Course List (11 courses, 35 units)
The Masters of Science in Healthcare Data Analytics program is comprised of 3 certificates that “stack together” which can be combined with graduate project for masters completion.
Certificate 1: Healthcare Systems and Operations (10 Units)
- MHDA 500: US Healthcare, Digital Health and Technology (3 units)
- MHDA 504: Epidemiology and Biostatistics for Health Analytics (3 units)
- MHDA 508: Quality and Operational Management in Healthcare (4 units)
Certificate 2: Healthcare Data Management (12 units)
- MHDA 501: Healthcare Data and Analytics (3 units)
- MHDA 502: Programming for Health Analytics (3 units)
- MHDA 505: Data Modeling for Healthcare Analytics (3 units)
- MHDA 506: Healthcare Data Visualization (3 units)
Certificate 3: Leadership and Strategy in Healthcare Analytics (10 Units)
- MHDA 503: Leadership and Ethics in Healthcare Data Analytics (3 units)
- MHDA 507: Statistical Analysis for Health Analytics (3 units)
- MHDA 509: Machine Learning and Artificial Intelligence in Healthcare (4 units)
Culminating Experience for Masters Degree (3 Units)
- MHDA 598: Graduate Project (3 units)
| Course | Name | Units | Description |
|---|---|---|---|
| Certificate 1: Healthcare Systems and Operations (can be taken as part of the master’s degree or individually) | |||
| MHDA 500 | US Healthcare, Digital Health and Technology | 3 units | This graduate-level course examines the evolving landscape of healthcare in the United States, including the emergence of digital health and technology. Students will engage in activities and discussions related to essential aspects of healthcare operations, policy implications, and sustainability practices within the healthcare system. |
| MHDA 504 | Epidemiology and Biostatistics for Health Analytics | 3 units | This course provides a comprehensive foundation in epidemiology and biostatistics tailored for healthcare analytics. Students will explore key public health concepts such as Community Health Needs Assessments (CHNAs), health determinants, and disease surveillance. Covers statistical techniques in designing epidemiological studies, presenting data, and calculating metrics like incidence and prevalence rates. Statistical techniques covered include measuring central tendency and variability, as well as advanced hypothesis testing and regression analyses in healthcare contexts. Additionally, students will examine the validity and reliability of diagnostic tools, identify biases in epidemiological research, and integrate epidemiological and biostatistical methods in healthcare analytics. Ethical considerations in data handling and its application in healthcare policy-making are also emphasized. |
| MHDA 508 | Quality and Operational Management in Healthcare | 4 units | This course provides an overview of fundamentals of Quality in Healthcare and the core quality competencies. Students will examine key performance measures and learn major quality scope of work, including risk management, regulatory compliance, patient safety and accreditation. Through a series of classroom exercises/project work, students will gain knowledge on the fundamentals of performance improvement tools and how healthcare analytic enables and improves quality of care. |
| Certificate 2: Healthcare Data Management (can be taken as part of the master’s degree or individually) | |||
| MHDA 501 | Healthcare Data and Analytics | 3 units | This graduate-level course introduces students to the dynamic domain of healthcare data and analytics. Designed to equip students with knowledge of diverse healthcare data sources, analytical methodologies, and their applications within the healthcare industry. The curriculum utilizes a multidisciplinary approach—including lectures, case studies, practical exercises, and group research—to enable students to critically analyze and apply data analytics in optimizing healthcare delivery, engaging patients, and improving health outcomes. |
| MHDA 502 | Programming for Health Analytics | 3 units | Programming for Health Analytics is designed to introduce students to the practical applications of programming in the health analytics field. The course demonstrates the use of programming languages through hands-on exercises and real-world examples, providing a strong foundation for future exploration and specialization in health analytics. |
| MHDA 505 | Data Modeling for Healthcare Analytics | 3 units | In this course, students will explore the intricacies of healthcare data modeling and will delve into data management, database systems, electronic medical records, medical coding, and interoperability standards. Through hands-on projects and theoretical instruction, learners will design healthcare data warehouses, navigate database platforms, and apply medical coding. The course culminates in a comprehensive project, ensuring students are well-prepared for real-world healthcare analytics challenges. |
| MHDA 506 | Healthcare Data Visualization | 3 units | In this course, students will delve into the realm of advanced health care data visualizations, equipping students with the skills to effectively communicate complex health care information through visual representations. Through a combination of theoretical learning and practical exercises, students will explore various visualization techniques, tools, and ethical considerations specific to the health care domain. |
| Certificate 3: Leadership and Strategy in Healthcare Analytics (can be taken as part of the master’s degree or individually) | |||
| MHDA 503 | Leadership and Ethics in Healthcare Data Analytics | 3 units | This course is designed to provide a solid foundation in leadership and ethical decision making with relation to management of Healthcare Data Analytics strategies and functions. Related theoretical concepts are reviewed, and practical applications are emphasized. |
| MHDA 507 | Statistical Analysis for Health Analytics | 3 units | This course offers a comprehensive exploration of statistical methods used in healthcare analytics. Specifically designed to meet the needs of the healthcare industry, the course focuses on various statistical techniques, including descriptive, inferential, and multivariate statistics. Students will learn to apply these methods to healthcare data, enhancing their skills in predictive modeling and advanced experimental design. The course also covers power analysis and survival analysis, equipping students with a robust understanding of these essential concepts in healthcare analytics. |
| MHDA 509 | Machine Learning and Artificial Intelligence in Healthcare | 4 units | This course provides an overview of how artificial intelligence is transforming the healthcare industry. Students will gain hands-on experience applying artificial intelligence and machine-learning techniques to real-world healthcare challenges. Topics covered include data wrangling and cleaning data, linear and logistic regression, decision trees, and popular models in use for machine learning. Students will gain insights on how to deploy big data architectures and why they are essential and used in healthcare and other industries. |
| Culminating Experience for Completion of the M.S. Healthcare Data Analytics | |||
| MHDA 598 |
Graduate Project |
3 units | Prerequisites: MHDA 508 and MHDA 509 or consent from the instructor. This graduate project course is the pinnacle of the Master of Science in Healthcare Data Analytics program, enabling students to synthesize and employ the knowledge and skills they've honed throughout their studies. Through this course, students will undertake projects that tackle genuine healthcare challenges with the aid of data analytics methods. |
