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Identifying Hidden “Signals” of Risks: A Case Study of Biomedical Research at Brigham and Women’s Hospital and Harvard Medical School

Sebastian Schneeweiss (Brigham and Women’s Hospital, Division of Pharmacoepidemiology and Pharmacoeconomics )
Precision Medicine Salon H-K
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In the U.S. alone, half of the population is taking one or more prescription drugs. Nearly four billion prescriptions are being filled annually. U.S. prescription drug sales are well over $300 billion per year and represent 10 percent of the total U.S. health expenditure (over $2.5 trillion)http://www.cdc.gov/nchs/fastats/hexpense.htm.

Providers, payers and patients need to understand the benefits and risks of prescription drugs. The risk and impact of patients consuming unsafe drugs, experiencing adverse reactions or misusing prescriptions is real. In the U.S., healthcare is producing hundreds of megabytes of data per patient, per year that, if utilized, could shed light on new benefits and hidden risks. Payers want to cover medications that are effective in their member population but have little information needed for multi-million dollar decisions. The ability to leverage technology to increase insights in to real-world drug effectiveness and uncover dangerous drugs more quickly, builds trust among consumers, pharma and the medical community, and ultimately will help patients and improve health outcomes.

Dr. Sebastian Schneeweiss, Harvard Medical School and Brigham and Women’s Hospital, will discuss how analytic capabilities for big data, based on principles of causal inference, are currently being used in his organization to make a big impact in drug safety and effectiveness. He is also Co-chair of the FDA’s Mini-Sentinel methods program, a post-market medical product safety assessment program.

With big data technology, the Brigham and Women’s Hospital team found it could immediately make full use of its large data sets and conduct multiple drug studies simultaneously. As a result the team has been able to uncover drug risk warning signals more quickly by executing queries 20 to 30 times faster, handling massive data volumes, including longitudinal data.

The Brigham and Women’s team is also making an impact to the industry with a recently developed semi-automated active monitoring system that uses sequential matched-cohort analysis to assess drug safety across a distributed network of longitudinal electronic healthcare data. Such a system would provide near-real-time monitoring of newly marketed medications regarding their effects in real-world setting.

The next step? Making analytics and data platforms sharable to build trust in data science and share insights in health outcomes analytics.

Sebastian Schneeweiss

Brigham and Women’s Hospital, Division of Pharmacoepidemiology and Pharmacoeconomics

Sebastian Schneeweiss is Associate Professor of Medicine and Epidemiology at Harvard Medical School and Vice Chief of the Division of Pharmacoepidemiology and Pharmacoeconomics of the Dept. of Medicine, Brigham and Women’s Hospital.

He is Principal Investigator of the BWH DEcIDE Research Center on Comparative Effectiveness Research and the DEcIDE Methods Center both funded by AHRQ and Director of the Harvard-Brigham Drug Safety Research Center funded by FDA/CDER. His research is funded by multiple NIH grants and focuses on the comparative effectiveness and safety of biopharmaceuticals and analytic methods to improve the validity of epidemiologic studies using complex healthcare databases particularly for newly marketed medical products. His work is published in high-ranking journals and was featured in Discover Magazine.

Dr. Schneeweiss is Past President of the International Society for Pharmacoepidemiology and is Fellow of the American College of Epidemiology, the American College of Clinical Pharmacology, and the International Society for Pharmacoepidemiology. He is voting consultant to the FDA Drug Safety and Risk Management Advisory Committee and member of the Methods Committee of the Patient Centered Outcomes Research Institute.

He received his medical training at the University of Munich Medical School and his doctoral degree in Pharmacoepidemiology from Harvard.

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