Online Data Analytics Master's Degree in Healthcare

Our Master of Science in Data Analytics is online and with a special focus on healthcare. This program is designed to address the specific challenges and opportunities in the healthcare sector and gives you the skills and know-how to succeed in the field of healthcare data analytics.

Whether you're a recent graduate or an experienced healthcare professional, our online program is flexible and comprehensive, designed to help you advance your career in healthcare data analytics.

Contact us today to shape the future of patient care and healthcare management.

Where Can I Work With a Healthcare Data Analytics Master's?

Upon completing our Healthcare Data Analytics Master's program, you’ll have a lot of options and opportunities for your career path.

  • Hospitals and Medical Centers: Enhance patient care and streamline operations through predictive analytics and operational insights.
  • Healthcare Systems and Networks: Utilize integrated analytics to improve health management and care coordination across diverse patient populations.
  • Pharmaceutical and Biotech Companies: Drive innovation in drug development and clinical trials with robust data-driven strategies.
  • Insurance Providers: Apply predictive modeling to refine risk assessment and elevate the customer experience.
  • Healthcare IT and Software Companies: Lead in the creation and improvement of cutting-edge healthcare analytics solutions.
  • Consulting Firms: Offer data-driven strategic guidance to optimize healthcare organization performance.
  • Research and Academic Institutions: Propel healthcare innovation through data-centric research and collaboration.
  • Government Healthcare Agencies: Inform policy and enhance public health initiatives through insightful analytics.
  • Health Information Exchanges (HIEs) and Health Data Organizations: Foster secure, efficient data exchange and interoperability to enhance collaborative care.
  • Medical Device and Equipment Manufacturers: Leverage data to guide product development and monitor performance effectively.

The field of healthcare data analytics continues to evolve, and so will the career paths. The MS in Data Analytics gives you the knowledge to evolve with it, and to apply it to various roles that align with your skills and passions.

You may qualify for data analyst jobs such as these:

  • Business Analyst
  • Data Scientist
  • Data Engineer
  • Systems Analyst
  • Operations Analyst
  • Statistician
  • Marketing Analyst
  • Supply Chain Manager
  • Logistics Analyst
  • Clinical Data Analyst

These roles encompass a range of responsibilities in healthcare administration, management, and analytics and allow institutions to make data-informed decisions, improve operational efficiency, optimize resource allocation, and better manage healthcare strategies.

What is the salary for a healthcare data analyst?

For data science professionals working in healthcare, with a skillset similar to the one you’ll get in our healthcare data analytics master’s program, here are some typical salary ranges:

According to Glassdoor, the average base salary for a Healthcare Data Scientist in the US is $117,622 per year. reports an average salary of $142,381, with a range typically falling between $128,248 and $156,569.

Per the Bureau of Labor Statistics, Medical and Health Services Managers, a broader category that could include healthcare data analytics, had a median pay in 2020 of $104,280 per year.

Why Touro’s Healthcare Data Analytics Master's Program?

  • Flexible: Our program is designed with your busy schedule in mind. It's online and asynchronous, allowing you to access recorded sessions and course materials at your convenience. Tailor your degree to align with your career goals through elective courses or independent study options guided by experienced mentors.
  • Real-World Tools and Experience: Our program focuses on practical application. You will work on real-world projects, learn how to use industry tools, and gain firsthand experience through optional internship experiences in related work environments, thanks to Touro University's expansive network.
  • Preparing for Professional Certification: Upon completing our program, you'll be well-equipped to pursue various data analytics and healthcare professional certifications, which can significantly enhance your career prospects. Some notable certifications to consider include the Certified Health Data Analyst (CHDA), Certified Analytics Professional (CAP), and Healthcare Information and Management Systems Society (HIMSS) certifications.
  • Experienced Faculty: Our faculty members are experienced professionals in data analytics, dedicated to facilitating your academic journey and professional growth. They bring practical insights to the classroom, ensuring you gain relevant knowledge and skills.
  • Academic Advising: We are here to guide you through your academic journey. Our academic advising services ensure you stay on track, helping you plan your course load and meet program requirements.
  • Affordable Education: Our commitment to affordability means that we provide various financial options to make your education accessible. Additionally, corporate discounts may be available (please inquire within your organization or provide us with the relevant contact information).
  • Board-Approved and Accredited: Our program is approved by the Illinois Board of Higher Education and Touro University Illinois is an institution accredited by the Higher Education Commission.

Is Coding Experience Required for the Master of Science in Healthcare Analytics Program?

While coding proficiency put you at an advantage, it is not a prerequisite for our program. As a healthcare data analyst, you'll find coding knowledge, especially in languages like Python and R, valuable for effective data handling and analysis. Our program places a stronger emphasis on cultivating a comprehensive skill set that includes data management, statistical analysis, data visualization, and strategic decision-making. This holistic approach ensures you're well-prepared for a successful career in healthcare analytics, whether you have prior coding experience or not.

Is there a lot of math in healthcare data analytics?

Healthcare data analytics involves a significant amount of math and statistics. As a healthcare data analyst, you'll use mathematical modeling and statistical techniques to analyze and interpret healthcare data. These skills are essential for identifying trends, patterns, and insights that can inform crucial decisions in the healthcare industry.

What Can You Expect from Our Healthcare-Focused Data Analytics Curriculum?

Our curriculum begins with five core courses. They start with basic concepts and progress to advanced techniques. You'll learn about Big Data, how to design databases, statistics, data warehousing, data mining, and how decisions can be improved using data.

To fit your interests in the healthcare industry, you can pick from a range of specialized electives. Options include studying Electronic Health Records, Health Data Visualization, or Healthcare Governance and Ethics. You can also look into current trends and challenges in healthcare management. For a deep dive into a topic of your choice, consider an independent study.

The program goes beyond theory. We make sure you get practical experience with real healthcare data and powerful industry tools.


All courses are eight weeks long. You'll take five core courses (15 credits) and choose five electives (15 credits) for a total of ten courses and 30 credits.


MDAI 600 - Introduction to Data Analytics (3 Credits)


The amount of data available to organizations has reached unprecedented levels. Companies and individuals who can use this data together with analytic methods give themselves an edge over their competitors. In this class, we introduce the topic of data analytics using real-world examples of how analytics have been used to transform a modern organization. Some examples of analytics covered in the class include IBM Watson, the modern supply chain, Moneyball, health forecasting and other prominent applications. Using these examples, this course will cover the following data analytics methods: linear regression, logistic regression, trees, deep learning, missing data imputation, text analytics, clustering, and optimization. Students will be introduced to the R programming language, a free open statistical computational environment, and data analytics and business intelligence tools such as Sisense. 3 credits. No prerequisites.

MDAI 601 - Introduction to Database Concepts and Design (3 Credits)


This course is intended to fine-tune the analytical and technical skills students need to function in our increasingly technological society. This course provides students with conceptual and practical experience in designing, implementing, and using databases, an increasingly important skill in the current “information age”. It serves to prepare the student to pursue a career in the highly competitive fields of database management and administration. The course will address the essential function of database management within business administration and the crucial importance of sound database design. Students will develop the skills to design, implement and utilize a database effectively. 3 credits. No prerequisites.

MDAI 602 - Statistics for Analytics (3 Credits)


This course introduces univariate data analysis methods using statistics. Data visualization methods and practices, and an overview of sampling techniques for data collection. Specifically, this course teaches introductory statistical methods for the analysis and visualization of data and basic concepts of probability theory. Course topics include descriptive statistics, data visualization techniques, an introduction to statistical inference (confidence intervals and hypothesis testing) for decision making, linear regression models, data sampling techniques. The students will learn the statistical package SPSS to analyze data sets from real-world applications. 3 credits. No prerequisites.

MDAI 603 - Data Warehousing and Data Mining (3 Credits)


This course is an introduction to the principles, methods and theory for development of data warehouses and data analysis using data mining. It includes data quality and methods and techniques for preprocessing of data, and the modeling and design of data warehouses. Algorithms for classification, clustering and association rule analysis will be studied. The course will consider the practical use of software for data analytics and business intelligence with the main goal to educate the students to assume roles such as data warehouse architect, project manager, or data administrator throughout their professional career. Students will be introduced to WEKA (the workbench for machine learning), the R programming language, and relational databases. 3 credits. No prerequisites.

MDAI 604 - Analytics Data Modeling and Strategic Decisions (3 Credits)


This course will teach a practical framework that includes creating data models, and using data analytics tools and technologies for the purpose of strategic decision-making in a modern, real-world environment. This course combines lectures with hands-on labs for the purpose of creating data models and visualizations to teach students the intricacies of data modeling and data analytics. There will be weekly lectures on various topics combined with hands-on labs so students can apply various data modeling and data analytics concepts using state-of-the-art tools. 3 credits. No prerequisites.



MDAI 610 - MIS and Healthcare Information Systems (3 Credits)


This course introduces the discussion and review of the various facets of healthcare-related management information systems (MIS) including acquiring, storing and interpreting information of interest to the healthcare professional, systems or information analyst. The analysis of effective data and information technology utilization to improve performance in healthcare organizations will be addressed including information systems, databases, analytical tools to structure, analyze and present information, and an introduction to the ethical issues related to the management of healthcare information. 3 credits. Prerequisites: Core Courses MDAI 600, MDAI 601, MDAI 602, MDAI 603, MDAI 604.

MDAI 611 - Healthcare Analytics for Professionals (3 Credits)


This course is designed to provide a comprehensive introduction of the current state of the science and practice of analytics in healthcare. It explores the data analysis needs of modern healthcare organizations, presents various models used in different aspects of healthcare management and delivery, and proposes best practices for applied healthcare analytics. The latest advances in information technology and their adoption in healthcare have allowed healthcare organizations to generate vast amounts of digital and diverse data. Terabytes of data such as doctor’s notes, streams of vital signs and statistics, lab values, pharmacy claims, genetic markers, x-rays, MRIs, etc. are generated daily. The availability of this data provides an opportunity for healthcare organizations to improve (among others) business processes, healthcare delivery, healthcare expenses, patient satisfaction, patient outcomes, treatments, diagnostic tools etc. and achieve the highly desired healthcare reform. 3 credits. Prerequisites: Core Courses MDAI 600, MDAI 601, MDAI 602, MDAI 603, MDAI 604.

MDAI 612 - Enterprise Electronic Health Records (EHR) (3 Credits)


This course introduces electronic health records (EHR) in a healthcare enterprise and is designed to provide an overview of the functions, limitations, opportunities and challenges presented by this very rapidly developing branch of data in the healthcare environment. EHR systems imply an enterprise beyond initial electronic medical records, and are a major component of the data environment and have evolved substantially since their first appearance in the 1960s. However, the impact of EHR data on quality remains unconfirmed. While there is increasing evidence that the use of EHR systems is associated with improved quality and reduced errors, knowledge of what data, why it is captured, how it is obtained, and how to analyze it are key functions. These issues highlight the need for skilled individuals who can understand and manage data in the enterprise of medical, clinical and administrative in healthcare organizations. 3 credits. Prerequisites: Core Courses MDAI 600, MDAI 601, MDAI 602, MDAI 603, MDAI 604.

MDAI 613 - Healthcare Governance, Compliance, and Ethics (3 Credits)


This course examines selected issues associated with compliance, governance, legal, and ethical considerations that are significant components related to the use and storage of healthcare data. Federal rules and regulations will be addressed including the major areas of healthcare compliance regulations: Health Insurance Portability and Accountability Act (HIPAA), Occupational Health and Safety Administration (OSHA), federal waste and abuse laws, and federal employment laws. Security and privacy of healthcare records will be addressed. 3 credits. Prerequisites: Core Courses MDAI 600, MDAI 601, MDAI 602, MDAI 603, MDAI 604.

MDAI 614 - Health Data Visualization (3 Credits)


This course is designed to enable students to acquire both the theoretical and technical skills to implement data visualization techniques for healthcare applications. This course focuses on the techniques, methodologies, and processes commonly used to explore and present health data to facilitate healthcare decision making. Students will learn about the data visualization process including data modeling, data processing, mapping data attributes to graphical attributes, and visual representation. Students will also learn to evaluate the effectiveness of visualization designs. Students will create their own health data visualizations, and learn to use open source data visualization tools. 3 credits. Prerequisites: Core Courses MDAI 600, MDAI 601, MDAI 602, MDAI 603, MDAI 604.

MDAI 615 - Data Analysis in Healthcare Internship (3 Credits)


This course provides students with the opportunity to work as an intern in the HealthCare Data Analytics area, and then to formulate a paper or project based on the approved internship. The internship must be pre-approved and should provide the student with the ability to combine his/her conceptual, technical, and applied knowledge in a business environment. This internship should draw on the skills and knowledge gained throughout the program. Regular progress reporting is expected throughout the internship. 3 credits. Prerequisites: Completion of the five core courses and 4 elective courses.

MDAI 616 - Big Data Analytics in Healthcare (3 Credits)


This course is designed for upper-level graduate students and is intended to build their understanding of using patient data, genomic databases, and electronic health records (EHR) to improve patient care and to achieve greater efficiencies in public and private healthcare systems. The course explores the concept of clinical intelligence and the role of analytics in supporting a data-driven learning healthcare system. The aim is to focus beyond data collection, to analyzing available data and making it actionable information. Open-source and web-based warehousing tools to perform practical use of healthcare analytics. 3 credits. Prerequisites: Core Courses MDAI 600, MDAI 601, MDAI 602, MDAI 603, MDAI 604.

MDAI 617 - Health Analytics Independent Study (3 Credits)


This course is designed to give students an individualized research project including reading and reporting on a specific topic approved by an instructor. The subject, topics and related material must be relevant and advanced in the area of healthcare analytics. 3 credits. Prerequisites: Completion of the five core courses and 4 elective courses.

MBAI 670 - Health Care Management: Trends and Challenges (3 Credits)


This course explores contemporary structures, trends, and issues affecting the business and professional challenges within the healthcare industry. An examination of the economics, policies, and delivery mechanisms associated with healthcare management. In addition, learners analyze the complex interrelationship of vital healthcare industry constituents: government, insurance companies, and providers. 3 credits. Prerequisites: Core Courses MDAI 600, MDAI 601, MDAI 602, MDAI 603, MDAI 604.

MBAI 676 - Healthcare Informatics (3 Credits)


This course examines the data available to healthcare providers and how to analyze and use that information to drive effective healthcare delivery. Students learn how mature health systems, medical centers, private practices, and research facilities use clinical and patient data to predict healthcare demand, be proactive with their patients, develop care management and disease management programs, and improve the patient experience. 3 credits. Prerequisites: Core Courses MDAI 600, MDAI 601, MDAI 602, MDAI 603, MDAI 604.


Each 16-week semester has two eight-week terms and each course lasts eight weeks, or one term. You'll register per term and can take one or two courses each term. For more information, visit the Touro University Illinois academic calendar.