An Introduction to Analytics in Healthcare: Pharma and Health Plans
The math and statistics that graduate students and postdoctoral scientists use in their day-to-day research are the same types of analyses, applied to a slightly different data set, that are used every day in business. In the simplest terms, the business side of Healthcare can be split into 3 groups, Pharma, Payers, and Providers. Pharma makes the drugs, Payers pay for drugs (and medical interventions), and providers are the MDs and satellites of support services that orbit them. This course will provide a basic introduction to the structure of Pharmaceutical Manufacturers and Payers (including PBMs and Health Plans), and will begin a (non-exhaustive) dive into the types of statistics and analytics that are being used every day to drive strategy, to make business decisions, to help contain healthcare costs, and to predict future opportunities and pitfalls.
Course Fee: $10.
Dates & Times
February 26th and March 5th, 12:30 – 4 pm
Introduction to Pharma and Pharma Analytics
The pharmaceutical industry is extremely complex, and the inner workings of the pharmaceutical and biotechnology companies are incredibly dynamic. Even seasoned industry professionals can find it difficult to understand the activities and interdependencies across all key functions within a pharmaceutical company. With that in mind, this “course” will provide a *basic* introduction to the organizational structure of the typical Pharmaceutical Manufacturer and will use that information as a launching pad into the kinds of data-driven analytics that Pharma uses every day to make some of its most important decisions.
Introduction to Commercial Payers (Health Plans and PBMS) and Payer Analytics
The United States health care system relies heavily on private (Commercial) health insurance to provide cost coverage for most Americans. While Health Insurance Companies cover medical expenses, Pharmacy Benefit Managers (PBMs) cover Pharmacy (drug) benefits. This course will provide an introduction to the organization structure of both the typical health plan and pharmacy benefit manager as well as providing some insights into the kinds of data-driven analytics that Payers use in their day-to-day business decision making processes.
Ryan Mastro, PhD, Vice President, Analytics, United Healthcare
Ryan has over 10 years of experience in applying data-driven analytics to developing business strategy in the healthcare sector. Currently, Ryan is Vice President, Analytics for United Healthcare in Downtown Chicago where he leads a team responsible for data warehousing, auditing, reporting, and strategic analytics. His team leverages “Big Data” to provide consultative support services for Sales, Marketing, Product, Distribution, and Clinical / Health Economics. Prior to joining United Healthcare, Ryan was with CVS /caremark where he led a Strategy and Analytics team providing data-driven insights for Sales, Distribution, Product and Business Development functions. Ryan held previous positions in Health Care and Life Sciences Consulting, most recently as an Associate Partner with Oliver Wyman in their Health and Life Sciences practice based in Chicago. Ryan earned his PhD in Neurobiology in 2006 and a Bachelor’s degree in Neuroscience from Yale University (a long, long time ago).