan “Jenny” Lo-Ciganic, Ph.D., M.S., M.S.Pharm., an assistant professor in the department of pharmaceutical outcomes and policy, with the 2019 Outstanding Publication in Clinical Science Research Award. Lo-Ciganic received the award for her paper published in JAMA Network Open that reported on her and her co-authors’ investigation of five different machine learning approaches to predict opioid overdose in the subsequent three months among 560,057 fee-for-service Medicare beneficiaries who had more than one opioid prescription from 2011 to 2015. Lo-Ciganic and her team’s work used innovative approaches to address a significant public health issue.

Jenny Lo-CiganicOpioid prescription misuse and opioid-related overdose deaths have become a public health crisis.  Health care systems and payers have attempted to combat this epidemic, but the lack of accurate and efficient methods to identify individuals who are most at risk has led to broad interventions that are costly for payers and burdensome to patients. Accurately determining who is at ‘high-risk’ can reduce the costs and burdens and improve patient outcomes. Lo-Ciganic and her team’s modeling classified patients into low, medium, and high-risk subgroups with over 90% of the overdoses occurring in the high and medium-risk subgroups.

Lo-Ciganic’s paper is published in JAMA Network Open, one of the American Medical Association family journals and achieved a high impact (Almetric score: 135 reflecting its ranking in the top 5% of all research outputs scored by Altmetric as of August 2020). It has been mentioned by 159 tweets and five news outlets (e.g., EurekAlert!, MedicalXpress), and cited by 32 articles in the in less than 17 months since publication. This work led National Institute on Drug Abuse to recruit Lo-Ciganic as a member to their Clinical Trials Network Computer Intelligence (CI)/Artificial Intelligence (AI) Workgroup. Ultimately, the cumulative results of Lo-Ciganic’s efforts will inform the Centers for Medicare & Medicaid Services’, state agencies’ and their partners’ opioid use policies and aid in developing effective prevention strategies to curb the opioid epidemic in the U.S.