This course explores key concepts and methods in Health Economics and Health Technology Assessment (HTA) and is intended for learners who have a foundation in data science, clinical science, regulatory and are new to this field and would like to understand basic principles used by payers for their reimbursement decisions.
Overview
Syllabus
- Health Economics
- This module covers the key principles of economic evaluation, including types of analysis, the technical issues such as choosing the comparator, perspective, and time horizon. It looks at types of costs, and the need for discounting.
- Health measurements and QALYs
- This module covers the measurement of health-related quality of life and its incorporation into economic evaluation.
- Health Economic Modelling
- This module introduces decision modelling techniques, deterministic and probabilitic sensitivity analyes and best practices for problem and model conceptualization.
Taught by
Monica Daigl
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Reviews
5.0 rating, based on 1 Class Central review
4.8 rating at Coursera based on 12 ratings
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I would rate the course on Data Science in Health Technology Assessment by Genentech via Coursera as excellent. The content is well-structured and provides a comprehensive understanding of how data science can be applied in health technology assessments. The instructors are knowledgeable, and the course includes practical examples that enhance learning. It effectively combines theoretical concepts with real-world applications, making it beneficial for both beginners and those with some background in the field. Overall, it's a valuable resource for anyone interested in the intersection of data science and healthcare.
