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Data-Driven Decision Making for New Drugs: A Collaborative Learning Experience
Abstract
Two courses, advanced decision-making and pharmaceutical marketing, were combined in a collaborative process to mimic how the pharmaceutical industry determines the potential of new drugs. Integrated student teams worked together to complete semester-long projects and taught each other their respective knowledge areas—marketing and statistics. Real-world data for medical and pharmacy claims payments were “cleaned” and mined by students to analyze usage and cost patterns for anti-hypertensive and anti-hypercholesterolemia drugs currently on the market. Analyses included merging the medical and pharmaceutical data records to derive individual electronic patient records, which were the basis of financial projections for the new drugs. Importantly, the single patient record is congruent with the needs of the stakeholders currently working to reform U.S. healthcare delivery.
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