Healthcare Technology, MSHT

Master of Science Healthcare Technology Overview

The Master of Science in Healthcare Technology (MSHT) program is designed to equip students with cutting-edge skills at the intersection of healthcare and technology. This eight-course degree offers a comprehensive curriculum covering key areas such as healthcare technology foundations, digital health applications, health information exchange, data analytics, cybersecurity, artificial intelligence, machine learning, and strategic management of healthcare technologies.

Students gain hands-on experience in designing and managing healthcare technology systems, developing secure and interoperable health information exchanges, and implementing AI-driven solutions to improve patient outcomes. Throughout the program, students engage in real-world projects and case studies, gaining exposure to widely-used healthcare platforms and learning about industry standards in data interoperability and cybersecurity. The program culminates with a capstone experience where students can either earn industry-recognized certifications or conduct in-depth research on emerging healthcare technology topics. This capstone allows students to demonstrate their expertise, preparing them to lead technology-driven initiatives in healthcare or pursue doctoral studies.

Graduates of the MSHT program are well-prepared to take on roles such as healthcare technology managers, healthcare data analysts, healthcare cybersecurity specialists, and healthcare AI consultants. They will contribute to the transformation of the healthcare industry and address critical challenges in patient care, privacy, and innovation.

Course of Study

This MSHT requires eight (8) specified courses plus an approved internship.

Full-time students can complete the degree in 3 semesters; part-time students can complete it in 4 semesters.

Required Core Courses

MSHT 3300 - Healthcare Technology Foundations  

MSHT 3301 - Digital Health Applications and Architecture  

MSHT 3302 - Health Information Exchange and Interoperability  

MSHT 3303 - Healthcare Data Analytics and Decision Support  

MSHT 3304 - Cybersecurity and Privacy in Healthcare  

MSHT 3305 - AI and Machine Learning in Healthcare  

MSHT 3306 - Healthcare Technology Management, Strategy, and Future Trends  

MSHT 3999 - Capstone in Healthcare Technology  

Internship

Completing an internship is a requirement in this graduate program.  Students are responsible for securing their own internship.  While students will gain valuable experience, they will not earn academic credit for their internship.

Internship requirements:

• Must include a minimum of 120 hours
• Must be directly related to the student’s program of study
• Must be approved by the Director of Career and Professional Development

Exceptions:

• Students who have seven (7) or more years of professional work experience directly related to their program of study may seek to waive the internship requirement.
• Students who currently work full-time in a field/industry directly related to their program of study.

Students seeking to waive the internship requirement must receive permission from the Director of Career and Professional Development by the end of their second semester in the master’s program.

Review the Internship Handbook for more information. Please connect with your academic advisor to plan your studies accordingly.

Program Learning Outcomes

Upon successful completion of the MSHT program, students will be able to:

• Design, implement, and manage healthcare technology solutions, including electronic health records, telemedicine, and digital health platforms, to enhance patient care and improve operational efficiencies.
• Apply data analytics and decision support tools to interpret healthcare data, optimize clinical decisions, and improve system interoperability.
• Develop and implement advanced cybersecurity measures to protect healthcare information systems, ensure regulatory compliance, and safeguard patient data privacy.
• Utilize AI and machine learning techniques for predictive diagnostics, personalized treatment planning, and automated clinical decision support.
• Lead technology-driven transformations by aligning technology initiatives with organizational strategies, navigating regulatory challenges, and driving innovation to improve patient outcomes.