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Home Programs Master’s Degrees Master of Science in Healthcare Analytics

Online Master’s in Healthcare Analytics

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Total credits

36 Transfer up to 18 credits. Speak to an enrollment counselor for more information.

Cost per credit

$675 No out of state tuition. No fees. No tuitition increases. Guaranteed.

Delivery

Online Our 8-week courses are 100% online, asynchronous, and fully flexible.

Starts per year

12 CSU Global offers start dates every month.

Program Details

Transforming Healthcare with Data: 100% Online Master’s in Healthcare Analytics

Harness the power of data with our Master of Science in Healthcare Analytics program, designed for those ready to make strategic decisions in healthcare. Here’s a snapshot of the skills and knowledge areas you’ll master:

Healthcare Data Proficiency: Manage and analyze diverse healthcare data sources, including EHRs and clinical trials.
Advanced Analytical Techniques: Apply statistical methods, predictive analytics, and machine learning to healthcare data.
Data Visualization: Create impactful data visualizations to communicate insights to stakeholders.
Clinical and Operational Improvement: Enhance clinical outcomes and operational efficiencies with data-driven solutions.
Ethical Leadership: Navigate ethical considerations in healthcare analytics and ensure compliance with regulations like HIPAA and GDPR.

This program prepares you for high-demand roles such as healthcare data analyst, clinical data scientist, and healthcare consultant.

Download the program information sheet

Courses in this Program

CSU Global’s accredited online Master of Science in Healthcare Analytics requires the completion of 24 core credits and 12 specialization courses in an area of interest to the student.

Prerequisites

In addition to the institutional graduate admission standards, students seeking admission to the MSHA program must have an undergraduate degree with a major or concentration in management information systems, information technology, computer science, or database management and demonstrate that they have recently (last 5 years) taken at least introductory courses in the following three areas: computer programming, database management, and statistics.

Students who do not meet the above conditions may be admitted provisionally to the program. Courses from the list below may be required to be completed as a prerequisite to the MSHA coursework to build up background knowledge in these areas for students that do not have courses or industry experience in these subjects in the last 5 years:

MIS446 – Statistics for Data Analytics Using R
MIS407 – Database Concepts

To meet prerequisite requirements for admission, students must complete the above coursework within 12 months of starting and maintain a 3.0 grade point average. Students should reference the provisional admissions policy in university catalog for additional admission requirements.

*Please click on a course title below to view description

HDA500 - Statistical Foundations in Analytics

Course Description

This course will introduce students to Bayesian statistics using Python. Students will learn probabilistic models and apply Bayes’ theorem to derive the logical consequences to models and data. This course will cover Bayesian data analysis and probabilistic programming.

Credit Hours: 3

MIS505 - Data Wrangling

Course Description

This course will introduce students to the purpose and need for wrangling data. Data wrangling is the process in which data is shaped and formed for usefulness to solve business problems. Students will learn to merge, clean, shape and store data to use for analytics. Students will use tools such as Excel, Python and R to prepare data for analysis.

Credit Hours: 3

MIS510 - Data Mining and Visualization

Course Description

This course will provide the basic framework for conducting various data and text mining methodologies, including logistic regression analyses, classical discriminant analyses, association rule, decision tree, support vector machine, neural networks, variable reduction, cluster analysis, text analytics, and web mining. In addition, this course teaches the essential and practical skills in visualization, including computer graphics, visual data representation, physical and human vision models, numerical representation of knowledge and concepts, pattern analysis, and computational methods. Recommended Prior Course: MIS500

Credit Hours: 3

MIS512 - SQL for Data Analytics

Course Description

This course will teach students to form hypotheses and generate descriptive statistics that can provide key insights into existing data. Students will learn how to write SQL queries to aggregate, calculate, and combine SQL data from sources outside of a current dataset. Students will learn the efficient application of SQL techniques in everyday business scenarios and looking at data with the critical eye of analytics professional.

Credit Hours: 3

MIS530 - Predictive Analytics

Course Description

This course covers the fundamental predictive analytics and data mining approaches applied in business. It introduces basic concepts and techniques to discover patterns in data, identify variables with the most predictive power, and develop predictive models.

Credit Hours: 3

MIS535 - Data Reporting & Visualization

Course Description

This course will provide students with an opportunity to learn how to visualize data and tell a data story using visualization tools. Students will learn to understand and determine the needs of the stakeholder by using Use Cases to provide data for decision-making. Students will also learn to create visualizations and dashboards to display an effective data story to an audience, create dashboards for monitoring metrics, and communicating complex ideas into effective results.

Credit Hours: 3

HDA565 - Analytics in Healthcare

Course Description

This course will provide students with the opportunity to analyze different types of datasets used in healthcare analytics. Data such as hospital ratings, population health, hospital readmissions, medicare spending, healthcare staffing, hospital emergency department performance and patient satisfaction will be analyzed for insights. Socio-economic factors will also be explored as predictors for healthcare treatment.

Credit Hours: 3

HDA595 - Healthcare Data Analytics Capstone

Course Description

This course will educate students on concepts that can lead an organization to sustained changes and to improve clinical, operational, and financial outcomes. Students will learn by using real-world healthcare problems and use cases focusing on connecting and integrating people, process, and technology to deliver insight-driven decisions. Students will also explore innovative technologies available to manage data and apply analytics with some best practices to transform an organization. This course will also explore the future of healthcare and what to expect with the rise of digital transformation, machine learning, and artificial intelligence.

Credit Hours: 3

Affordable Tuition

As a not-for-profit public university, our goal at CSU Global is to make your online tuition cost as affordable as possible. We offer low-cost online degree tuition rates without taking anything away from the quality of the education you receive. We also lock in that low tuition rate with our tuition guarantee, and we provide additional discounted tuition rates for members of the armed forces and employees of our corporate affiliate partners.

Learn more about CSU Global tuition rates and explore financial aid options available that can help cover the cost of your education.

Career Outlook and Outcomes

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Institutional accreditation by the Higher Learning Commission (HLC) means your degree comes from a top-quality, trusted university.

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