Using Electronic Health Records and Claims Databases for Rapid-Response Pharmacovigilance Studies

In a number of recent, high-profile situations, urgent drug-safety issues have been brought to the attention of regulators and pharmaceutical manufacturers in a way that requires a rapid assessment of available data. Other safety issues arise on a day-by-day basis, as a result of ongoing spontaneous reports. It is vital that a pharmaceutical manufacturer be able to quickly assess these issues on a sound statistical basis, in a way that eliminates bias due to confounding factors as much as possible. Recently, databases and software tools for investigating the relationship of drugs to safety issues have become available, which utilize large-scale, anonymous electronic-health-record (EHR) and medical-claims data. The large number of patients in these databases facilitates the use of statistical methods such as propensity score adjustment to reduce bias. This presentation will give an overview of these new tools and techniques for the non-statistician/epidemiologist.

Areas Covered in the seminar:

• What safety information is contained in EHR databases, and how is it extracted?
• Can you describe propensity score matching to a non-statistician, and explain how it reduces bias?
• What are the capabilities and limitations of this approach to safety studies?
• What are the next steps after analyzing a safety issue using these databases?
• How to I manage the resulting information?
• What procedures and policies are required to implement the analysis of these databases?
• What does the future hold for the use of these databases in drug safety?

Who will benefit:

• Safety and regulatory professionals who work with statisticians and epidemiologists in the analysis of safety signals.
• Executive decision-makers who are considering whether or not to incorporate E.H.R. and claims data as a component of pharmacovigilance, and if so, how.
• Safety consultants who currently rely primarily on tradtional medical review, and who are interested in adding the capability of analyzing E.H.R. and claims data.

Instructor Profile:

Alan Hochberg, is Vice President of Research for ProSanos Corp., a biomedical informatics company in Harrisburg, PA, where he is involved in the development and evaluation of algorithms for drug safety signal detection and investigation. He has worked as a technical professional in biostatistics, bioinformatics and biomedical engineering for the past 29 years. He joined ProSanos from DuPont, where he was developed pattern-matching methods for bacterial DNA fingerprints. Previously, he worked for Hologic, Inc., Ortho Diagnostics (J&J), and American Science & Engineering, and has participated in all phases of bioanalytical instrument development, from initial concept to final product validation, with an emphasis on signal detection, and on algorithms for the use of quantitative data in medical decision-making. Mr. Hochberg holds several patents on optical immunoassay devices, and on data analysis methods for biologically-derived signals. He received his B.S. degree in Electrical Engineering from Princeton University.

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