MSc in Healthcare Analytics

The MSc in Healthcare Analytics brings together our expertise in healthcare, data science, and business analytics to create a unique program offering for current and future healthcare professionals. Under the expert guidance of Dr. Pariksith Singh, a renowned physician, founder, and healthcare leader, and Dr. David Lopez, an accomplished data scientist with extensive academic, research, and industry experience, the program has been designed to provide students with the analytical, technical, and communication competences to drive improvement in quality, utilization, operations, and other areas of healthcare management.


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In today’s era of big data and AI, organizations in all areas of healthcare need analysts and data scientists who can harness advanced skills and technologies to derive insights and drive improvement. This program delivers these competencies.
Dr. Pariksith Singh
Chairman & Chief Education Officer, Vedere University
CEO, Access Health Care Physicians

Program Overview

The main objective of this program is the training of recent graduates to help them land their first job as entry-level data scientists or analysts in health-related industries and organizations. The program will also support healthcare professionals already in managerial or oversight roles who are seeking to create data-driven solutions for complex problems in their areas and organizations.

The program adopts a Problem-Based Learning (PBL) approach to design and deliver the modules of the program. PBL is increasingly considered an effective instructional approach to facilitate students’ attainment of the high-level competences and transferable skills increasingly being demanded by industry and the public sector.

The program is structured in 3 stages:
  • Stage 1 will ensure that students acquire advanced programming skills and statistical analysis and data visualization techniques.
  • Stage 2 will introduce students to machine learning techniques and generative AI and allow them to apply their skills in healthcare contexts to solve problems and drive decision-making.
  • Stage 3 will provide students with the latest knowledge of healthcare delivery models and services and understand how to apply their analytical, technical, and communication competences to drive improvement in quality, utilization, operations, and other areas of healthcare management.

Program Outcomes

By completing the program, students will learn to:

Analytical Competencies

  • Build statistical models and understand their power and limitations.
  • Design an experiment.
  • Apply problem-solving strategies to open-ended questions.
  • Determine when to use generative AI in healthcare contexts.
  • Translate business requirements into technical specifications.
  • Design and adapt secure generative AI systems in healthcare contexts

Technical Competencies

  • Acquire, clean, and manage health data.
  • Handle and analyze massive health datasets.
  • Use machine learning and optimization to make decisions.
  • Assemble computational processes to develop data science using widely available market tools.

Communication Competencies

  • Visualize data for exploration, analysis, and communication in healthcare contexts.
  • Collaborate with other functional teams.
  • Perform reproducible data analysis.
  • Conduct data science activities mindful of policies, privacy, security, and ethical considerations.
  • Utilize generative AI-based systems consistent with privacy best practices, ethical principles, and security.

Healthcare Competencies

  • Demonstrate a practical understanding of care model concepts, funding and reimbursement models, basic organizational decisions, and patient population selection and coverage.
  • Demonstrate a practical understanding of quality, utilization, and operations in a healthcare context and the ability to apply analytical, technical, and communication competencies to improve outcomes for patients and providers.

Program Structure

The program consists of a total of 36 credits and 12 required courses. It is structured to be completed in a specific sequence, as indicated by the prerequisites mentioned in the Course Descriptions section below. The Capstone Project serves as a platform to integrate and apply the knowledge acquired throughout the degree program.
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Course Descriptions

Admission Requirements:

  • An undergraduate degree from an accredited Institution – with a preferred GPA of 3.0 or higher
  • A quantitative background from prior academic study or work experience
  • Completed application form including personal statements/essays
  • Resumé and letters of recommendation
  • Official academic transcripts and certificates
  • TOEFL/IELTS or other English language proficiency test if applicable

Costs & Fees

15,984 USD
Total Program Fee
36
Credits
444 USD
Cost per Credit
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