MDA in Health Management | Hamad Bin Khalifa University
Master of Data Analytics in Health Management

Master of Data Analytics in Health Management

A multidisciplinary program aimed at equipping students with knowledge of the latest advances in the tools and principles of big data handling and analysis and their application in managing the ever-growing health data.

As Qatar continues to expand its medical facilities in what is today the region’s biggest health care expansion project, the need for highly-trained data analytics specialists in digital health management continues to grow manifold. 

The Master of Data Analytics in Health Management (MDA-HM) program is the very first of its kind in the world and aims to train talented scientists and researchers to effectively contribute in designing and implementing data analytic tools in healthcare systems in both Qatar and abroad.

Overview:

The MDA-HM program aims to equip students with knowledge of the latest advances in the tools and principles of big data handling and analysis and their application in managing the ever-growing health data. 

During the course of their studies at the College of Science and Engineering (CSE), students will undergo specialized training that will equip them to develop advanced and effective strategies and policies to enhance preventive care, reduce per capita cost of patient care, and enhance progress in diagnostics and medical research leading to the development of more efficient health care systems. Uniquely, the program will also give students a myriad of opportunities to collaborate with professionals from relevant industrial and government sectors around the world, hence inspiring the student body with positive qualities of leadership, social consciousness, integrity and general ethics. 

Major local and international organizations continue to grow their investments in the concept of big data analytics and use of business intelligence and technology to better serve their audiences. Furthermore, in a recent report, the government of the State of Qatar underscored the need for greater mechanisms of data analysis.

As such, a key focus of the MDA-HM program will be to produce graduates who may go on to undertake challenging roles as health data analysts, epidemiologists, biostatisticians and bioinformatics specialists, healthcare managers in health services in Qatar and abroad. 

 


Program Focus

Combining data analytics with health care management for the first time, the MDA-HM program uniquely focuses on educating students on the latest advances in the tools and technologies involved in big data analytics for health management applications. Furthermore, the program aims to train students in various applied techniques, methodologies and tools to effectively manage and analyze the constant growths of health data in order to drive higher productivity in health care sector.

Enrolled students will:

  • Develop core knowledge in data analytics: Students will acquire essential skills for scientific studies, research work and decision-making through undergoing core courses that include applied statistics, data analytics tools and methods as well as general methodologies, policies and ethics applied to different fields.
  • Master big data systems for multiple disciplines: Students will explore the impact of examining big data, which are large datasets containing a variety of data types for health or other applications. Furthermore, students will be trained to master state-of-the-art tools and methodologies in uncovering hidden patterns, unknown correlations, market trends, customer preferences and other useful business information from big data.
  • Study ethics involved in data analytics: Students will obtain a deep knowledge of today’s health management systems and their pitfalls. Importantly, they will apply high ethical standards and propose draft policies for dealing with big data applied to health management. A key objective of the MDA-HM program is to foster a strong understanding of health management values, policies, challenges, opportunities as well as their impact on health.

 

Curriculum:

A 33-credit program, taught in English, typically over two years including:

  • Core courses in data analytics (12 credits)

  • Electives courses

  • Research thesis (9 Credits) or multidisciplinary project (6 credits) and an elective course

View Admission & Application Requirements

Core courses

Data Collection, Storage and Retrieval (3 credits):

The course will expose students to state-of-the art of health data science methodologies for data collection, storage and acquisition of health datasets. Effective management and usage of datasets in any health organization depends on the way data is stored and processed. This course exposes students to the basic principles of data storage, retrieval, and processing tools in the context of integrated data analytics processing needs. As these concepts are introduced, various informatics and artificial intelligence tools will be used to illustrate how to build storage and processing architectures. Students will use case studies, recent publications on background theory, and hands-on experimentation, to learn how to select, plan, and implement storage, search, and retrieval components of large-scale structured and unstructured information repositories. The goal of this course is to provide a set of methodologies by which one can construct a complete architecture for storing and processing data.

 

Artificial Intelligence and Machine Learning in Health care (3 credits)

In this course, students will be introduced to basic techniques and principles of data mining and their applications in the management and analysis of healthcare data. Participants will discuss basic learning algorithms, such as regression and decision trees and their application in the analysis and implementation of various data types. 

 

Health Sciences Data Analytics (3 credits)

Students will be trained how to use the various health data analytics tools. The focus will be on various topics such as the multiple ways of identifying stakeholder needs; the different types of health data; software tools; as well as case studies from public health, electronic health records, claims data, home-monitoring data and response to various drug treatments. An emphase will be put on the importance of understanding the complexity and potential biases in the ways by which health data (direct or indirect) are collected and represented. Students will be offered an opportunity to practice presenting results of real case analyses studies.

 

Research Methods and Ethics (3 credits)

This course is a foundational course for graduate students who will be engaged in Big data analytics in health management. It provides students with advanced discussions on ethics and ethical misconduct, intellectual property and environmental health and safety as well as scientific thought and design of experiments. A focus of the course is to transition students from textbooks to primary literature as their main source of information.