Master of Science in Health Informatics/Healthcare Analytics

HIM6930 - Health Data Management

Credits: 3

This course introduces data management and database technologies, including relational database systems and the structured query language (SQL).  In addition, data warehousing and more analytic databases also are introduced, along with online analytic processing (OLAP) tools to support decision making.  Data quality issues, emerging cloud databases and other special topics will round out the coverage. Finally, the course offers a brief introduction to data mining techniques.

HIM6141 - Introduction to Healthcare Analytics

Credits: 3

Introduction to Healthcare Analytics is designed to provide a comprehensive introduction of the current state of the science and practice of analytics in healthcare.
 

HIM6667 - Foundation in Management Information Systems

Credits: 3

This course is designed to provide a discussion of the various facets of MIS, including acquiring, storing and interpreting information of interest to the informaticist and healthcare professional.

HIM6017 - Legal Aspects of Health Info Management

Credits: 3

This course provides an in-depth discussion of selected legal and regulatory issues that are applicable to the management of patient information in health informatics.

HIM6018 - E-Healthcare Ethics

Credits: 2

This course examines selected ethical considerations that are significant components of health sciences, informatics and electronic medicine and often represent important considerations to be addressed during the delivery of healthcare using e-medicine models.

HIM6623 - Statistics for Healthcare Analytics

Credits: 3

This course provides an in-depth discussion of selected topics of statistical analysis applicable to healthcare data. It is designed to assist graduate students in the application of traditional statistical methodologies to real life healthcare datasets.
 

HIM6655 - Healthcare Data Mining and Predictive Analytics

Credits: 3

Healthcare Data Mining and Predictive Analytics is designed to introduce students to various data mining concepts and algorithms. It emphasizes on classifiers, clustering, and association analysis applicable to the distinct nature of healthcare data.
 

HIM6628 - Health Data Visualization

Credits: 3

This course focuses on techniques and methodologies commonly used to explore and present health data to facilitate healthcare decisions.
 

HIM6810 - Health Outcomes Research

Credits: 3

This course is designed to introduce students to the fundamentals of health outcomes research and clinical trial design. It explores the principles and methods used to obtains quantitative evidence on the effects of interventions on the diagnosis, etiology, and prognosis of a disease.
 

HIM6934 - Medical Terminology

Credits: 3

Medical Terminology in Health Informatics is designed for graduate students who wish to gain a core understanding of the various medical terms used by healthcare personnel during healthcare delivery, as well as health informatics individuals to successfully undertake a healthcare project. This course employs a programmed learning approach by body systems. It reflects current trends and new approaches to teaching medical terminology.

HIM6686 - Healthcare Decision Support

Credits: 3

This course presents in detail all steps involved in medical decision making. It discusses both normative and descriptive theories and uncovers the link between medical decision making, healthcare analytics and improvement of health outcomes at the individual as well as population level.
 

HIM6629 - Applied Healthcare Analytics

Credits: 3

This course provides an in-depth examination of advanced level regression models applied in healthcare data. Topics include mix models, propensity scores, instrumental variables, and time-to-event analysis. Models will be developed based on real life large healthcare datasets such as the National Surgical Quality Improvement Project dataset from American College of Surgery.
 

HIM6671 - Advanced Healthcare Analytics Applications

Credits: 3

This course is designed as a guide to the analytics steps required for the analysis of real life, big healthcare datasets such as the SEER cancer database, the Framingham heart disease dataset, the SUPPORT prognostication model and the STAR transplant database. It emphasizes the data preparation and analysis techniques necessary to define a problem, describe the data and model prediction of health outcomes.
 

HIM6908 - Health Informatics Independent Study

Credit hours for this course may vary from 1-3. Prior approval is required.

Credits: 1

Develop, in conjunction with a faculty advisor, an individual project with the goal of completing an in-depth study of a topic directly relevant to the student's program of study in health informatics.