Data Science in Health Technology Assessment
Master data science applications in healthcare economics and technology assessment. Learn cost-effectiveness analysis and quality-of-life measurements.
Master data science applications in healthcare economics and technology assessment. Learn cost-effectiveness analysis and quality-of-life measurements.
This comprehensive course explores essential concepts in Health Economics and Health Technology Assessment (HTA) for professionals with data science or clinical backgrounds. Students learn key principles of economic evaluation, health-related quality of life measurements, and health economic modeling. The course covers cost-effectiveness analysis, QALY calculations, and decision modeling techniques, providing practical knowledge for healthcare reimbursement decisions. Designed for intermediate learners, it combines theoretical foundations with real-world applications in healthcare technology assessment.
4.8
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What you'll learn
Learn key principles of economic evaluation in healthcare
Understand different types of cost analysis and their applications
Master the concept of Quality Adjusted Life Years (QALYs)
Develop skills in health-related quality of life measurement
Explore decision modeling techniques for healthcare assessment
Apply sensitivity analyses in health economic modeling
Skills you'll gain
This course includes:
36 Minutes PreRecorded video
3 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 3 modules in this course
This course provides a comprehensive introduction to Health Technology Assessment (HTA) and health economics for professionals in data science and healthcare. The curriculum covers three main areas: health economics fundamentals, health-related quality of life measurements, and health economic modeling. Students learn about economic evaluation principles, cost analysis, quality-adjusted life years (QALYs), decision modeling techniques, and sensitivity analyses. The course emphasizes practical applications in healthcare decision-making and reimbursement strategies.
Health Economics
Module 1 · 2 Hours to complete
Health measurements and QALYs
Module 2 · 2 Hours to complete
Health Economic Modelling
Module 3 · 1 Hours to complete
Fee Structure
Payment options
Financial Aid
Instructor
Health Economics and Technology Assessment Expert
Monica Daigl has established herself as a leading expert in Health Economics and Health Technology Assessment (HTA) at Genentech. As the instructor for "Data Science in Health Technology Assessment," she specializes in teaching key concepts and methods in health economics to professionals with backgrounds in data science and clinical studies. Her course covers crucial areas including economic evaluation principles, health-related quality of life measurement, and decision modeling techniques. Her expertise spans technical aspects such as cost-effectiveness analysis, quality-adjusted life years (QALYs), and economic modeling. Her teaching has received strong recognition, with a 4.5/5 rating from students. Through her work, she helps professionals understand the principles used by payers for reimbursement decisions, bridging the gap between data science, clinical research, and healthcare economics
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4.8 course rating
12 ratings
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