Master of Health Data Science at Thomas Jefferson University

Health Data Science is a rapidly evolving field that integrates informatics, machine learning, artificial intelligence (AI), and statistics to enable innovative approaches to analytics and health research. It is more important than ever to focus on what data science training in the health space can do for the growing AI industry, especially within precision medicine and predictive analytics.

To rise to this challenge, our program prepares learners to: 

• Master the machine learning algorithms that power AI systems
• Integrate and wrangle large and disparate real world data sources including registries and electronic health records
• Build statistical and predictive models using SAS, R, and Python
• Create effective data visualization tools and reports to power research and business decision-making
• Communicate statistical and data-driven findings to technical and non-technical audiences
• Provide data analytics leadership to support value-based care in health organizations

Our HDS program includes quantitative training in statistics, informatics, machine learning, and artificial intelligence to learners' careers across the health data space. Learners are prepared for careers where there is a growing need for professionals who can learn from data and analytics to address critical healthcare questions. This is especially important in the age of value-based care where data and outcomes are driving health organizations' growth and prosperity. This program is differentiated from other graduate programs as its faculty come from all segments of industry and academia and integrate real-world experience into the classroom environment, with a special focus on electronic health record data.

Our Health Data Science (HDS) program has two degree options: a graduate certificate and a master's degree. All coursework is 100% online and uses an accelerated term format specifically designed for working professionals. This enables learners to focus on building one set of skills at a time, but still graduate at the same pace as traditional graduate degree programs.

The graduate certificate focuses on the foundations of health data science. This option contains five online courses and can be completed in one year. 

The Master of Science (MS) in Health Data Science builds upon the foundation concepts presented in the Graduate Certificate and focuses on the advanced application of health data science concepts necessary for the applied practice of health data science in industry and research settings. This option contains 10 online courses and a capstone, which is specifically designed to enhance the learner's career trajectory. This option can be completed in two years.

Two track options allow learners to focus their studies in health data science:

Management Track

The Management Track prepares learners to lead data science initiatives in their organizations (whether providers, payers, vendors, employers, consulting, or governmental agencies) of steadily increasing scope and importance. This track provides students with competencies in the latest data science methods including statistics and predictive analytics, as well as the ability to visualize and gain insights from data. These competencies provide learners with the practical expertise to help improve the demonstrable quality, safety, and value of their organizations. Learners develop skills to plan and lead evidence-based practice implementations. This track targets learners early in their careers who seek leading roles that require technical expertise, as well as more seasoned professionals (including clinicians) who aspire to become mission-critical chief analytics officers for their organizations.

Research Track

The Research Track prepares learners to conduct research using data scientific methods either academically or as a part of an organization. Learners acquire competencies in statistics, data wrangling, data visualization, supervised, unsupervised and deep learning machine learning methods for work on real-world health data science projects, including AI-infused technology. Learners acquire expertise in SAS, R, and Python, with no expectation of prior coding proficiency. The target audience includes learners who seek the technical expertise to lead health data science research efforts with providers, payers, employers, data vendors, consulting, and governmental agencies. 

Health data science is used in a variety of healthcare settings. Consequently, our learners come from a diverse range of backgrounds, including:

• Accountable Care Organizations (ACOs), Clinically Integrated Networks, and other integrated delivery systems
• Large, multi-site healthcare delivery organizations
• Health insurance plans or third-party administrators
• Clinicians who are interested in focusing on statistics and data, and turning insights into action
• Health information exchanges
• Population health management companies
• Public/government entities engaged in healthcare or public health oversight
• Public health surveillance agencies
• Hospital associations and other professional or trade associations
• Pharmaceutical, device, and biotechnology industries
• Healthcare management consulting firms
• Healthcare-focused technology companies

• 100% online with no synchronous learning requirement
• Globally-focused curriculum designed by and for Health Data Science professionals
• Curriculum tracks for management or research provides options for career trajectory
• Accelerated seven-week term format tailored to working professional
• Courses taught by expert practitioner faculty who bring their extensive real-world experience to the classroom
• Complete a graduate certificate in one year or a master’s degree in two years by taking just one course at a time
• Memberships in professional associations

The program also includes training in the leading software used by industry experts: