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Data Science in Health Technology Assessment
Monica Daigl
Monica Daigl
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.
Register for this course and see more details by visiting:
OpenCourser.com/course/rtwxim/data
What's inside
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.
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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.
Read more
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.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Explores economic evaluation and Health Technology Assessment (HTA) methods
Covers key principles of economic evaluation, comparator selection, and time horizon
Examines the measurement of health-related quality of life and its use in economic evaluation
Introduces decision modelling techniques for health economic analysis
Emphasizes problem and model conceptualization best practices
Intended for learners new to health economics and HTA
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Activities
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Data Science in Health Technology Assessment.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Data Science in Health Technology Assessment will develop knowledge and skills
that may be useful to these careers:
Health Economist
Health Economist
Health Economists study the costs and benefits of healthcare interventions and policies. Data Science in Health Technology Assessment would help build a strong foundation for a Health Economist, especially one who wishes to work with data-heavy healthcare decisions.
Health Policy Analyst
Health Policy Analyst
Health Policy Analysts research and analyze health policy issues and make recommendations to policymakers. Data Science in Health Technology Assessment would help build a strong foundation for a Health Policy Analyst who wishes to specialize in health technology.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to extract insights. Data Science in Health Technology Assessment would be useful for Data Analysts who wish to work in healthcare, especially in health technology assessment.
Data Scientist
Data Scientist
Data Scientists help companies harness data to gain insights and make better decisions. Data Science in Health Technology Assessment would help build a foundation for a Data Scientist working in the healthcare industry as it delves into data science concepts used for healthcare evaluation.
Market Researcher
Market Researcher
Market Researchers study market trends and competition. Data Science in Health Technology Assessment may be useful for Market Researchers who work in healthcare, especially in health technology.
Pharmaceutical Market Analyst
Pharmaceutical Market Analyst
Pharmaceutical Market Analysts research and analyze market trends and competition in the healthcare industry. Data Science in Health Technology Assessment would help build a useful foundation for a Pharmaceutical Market Analyst, especially one who wishes to specialize in health technology.
Business Analyst
Business Analyst
Business Analysts analyze business processes and make recommendations for improvement. Data Science in Health Technology Assessment may be useful for Business Analysts who work in healthcare, especially in health technology.
Project Manager
Project Manager
Project Managers plan and execute projects to achieve specific goals. Data Science in Health Technology Assessment may be useful for Project Managers who work in health technology.
Quality Assurance Manager
Quality Assurance Manager
Quality Assurance Managers oversee the quality of products and services. Data Science in Health Technology Assessment may be useful for Quality Assurance Managers who work in health technology.
Regulatory Affairs Specialist
Regulatory Affairs Specialist
Regulatory Affairs Specialists ensure that products and services comply with government regulations. Data Science in Health Technology Assessment may be useful for Regulatory Affairs Specialists who work in health technology.
Medical Writer
Medical Writer
Medical Writers create and edit written materials about medical topics. Data Science in Health Technology Assessment may be useful for Medical Writers who wish to specialize in health technology.
Biostatistician
Biostatistician
Biostatisticians apply statistical methods to design and analyze studies in the health sciences. Data Science in Health Technology Assessment may be useful for Biostatisticians who wish to work in health technology assessment.
Healthcare Consultant
Healthcare Consultant
Healthcare Consultants provide advice to healthcare organizations on how to improve their operations and efficiency. Data Science in Health Technology Assessment would be useful for Healthcare Consultants who work in health technology assessment or who wish to do so in the future.
Epidemiologist
Epidemiologist
Epidemiologists investigate the causes and distribution of diseases in populations. Data Science in Health Technology Assessment may be useful for Epidemiologists who wish to work in health technology assessment.
Clinical Research Associate
Clinical Research Associate
Clinical Research Associates manage clinical trials and ensure that they are conducted in accordance with regulations. Data Science in Health Technology Assessment may be useful for Clinical Research Associates who wish to work in health technology assessment.
For more career information including salaries, visit:
OpenCourser.com/course/rtwxim/data
Reading list
We've selected seven books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Data Science in Health Technology Assessment.
Presents a comprehensive overview of established and developing knowledge and practice in health economic evaluation, providing a practical guide to the process of economic evaluation.
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Presents an in-depth overview of the principles and concepts of health economics, enabling readers to better understand the issues that decision-makers in the health sector face.
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Presents an introduction to modeling in health economics, addressing the basic theory and application of common modeling types, including Markov models, decision trees, and agent-based models.
Presents a guide to Health Technology Assessment (HTA) from conceptualization to dissemination and appraisal.
Provides a clear and concise introduction to the field of health economics.
This textbook provides an introduction to health economics. It good starting point for learners who are new to the field.
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Examines the financing and policy issues in health care.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/rtwxim/data
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Effort
3 weeks of study 3h per week
Level
Intermediate
Via
Coursera
Institution
Genentech
Instructor
Monica Daigl
Language
English
Good to know
Explores economic evaluation and Health Technology Assessment (HTA) methods
Covers key principles of economic evaluation, comparator selection, and time horizon
Examines the measurement of health-related quality of life and its use in economic evaluation
Introduces decision modelling techniques for health economic analysis
Emphasizes problem and model conceptualization best practices
Intended for learners new to health economics and HTA
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