The online MS in Health Informatics & Analytics at Tufts School of Medicine is an interdisciplinary program that combines course work in healthcare, IT, information management and data science. Taught by distinguished professors who are experts in their field, courses will prepare you to use emerging technologies, analytical tools, and existing information systems to improve patient outcomes and develop better solutions for health organizations.
HIA201 Introduction to Health Informatics and Analytics (3 credits)
This 14-week course provides an overview of the fields of informatics and analytics in the context of data lifecycle, how they emerged overtime following the evolution of information technology, and specifically, health information technology (electronic health records, telehealth and digital health). Commonalities of these two disciplines (terminologies, approaches, standards, domains of use, the roles of users) and their complementary roles in the data/information/knowledge generation process are emphasized. Students will learn how these disciplines are used in healthcare, public health and research via specific business cases and use cases. The course includes asynchronous lectures and subject matter expert panels, live online class discussions, individual assessments, and group exercises on business case/use case development.
HIA230 Health Data Analysis and Usage (3 credits)
This course has two main parts. The first is an introduction to health data analysis (DA) and the second is health data usage (DU).
The first half of the course (7 weeks) will introduce students to data analysis concepts in health informatics. In essence, this will be a gentle introduction into the principles of epidemiology (study types, concepts of prevalence and incidence, measures of risk and confidence intervals, confounding, test validation/screening, etc) and biostatistics (descriptive vs. analytic statistics, the p-value, univariable and multivariable analyses, etc). All of this will be an introduction to the concepts and principles of data analysis, not into the many ways data are analyzed in practice.
The second 7 weeks of the course provide a broad overview of how health data are used today. We discuss the health data ecosystem and technologies, and data in healthcare, clinical research, and public health. Special topics are social determinants of health and environmental data. The asynchronous material is provided by faculty with expertise in these fields. Assessments will be weekly, both individually and in groups, and with a final paper critique group assignment, as well as a final paper about a health data topic relevant to students’ interest.
Each week has one block of asynchronous instruction (90 min online video and presentation) and one block of synchronous instruction (90min online classroom via Zoom). All preparatory asynchronous material is reviewing a certain area of health data usage and each synchronous meeting will have a group activity related to data analysis and usage as well as a journal club looking at the data analysis and usage in a particular paper selected by students. This will initiate a discussion about students’ experiences and/or areas of interest in relation to the weekly topic.
HIA203 Digital Health (3 credits)
We all generate data through smartphones, sensors, trackers, and other devices, and our physicians generate data about us. In this course, we look at how medical practitioners, technology professionals, data analysts, and public health professionals use technology and data to bring value to the lives of patients. This course focuses on the variety of technologies available, how they are used, and how they can be used ethically to assist in behavior change, diagnosis, and treatment for individuals and populations. The course provides an overview of digital health through lectures, readings and expert guest interviews. Students engage with real technologies, and examine the experience of using these, and their potential applications, through assignments and class discussion. The course culminates in a group design project, where students create a viable digital solution to a health problem.
HIA215 Quality and Outcomes (3 credits)
The course reviews the fundamental steps, measures, and data analysis requirements for systems and quality improvement necessary in healthcare. The content will address systems and quality improvement theories, root cause analysis, and change management steps. Commonly used measurements, statistical tools, quality structure, process, and outcomes will be addressed to evaluate outcomes of quality and safety initiatives in healthcare settings. The course will also address the importance of interprofessional collaboration in the context of change improvement using evidence- based practice, reviewing the implications of variation in practice, and understanding the difference between research and clinical quality improvement. Course information will emphasize approaches applied to solving actual problems using clinical use case scenario.
HIA218 Introduction to Big Data Analysis and Artificial Intelligence in Healthcare (3 credits)
In this 14-week course, students will learn to understand and apply concepts in Big Data (BD) analytics and Artificial Intelligence (AI)- the two key catalyzers for technological revolution within the context of the healthcare industry and analyze case studies from healthcare, public health and research. The students will be introduced to the concepts of BD, AI and Machine Learning (ML) and their application in health care. Students will explore the application of supervised, unsupervised ML algorithms and Natural Language Programming (NLP) through various use cases in health care including medical diagnosis, disease management, screening, and clinical decision support. Advantages, disadvantages and ethics of leveraging AI and BD in the health care domain will be discussed. As a hands-on lab, students will work with R/ R Studio to apply the concepts taught in class. The course will prepare students for a career in health informatics and analytics space through a real-world understanding of the role of BD and AI within the health care context.
HIA220 Business of Healthcare (3 credits)
The Business of Healthcare is a 14-week elective that will provide students a foundation for understanding financial and operational management of healthcare organizations. The course will begin with a global overview of how the US healthcare system is financed and show how that translates locally into a healthcare organization’s budget. Students will learn how to properly create and monitor a budget while also learning to benchmark financial as well as non-financial performance in the industry. After the financial management foundation is set, the course will then explore general management topics and assist with developing useful skills in human resources management, project management, strategic planning, conflict resolution and negotiations.
HIA222 Fundamentals of Privacy and Security in Health IT (3 credits)
This 14-week elective course is focused on best practices in health information technology (HIT) security and privacy used to safeguard the confidentiality, integrity, availability and privacy of health data, especially, Personal Health Information (PHI). As such, students will develop a practical understanding of: (a) laws, regulations and policies related to information assurance, security and privacy of data in healthcare systems, (b) Health Information Portability and Accountability Act (HIPAA) regulation and the legal and other consequences of non-compliance with the HIPAA security rule; (b) security threats and what to do in event of a breach of HIT systems and the unauthorized disclosure of PHI; and (c) the role of usable security and risk management to protect PHI and other healthcare data.
HIA226 Data Wrangling (1.5 credits)
This 7-week course provides the foundation for students who wish to engage in data analytics. The course introduces the basics of using software R and various downloaded expansion packages to compile and manage data sets for analyses. It also introduces the use of Structured Query Language (SQL) in data set preparation. Upon successful completion of the seven-week course, students will be able to carry out simple to moderate data abstraction tasks, so that they can be ready to build a stronger understanding of the data and their inter-relationship prior to in-depth analysis. All weeks include asynchronous lectures, and synchronous online live sessions, and individual assessments.
HIA204 Health Information Systems, Standards, Decision Support (3 credits)
This 14-week course is focused on the use of health information technology (HIT) in healthcare organizations. The course consists of 3 modules: (1) introduction to health information systems in care delivery settings including electronic health record systems, financial systems, laboratory information systems, imaging information systems, personal health record, telehealth, mobile health, public health and population health systems; (2) HIT standards and systems interoperability; and (3) clinical decision support. Using various use case examples, students will learn how informatics and analytics projects enable successful HIT adoption and use by health professionals. The course includes asynchronous lectures and subject matter expert panels, live online class discussions, individual assessments, and group final assignment on evaluating/critiquing health informatics and analytics project from the publications in the Journal of American Health Informatics Association (AMIA).
HIA205 Design and Evaluation of Digital Health Technologies (3 credits)
Digital Technologies are transforming healthcare in a variety of beneficial ways, from streamlining workflow processes to making more precise patient diagnoses. In this course, you will learn how digital technologies in healthcare are designed applying the principles of user-centered design and cognitive psychology. You will learn and apply a rigorous, objective, and standardized process of evaluating various health technologies such as web portals, smartphone apps, clinical decision support and population health management tools. Through the course, you will also investigate the barriers and opportunities for implementing digital technologies in healthcare settings to transform patient care. Finally, you will explore the roles, teams and skills required to enable technology implementation in healthcare settings in addition to exploring the regulatory and ethical aspects.
HIA211 Informatics Fundamentals (1.5 credits)
In this 7-week course students will develop an understanding of health informatics, broadly considered. The course learning objectives include gaining a system view of information problems, which activity includes examining broad context, organizational issues, roles, business processes, information system, data, information, knowledge, algorithms, and underlying technologies. It includes lectures, reading, tutorials, “live talks,” quizzes and a final project.
HIA212 Informatics for Healthcare Professionals (1.5 credits)
This 7-week course is designed for healthcare professionals. The course learning objectives include applying a system view of informatic problems and gaining practical skills in guiding the development of information technology solutions in healthcare delivery and population health. The course is built around relevant business cases/use cases and functional requirements analysis related to direct patient care in ambulatory or hospital settings, including clinical documentation, care coordination, and medication management. The course includes asynchronous lectures, live online class discussions, individual assessments, and group exercises on business case/use case development.
HIA213 Informatics for Public Health Professionals (1.5 credits)
This 7-week course is designed for public health professionals. The course learning objectives include applying a system view of informatic problems and gaining practical skills in guiding the development of information technology solutions for public health practice and health services research. The course is built around relevant business cases/use cases and functional requirements analysis related to public health practices including health statistics, electronic data reporting, syndromic surveillance, and emergency preparedness. The course includes asynchronous lectures and subject matter expert panels, live online class discussions, individual assessments, and group exercises on business case/use case development.
HIA214 Informatics for Clinical Research (1.5 credits)
In this 7-week students will develop an understanding of informatics principles and tools that support the clinical-research life cycle. The course learning objectives include learning the research life cycle, the potential for supporting each phase of that cycle, and currently available tools and initiatives. The course is built around relevant use cases related to clinical research. It includes lectures, reading, tutorials, “live talks,” quizzes and a final project.
HIA 227 Applied Univariable and Bivariable Statistics (1.5 credits)
This seven-week course introduces the fundamental concepts of summarizing data and statistical inference, including descriptive statistics, graphical displays, hypothesis testing of means and proportions, p-values, confidence intervals, and statistical power. Students will analyze data using R and learn how to interpret results and report findings.
All seven weeks include asynchronous learning and live online synchronous sessions, and individual assessments.
This seven-week course introduces the principles of regression modelling, including simple linear regression, multiple linear regression, two-factor analysis of variance, and logistic regression. Students will analyze data using R and learn how to interpret results, assess model fit, create prediction equations, and report findings.
All seven weeks include asynchronous learning and live online synchronous sessions, and individual assessments.
HIA 229 Data Visualization (1.5 credits)
During the 7-week course, students will learn how to graphically express their quantitative results. Important concepts and practices in data visualization will be discussed, as well as exploring how to create clear and well-planned graphs using the ggplot2 package of R and commercial software Tableau. As a culminating experience, students will present their individual data analysis and visualization project in the last week.
All 7 weeks include asynchronous lectures, synchronous online live sessions, and individual assignments.
HIA219 GIS/Spatial Epidemiology (3 credits)
In public health, “place” matters as it is a close reflection of the social and economic deprivation and environmental exposures that can result in significant health disparities that are manifest in health outcomes. Geographic information systems (GIS) and spatial epidemiology are important tools that allow us to present and critically assess spatial distributions and associations. This course will provide students with the basic skills needed to obtain, clean, analyze, and decipher spatial data in a GIS, using a variety of examples (use cases) from public health, nutrition, urban development, and the US Census Bureau.
HIA221 Data Trust – Information Governance in Health (3 credits)
Information Governance (IG) is defined as an enterprise-wide framework that defines how information is controlled, accessed, and used, as well as the mechanisms that enforce it. IG Framework is a foundation for the data trust within and across organizations. This 14-week elective provides students with an understanding of IG framework in the modern electronic-health data environment; the needs for such a framework; and the process and the implications of putting one into place. Student will learn practical skills in (a) using IG in the creation, management, use and re-use of electronic information and “legacy” printed information, (b) legal aspects of electronic information in healthcare including the electronic Legal Health Record, (c) using standards to support IG in e-Health, and (d) methods for instituting IG practices.
HIA 223 Organizational Behavior, Leadership and Change Management (3 credits)
This 14-week course provides students with an understanding of the principles of organizational behavior (people, structure, technology, and the external environment), leadership and change; change management and why change management matters in the success of health informatics and analytics projects. The ability to understand organizational behavior and apply leadership and change management is essential in today’s workforce and a required competency regardless of the person’s role in the organization. Students will develop an understanding of the principles of organizational behavior, leadership, and change management, all with an emphasis on sustaining positive outcomes from informatics and analytics projects. Students will develop strategies for building organizational capacities ensuring engagement of stakeholders and employees. Students will also learn a range of inter-personal skills for teamwork and collaboration, conflict resolution and negotiation, and management and leadership.
HIA 224 Project Management (1.5 credits)
This 7-week course provides students with a foundation in project management. Project management competency is essential in healthcare, where projects launched are more complex than previously. The ability to shepherd health informatics and analytics projects through, from making the business case through to capturing lessons learned for continuous improvement, is essential for ensuring projects meet the defined objectives and are completed within the limited time often allocated for completion. Students in this course will learn a variety of best practices, tools and techniques that will enable them to better manage and oversee health informatics and analytics projects of any complexity and size. Students will develop a comprehensive project management plan to manage projects, creating a variety of project artifacts necessary for overall project management and ultimate success in the project implementation.
HIA225 Introduction to Python for Health Informatics and Analytics (1.5 credits)
Python is one of the most widely used programming languages in health informatics and analytics. This 7-week course provides a high-level introduction to the Python language and familiarize you with how it is used in some healthcare settings. You will have an introductory session on the language and user interfaces available, do some coding, and review existing, real-life code examples from healthcare and public health applications. This course is intended for students with no prior coding experience. Note that this is not a programming course.
The Capstone Planning Immersion is a cumulative practice-based experience to begin the student’s capstone project for the Health Informatics and Analytics Program. The purpose of the immersion weekend is to prepare the HIA student to apply the skills and knowledge that they have acquired during their time in the HIA Program to complete a Health Informatics or Health Analytics project with an organization with the assistance of their advisor, career services and/or other faculty members. Students initiate and design capstone projects in consultation with faculty, career services and Capstone organizations. Faculty members provide guidance and mentoring. Requires prior completion of at least three semesters of graduate study in health informatics. During their immersion students will participate in seminars, lectures, and group discussions with HIA faculty, subject matter experts, and classmates to conceptualize how they will initiate, plan and execute a project in their chosen track of either Health Informatics or Analytics.
HIA302 Capstone Practicum (3 credits)
As a culminating experience, students will put into practice the knowledge and skills they learned during their coursework through the Capstone Practicum. The Capstone Practicum will provide the student a launching pad to pursue opportunities for professional growth and development in the field of health informatics and health analytics. Students will have the opportunity to develop and implement a health informatics or health analytics project within a host organization, or within their workplace.
Students will identify a health care need/problem and use the methodologies learned in the HIA program to address the problem including creating new data management resources, optimizing current data systems, conducting data analytics, building machine learning algorithms, deploying clinical decision support systems, designing and evaluating new technology solutions. Students will engage with problems in a variety of settings: clinical, research, and industry (health technology companies, pharmaceutical companies). During the Capstone Practicum, students will have the opportunity to continue developing these skills, while they earn recognition for their professional competence, technical skills and leadership acumen. The program will also aid students in identifying viable Capstone projects and establishing a preceptor for oversight and mentorship.