Data Science (DS), a track in the Master of Science in Health Informatics program, provides students with the tools to analyze, extract and present data to the health care community. With these skills, graduates can help health care organizations make well informed data-driven decisions.
The Data Science track will:
- Teach you how to extract information from large and complex datasets, visualize it and communicate it to C-suite executives and health care providers alike.
- Enable you to help health care systems and organizations with performance improvement, especially in relation to quality measurement, patient outcomes and financial performance.
The Data Science track is for:
- Professionals who want to learn data analysis (pattern identification, hypothesis testing, risk assessment) and prediction (machine learning models that predict the likelihood of an event occurring in the future, based on known variables).
- Those who want to manage large databases with multiple types of data from different sources.
- Those who want to use data from multiple sources to guide their decision-making.
Potential career paths through the Data Science track include:
- Chief Information Officers, Chief Data Officers, Chief Analytics Officers, Chief Medical Information Officers, Chief Research Officers, Chief Quality Officers, Chief Actuaries
- Directors and Managers of Data and Analytics, Data Warehousing, Data Governance, Business Intelligence, Population Health, Clinical Research, Clinical Informatics, Clinical Decision Support, Financial Analytics, Process Improvement, Operations, Precision Medicine
- Data Analysts, Data Architects, Data Scientists, Data Stewards, Data Integration Architects
- Statistical Analysts, Medical Informaticists, Actuaries
- Database and Data Warehouse Developers, Administrators, Architects
- Health IT System Developers
DS Curriculum Requirements
All students enrolled in the Data Science track are required to complete 36 credits. Students enrolled full-time normally complete the program in three to four consecutive terms. There are online and on-campus versions of this track. The curriculum and course contents are identical in these two versions. Domestic students can choose either program according to their situation or preference before the enrollment. International students are required to attend the on-campus version of the track.
The Data Science curriculum allows students to choose from required courses and elective courses. Elective courses can be chosen from other health informatics tracks in the department, other departments in SHRS, or other academic programs within the University.
Curriculum Effective Spring 2023
Required Courses (24 credits)
- HI 2021 Practical Statistics & Programming Using R (3 credits)
- HI 2022 Introduction to Python for Health Informatics (3 credits)
- HI 2210 Health Information and the Health Care System (3 credits)
- HI 2250 Foundations of Health Informatics (3 credits)
- HI 2251 Healthcare Analytics and Data Visualization (3 credits)
- HI 2454 Data Science in Health Informatics (3 credits)
- HI 2453 Data Analytics and Machine Learning in Health Science (3 credits)
- HI 2451 Database Design and Big Data Analytics (3 credits)
Elective Courses (12 credits)
- HI 2230 Financial Management & Health Care Reimbursement (3 credits)
- HI 2231 Talent Management and Human Resources (3 credits)
- HI 2236 Quality and Performance Improvement in Healthcare: Methodologies, Core Skills, and Lean Green Belt Certification (3 credits)
- HI 2410 Health Vocabulary, Terminology & Classification Systems (3 credits)
- HI 2411 Revenue Cycle Analytics (3 credits)
- HI 2450 Security, Privacy, Legal & Ethical Issues in Health Care (3 credits)
- HI 2452 Digital Health (3 credits)
- HI 2456 Healthcare IT Trends and Innovation (3 credits)
- HI 2457 Design Thinking in Health Informatics (3 credits)
- HI 2632 Leadership and Project Management (3 credits)
- HI 2670 Health Informatics Capstone/Internship (3 credits)
View Program Catalog and Course Descriptions
Curriculum Effective Fall 2022
Required Courses (21 credits)
- HI 2021 Practical Statistics and Programming Using R
- HI 2022 Introduction to Python for Health Informatics
- HI 2210 - Health Information and the Health Care System
- HI 2250 - Foundations of Health Informatics
- HI 2454 - Data Science in Health Informatics
- HI 2453 - Data Analytics and Machine Learning in Health Science
- HI 2451 - Database Design and Big Data Analytics
Elective Courses (15 credits)
- HI 2450 - Security, Privacy, Legal and Ethical Issues in Health Information Systems
- HI 2410 - Health Vocabulary, Terminology & Classification Systems
- HI 2452 - Digital Health
- HI 2236 - Quality and Performance Improvment in Healthcare: Methodologies, Core Skills and Lean Green Belt Certification
- HI 2632 - Leadership and Project Management
- HI 2650 - Practical Research and Evaluation Methods
- HI 2230 - Financial Management & Health Care Reimbursement
- HI 2456 - Healthcare IT Trends and Innovation
- HI 2231 - Talent Management and Human Resource
- HI 2670 - Health Informatics Capstone/Internship
Curriculum Effective Spring 2021
Required Courses (18 credits)
- HI 2020 - Practical Statistics and Programming Using Python and R
- HI 2210 - Health Information and the Health Care System
- HI 2250 - Foundations of Health Informatics
- HI 2454 - Data Science in Health Informatics
- HI 2453 - Data Analytics and Machine Learning in Health Science
- HI 2451 - Database Design and Big Data Analytics
Elective Courses (18 credits)
- HI 2450 - Security, Privacy, Legal and Ethical Issues in Health IT
- HI 2410 - Health Vocabulary, Terminology & Classification Systems
- HI 2452 - Digital Health
- HI 2236 - Quality and Performance Improvment in Healthcare: Methodologies, Core Skills and Lean Green Belt Certification
- HI 2632 - Leadership and Project Management
- HI 2650 - Practical Research and Evaluation Methods
- HI 2230 - Financial Management & Health Care Reimbursement
- HI 2456 - Healthcare IT Trends and Innovation
- HI 2231 - Talent Management and Human Resource
- HI 2670 - Health Informatics Capstone/Internship
Curriculum for Students who Entered Before Spring 2021
Required Courses (36 credits)
- HI 2250 - Foundations of Health Informatics
- HI 2450 - Security, Privacy, Legal and Ethical Issues in Health IT
- HI 2210 - Health Information and the Health Care System
- HI 2410 - Health Vocabulary, Terminology & Classification Systems
- HI 2451 - Database Design and Big Data Analytics
- HI 2452 - Digital Health
- HI 2454 - Data Science in Health Informatics
- HI 2632 - Leadership and Project Management
- HI 2453 - Data Analytics and Machine Learning in Health Science
- HI-2670 - Health Informatics Capstone/Internship
- HI 2020 - Practical Statistics and Programming Using Python and R
- HI 2650 - Practical Research and Evaluation Methods
Many HI courses are only offered once per academic year. In this case, if a student fails to successfully complete a course, the student must retake the course the next academic year. This may prevent the student from registering for advanced-level courses and delay graduation.
Please note: All students are required to finish one Health Informatics capstone/internship and one course in medical terminology if they do not have that course or clinical background. Pitt offers a Coursera course in Medical Terminology that can meet this program requirement. However, the student can choose another medical terminology course as well.
Online MSHI Program Ranked #4
The online MS in Health Informatics (MSHI) program was ranked #4 for Best Online Master's in Healthcare Analytics programs by AnalyticsDegrees.org. The Data Science track was ranked according to a weighted algorithm that considers quality, reputation and cost.