Health Informatics Curriculum
Degree Requirements
Curriculum Overview
The Master's in Health Informatics requires the successful completion of 12 courses. Students must complete five core courses and seven additional courses corresponding to a chosen area of specialization. Specializations allow students to tailor their studies to specific career goals.
Please see the academic catalog for additional information regarding the curriculum. Current students should refer to curriculum requirements in place at time of entry into the program.
Core Requirements:MHI 401 – American Health Care System
The course provides knowledge of the key components of health care in the United States—the policy, economic, and societal forces that shape health care delivery. The course serves as an introduction to elements of the American health care system, including the provider components, the financing of health care, the basic structure of public policy making and public health systems, a comparative analysis of the American system to health care systems of other countries, and the legal and regulatory framework within the American health care system functions. In addition to the structural components of the system, the course reviews current issues within the American health care system, including public health, preparedness, quality of health care, health reform, payment mechanisms, and consumerism.
View All SectionsMHI 403 – Introduction to Health Informatics
The course is an introductory survey of fundamentals of health information technology. Topics center on how information technology enables patient care, how information technology is used by healthcare providers and caregivers, and it’s use to fuel modern health care organizations. This course provides an overview of health informatics with emphasis on the factors that helped create and sustain this new field, the key players involved, and the impact health information technology is having on the delivery of care in a rapidly changing healthcare marketplace.
We explore a range of critical health care informatics topics, including: electronic health records, health information exchange, how health information technology impacts quality of care and patient safety, big data and predictive analytics, clinical decision support and knowledge management, regulatory issues, consumerism and technology, systems integration, and virtual health. The course also explores emerging and new uses of technology.
View All SectionsMHI 407 – Legal, Ethical & Social Issues
The American health care landscape is incredibly dynamic, rapidly evolving, and highly regulated. This course explores the intersection of compelling legal, ethical, and social facets that impact the health care enterprise. The content, research, and group discussions support informaticists in building knowledge they need to navigate competing interests, underlying ethical principles, and key regulatory requirements. The course integrates changing financing paradigms, reimagined health care services delivery systems, the tension between precision medicine and population health, and evolving consumer expectations in the digital age. The challenges of safeguarding individual privacy rights and data security are assessed, along with the promise of innovative public-private partnerships that are shaping health informatics in the Learning Health Care System.
MSHA 480 – Health Analytics Leadership
Note: This course was formerly Leaders 481-DL. Students may not take both Leaders 481-DL and MSHA 480-DL.
This course is designed as an introduction to health analytics leadership practice, high level project management, customer engagement, and effective communication in health care organizations. Healthcare has seen a tremendous increase in available data in the past decade; however much of it is siloed and very difficult to piece together. Physicians and leaders struggle with reliability and transparency of data. Managers struggle to get the data they need to make informed decisions.
Students in analytics-based roles and disciplines will learn organizational strategies for developing and executing a robust Business Intelligence vision and strategic plan. Health care organizations with a strong business intelligence platform enable clinical and business decision making and improve the efficiency of the overall data delivery system.
Leadership strategies including data governance fundamentals, elements of the Business Intelligence (BI) maturity model, and key practices to improve organizational data literacy will be examined. Students will also learn methods to effectively lead projects and engage both leadership and key stakeholders using change management principles, models, and project management tools. Before analytic tasks are undertaken, change management ensures an organizational culture that will support a successful data analytics strategy. Project and portfolio management tools will ensure effective execution of the strategy.
This course introduces best practices in leading change and project management, including: stakeholder engagement, project chartering, scope definition, and key metric development. Students will use these methods and models to demonstrate their understanding and ability to improve project definition and structure. Students should able to execute projects more effectively in their organizations.
The course will also focus on developing effective communication and presentation skills to translate analytics to actionable recommendations that can be used to solve problems in their organizations. Through case scenario exercises, students will deepen their ability to present data analyses and recommendations in a clear and concise manner, evaluate analyses others have done, and articulate the strengths and limitations of their analyses. Students will demonstrate success if they are able to connect and translate their analytics to purpose, process, and people.
Over the next ten weeks, students will examine and analyze current literature and case studies, compare and contrast BI best practices in health care organizations, and demonstrate their learning through assignments, exercises, discussions, and a course project. Students will deepen their ability to develop and deploy a robust BI platform in their health care organization.
MHI 498 or MHI 590 – Capstone or Thesis
Capstone Project
As a culminating experience, students will put into practice the knowledge and skills they have learned during their coursework through a Capstone Project. Students will have the opportunity to develop and implement a Health Informatics project with an industry or university partner or in their workplace. Alternatively, students can develop a culminating, two-part project. This alternative capstone project will leverage health informatics to provide an innovative, consultative response to a need or problem arising as part of a real-world case study. The project will challenge each student to conduct and integrate comprehensive research and to apply knowledge, skills, and competencies built through coursework they have completed in the MHI program.
In addition to each student’s individual research and project development, the course emphasizes collaboration with fellow students by using the Canvas discussion board to crowdsource strategies and approaches for their Capstone Project. Each student will work with the instructor to establish an “Advisory Committee” for their project which, ideally, will be comprised of a “Knowledge Expert” from the organization they are working with and a faculty advisor from the Northwestern University Health Informatics program. Prerequisite: The earliest students may take Capstone is in the quarter of their final MHI course in the program.
Note: Registration for this course will close one week prior to the start of the term.
MHI 590 Thesis Research
The 590 Thesis Research is an individual research project in an independent study format. The paper is written under the supervision of an approved faculty member and presents an opportunity to research and explore a topic thoroughly. The typical time to complete the master’s thesis is four months to a year. Please contact your advisor for information on how to register for the MHI Thesis Research course.
Clinical Informatics Specialization
The Clinical Informatics specialization is designed to prepare students to master the knowledge and skills reflected in the core content for clinical informatics approved by the American Medical Informatics Association (AMIA), which defines the boundaries of the discipline and informs the program requirements for fellowship education in clinical informatics. This specialization also prepares students for board certification in medical informatics, a designated medical subspecialty.
Clinical Informatics Specialization – Required Courses:MHI 405 – HIT Standards and Interoperability
This course provides concepts and practical examples of health care information interoperability, standard terminologies, messaging standards, health information exchanges (HIEs), and projects deploying these capabilities. Topics covered by the course include the importance of standards; information architecture and application programming interfaces (APIs); principles and examples of standard terminologies; current messaging standards; and their use in health information exchanges for coordination of care and payment reform. Core principles, challenges, benefits, and limitations will be discussed in each of these topics.
MHI 406 – Decision Support Systems
This course provides an introduction to decision analysis with an emphasis on medical decision-making and elements of human cognition under uncertainty. Topics include structuring decision problems and developing creative decision options, quantifying uncertainty and preferences, and combining them to arrive at optimal decisions. Also provides the foundation needed to apply the methods of decision analysis in decision support systems and intelligent systems. Students become familiar with the graphical display of medical information, decision analysis and modeling, evidence-based medicine, Bayes' theorem, knowledge-based systems, learning systems, lexicons, coding and structured data entry, and data mining techniques.
MS_IDS 452 – Introduction to Data and Analytics
This course will introduce students to the appropriate uses of analytics and its limitations and define how to approach the various stakeholders within an organization with analytic information. Included will be a review of the ethical, regulatory, and compliance issues related to a given business problem and/or solution. Time will be spent interpreting performance-based organizational issues while concurrently identifying solutions for these same performance-based organizational issues. In addition, time will be spent identifying best practices to plan for engaging, implementing, and sustaining organizational change.
Prerequisites: Students should have a basic understanding of Microsoft Excel.
CIS 413 – Telecommunication Networks
This course provides an overview of telecommunications and data communications. Course work includes local area network (LAN) and wide area network (WAN) components such as switches, routers, telecommunication circuits, and protocols. Advanced topics such as information security, information assurance, advanced networking technologies, and others will be overviewed as well.
MHI 402 – Introduction to Clinical Thinking
Provides insight into the clinical care process. Designed for students not previously involved in clinical medicine as a nurse, pharmacist, or physician, as well as those trained in medicine outside the U.S. Includes basic medical terminology and introductory psychophysiology. Topics include eliciting information from patients, synthesizing history and physical examination, decision making for ordering tests, establishing diagnoses, treatment planning, integrating evidence-based medicine, and using an intelligent medical record in a complex environment.
MHI 404-DL – Health Care Operations
This course examines various aspects of healthcare delivery, with a special focus on healthcare operations and its management to confront the many challenges faced by modern healthcare organizations today with the limited resources at their disposal. Students learn about the role of strategic planning and governance, interdisciplinary care, patient safety and quality improvement, emergency preparedness, cybersecurity, finance, change management, information technology and data analytics.
Recommended taking after MHI 401- American Health Care System and MHI 403- Introduction to Health Informatics
MHI 408 – Information System Acquisition & Lifecycle
A practical course on acquiring and assessing new medical technology, either as a vendor who needs to know how to meet the expectations of customers and their acquisition requirements or as a customer/practitioner who must know how to validate technology selections and implementations. Topics include cost analysis and justification, economic models, capital purchase, leasing strategies, the application service provider or risk-sharing model, purchase agreements and contracts, writing a RFP, analyzing a RFP response, and industry business trends.
MHI 413 – Consumer Digital Health
In this course, we will introduce you to the emerging practice area of Consumer eHealth, the aim of which is to empower consumers to better manage and influence their health and wellness, access healthcare services, and improve interactions with their caregivers by leveraging digital health solutions and services. Topics include solutions that emphasize the consumer experience (CX), new consumer access models and modalities, consumer-oriented technologies and systems such as APPs and health and wellness devices and platforms, HIPAA-compliant cloud based services, the use of innovative wearables (i.e., electronic tattoos), internables/ingestibles and consumables, and behavioral management solutions such a Digiceuticals and PHRs. Additional topics include patient generated healthcare data (PGHD) and the evolution of consumer driven healthcare in the United States: specifically, evaluating how a connected society will enable previously unattainable levels of patient/provider inter-activity.
MSHA 405 Data Literacy and Analytics in Healthcare OR CIS 417 – Database Systems Design & Implementation
MSHA 405-DL Data Literacy and Analytics in Healthcare
Students will learn about current and future data trends, relational databases, healthcare data standards, and the basics of utilizing SQL for data and analytics. Becoming familiar with the fundamentals of relational databases and SQL, the most popular language used to query data from relational databases, is an essential part of this class. Students will leave this course with a strong understanding of standard healthcare terminologies (i.e., RxNorm, SNOMED), relational databases, and how to retrieve, analyze, and aggregate relational data for analytics purposes using SQL. Concepts learned in this class can be used to store, prepare, and analyze large data sets using SQL.
CIS 417 Database Systems Design & Implementation
This course covers the fundamentals of database design and management. Topics include the principles and methodologies of database design, database application development, normalization, referential integrity, security, relational database models, and database languages. Principles are applied by performing written assignments and a project using an SQL database system.
MSHA 409 – Biostatistics
This is an introductory course to general concepts and fundamentals in the practice of biostatistics as commonly used in health data. This will form the foundation for more advanced topics to come in later courses, such as intermediate biostatistics. On its own, the material covered here will be sufficient to perform basic descriptive statistical analyses on your own, and indicate when you should ask for assistance.
The goal of this course is to teach students how to perform basic statistical analysis of health data sets in RStudio. The techniques you’ll learn in this course are important in themselves, and will form the foundation for later courses in the MSHA program, as well as learning how to be productive in R Studio.
MSHA 412 Feature Engineering and Text Mining OR MS_IDS 453 – Techniques of Analytics
MSHA 412 Feature Engineering and Text Mining
This course will provide students with the skills to develop analytical features from health datasets. Students will develop an understanding of healthcare data, particularly electronic health record (EHR) data, and use R & SQL to build features for analytical modeling. In addition to working with continuous and categorical health data, students will understand and develop skills for natural language processing to extract discrete data elements from free-text clinical documentation, such as physician notes, for the development of analytical features. Prerequisite: MSHA 405-DL.
MS_IDS 453 Techniques of Analytics
Students learn to apply statistical techniques to the processing and interpretation of data from various industries and disciplines. This course introduces statistical models as they are used in predictive analytics. It addresses issues of statistical model specification and model selection, as well as best practices in developing models for management.
CIS 436 – Big Data Management & Analytics
This course provides an overview of machine learning concepts, techniques, and tools with a practical emphasis on understanding large, complex datasets and building intelligent systems. Insights gleaned from data mining and machine learning can be used to optimize operational processes, identify new business opportunities, and support evidence-based decision making and digital marketing with applications in industries such as finance, retail, and healthcare. (Required: CIS 417-0 or CIS 417-DL and MSDS 430-DL.)
MSDS 402 – Data Science and Research Practice
This course introduces the field of data science, which combines business strategy, information technology, and modeling methods. The course reviews the benefits and opportunities of data science, as well as organizational, implementation, and ethical issues. The course provides an overview of modeling methods, analytics software, and information systems. It discusses business problems and solutions for traditional and contemporary data management systems, and the selection of appropriate tools for data collection and analysis. The course also reviews approaches to business research, sampling, and survey design.
Prerequisites: None.
MSDS 475 – Project Management
This course introduces best practices in project management, covering the full project life cycle with a focus on globally accepted standards. It reviews traditional methods, including: integration, portfolio and stakeholder management, chartering, scope definition, estimating, the Delphi method and project evaluation and review technique, precedence diagramming and the critical path method, scheduling, risk analysis and management, resource loading and leveling, Gantt charts, earned value analysis and performance indices of project cost/schedule control systems criteria. It shows how the project management maturity model, leadership, team development, and principles of negotiation apply to organizations of various types: hierarchical and matrix organizations, international teams, and virtual teams. Options in project management software systems are included. Using methods and models from this course, analytics managers and team leaders should experience greater project definition and structure. They should be able to execute data science and data engineering projects more effectively.
This is a required course for the Analytics Management specialization.
MS_IDS 401 – User-centered System Design
The User-Centered Design course gives students hands-on experience with the latest design frameworks and methodologies that focus on the end user. Students will learn how a user focused design process can be used to solve the most challenging problems facing businesses and organizations today. Students will be introduced to the latest trends in design thinking, the importance of iterative design frameworks, researching user needs, prototyping, collaboration and critical feedback.
MS_IDS 409 – Data Management Principles: User Perspective
Database systems are at the core of modern information systems. In this course, students will explore the principles of data management and data extraction. Database design, modeling, and implementation concepts will be reviewed and discussed. Students will learn how the different forms of data such as structured data in SQL databases, and unstructured data in NoSQL database systems are stored and accessed. Students will also learn how to query a database and extract useful information to support the decision making process for information design and strategy. The course has hands-on modules that provide the students with SQL and NoSQL programming skills in order to extract and process data from a database engine and present the information in forms suitable for end-users.
MSGH 417 – Global Health Systems
Overview of the structure of the U.S. health systems followed by a selective international comparison of other health delivery systems including their relationships to social policies and economic factors.
MSGH 458 – Global Health and Technology
This is an introductory course positioning technology in the global health landscape. Health systems of the future will increasingly be dependent on technology; how the technology value-proposition is leveraged will be a critical determinant of health outcomes, nowhere more so than in developing countries and resource-scarce settings (DC&RSS). Topics will include: health technology - what’s in a name (unpacking the term); why health technologies matter (linking technologies to burden of disease, healthcare services, quality of care and health outcomes); health technology innovation, introduction/adoption and utilization challenges in DC&RSS; the complementary roles of health technology assessment, regulation and management; health-related technologies and infrastructure as the new frontier for achievement of improved health status in DC&RSS.
Health Technology Informatics Specialization
This specialization is geared for students typically involved in information technology, not necessarily in the health care sector, in roles such as technology suppliers, web developers and administrators, information system coordinators, and IT project managers, among others.
Health Technology Informatics Specialization – Required Courses:MHI 402 – Introduction to Clinical Thinking
Provides insight into the clinical care process. Designed for students not previously involved in clinical medicine as a nurse, pharmacist, or physician, as well as those trained in medicine outside the U.S. Includes basic medical terminology and introductory psychophysiology. Topics include eliciting information from patients, synthesizing history and physical examination, decision making for ordering tests, establishing diagnoses, treatment planning, integrating evidence-based medicine, and using an intelligent medical record in a complex environment.
MHI 404 – Health Care Organization Operations (Recommend taking after MHI 401)
This course examines various aspects of healthcare delivery, with a special focus on healthcare operations and its management to confront the many challenges faced by modern healthcare organizations today with the limited resources at their disposal. Students learn about the role of strategic planning and governance, interdisciplinary care, patient safety and quality improvement, emergency preparedness, cybersecurity, finance, change management, information technology and data analytics.
Recommended taking after MHI 401- American Health Care System and MHI 403- Introduction to Health Informatics
MHI 405 – HIT Standards and Interoperability
This course provides concepts and practical examples of health care information interoperability, standard terminologies, messaging standards, health information exchanges (HIEs), and projects deploying these capabilities. Topics covered by the course include the importance of standards; information architecture and application programming interfaces (APIs); principles and examples of standard terminologies; current messaging standards; and their use in health information exchanges for coordination of care and payment reform. Core principles, challenges, benefits, and limitations will be discussed in each of these topics.
MHI 406 – Decision Support Systems
This course provides an introduction to decision analysis with an emphasis on medical decision-making and elements of human cognition under uncertainty. Topics include structuring decision problems and developing creative decision options, quantifying uncertainty and preferences, and combining them to arrive at optimal decisions. Also provides the foundation needed to apply the methods of decision analysis in decision support systems and intelligent systems. Students become familiar with the graphical display of medical information, decision analysis and modeling, evidence-based medicine, Bayes' theorem, knowledge-based systems, learning systems, lexicons, coding and structured data entry, and data mining techniques.
MHI 408 – Information System Acquisition & Lifecycle
A practical course on acquiring and assessing new medical technology, either as a vendor who needs to know how to meet the expectations of customers and their acquisition requirements or as a customer/practitioner who must know how to validate technology selections and implementations. Topics include cost analysis and justification, economic models, capital purchase, leasing strategies, the application service provider or risk-sharing model, purchase agreements and contracts, writing a RFP, analyzing a RFP response, and industry business trends.
MHI 413 – Consumer Digital Health
In this course, we will introduce you to the emerging practice area of Consumer eHealth, the aim of which is to empower consumers to better manage and influence their health and wellness, access healthcare services, and improve interactions with their caregivers by leveraging digital health solutions and services. Topics include solutions that emphasize the consumer experience (CX), new consumer access models and modalities, consumer-oriented technologies and systems such as APPs and health and wellness devices and platforms, HIPAA-compliant cloud based services, the use of innovative wearables (i.e., electronic tattoos), internables/ingestibles and consumables, and behavioral management solutions such a Digiceuticals and PHRs. Additional topics include patient generated healthcare data (PGHD) and the evolution of consumer driven healthcare in the United States: specifically, evaluating how a connected society will enable previously unattainable levels of patient/provider inter-activity.
MSHA 405 Data Literacy and Analytics in Healthcare OR CIS 417 – Database Systems Design & Implementation
MSHA 405-DL Data Literacy and Analytics in Healthcare
Students will learn about current and future data trends, relational databases, healthcare data standards, and the basics of utilizing SQL for data and analytics. Becoming familiar with the fundamentals of relational databases and SQL, the most popular language used to query data from relational databases, is an essential part of this class. Students will leave this course with a strong understanding of standard healthcare terminologies (i.e., RxNorm, SNOMED), relational databases, and how to retrieve, analyze, and aggregate relational data for analytics purposes using SQL. Concepts learned in this class can be used to store, prepare, and analyze large data sets using SQL.
CIS 417 Database Systems Design & Implementation
This course covers the fundamentals of database design and management. Topics include the principles and methodologies of database design, database application development, normalization, referential integrity, security, relational database models, and database languages. Principles are applied by performing written assignments and a project using an SQL database system.
MSHA 412 Feature Engineering and Text Mining OR MS_IDS 453 – Techniques of Analytics
MSHA 412 Feature Engineering and Text Mining
This course will provide students with the skills to develop analytical features from health datasets. Students will develop an understanding of healthcare data, particularly electronic health record (EHR) data, and use R & SQL to build features for analytical modeling. In addition to working with continuous and categorical health data, students will understand and develop skills for natural language processing to extract discrete data elements from free-text clinical documentation, such as physician notes, for the development of analytical features. Prerequisite: MSHA 405-DL.
MS_IDS 453 Techniques of Analytics
Students learn to apply statistical techniques to the processing and interpretation of data from various industries and disciplines. This course introduces statistical models as they are used in predictive analytics. It addresses issues of statistical model specification and model selection, as well as best practices in developing models for management.
CIS 413 – Telecommunication Networks
This course provides an overview of telecommunications and data communications. Course work includes local area network (LAN) and wide area network (WAN) components such as switches, routers, telecommunication circuits, and protocols. Advanced topics such as information security, information assurance, advanced networking technologies, and others will be overviewed as well.
Note for students in the MSIS program: This is a core course for all students pursuing the MSIS degree, with the exception of students specializing in Analytics and Business Intelligence. Students should take this course at their earliest opportunity.
Note for students in the MHI program: This is a core course for students pursuing the Clinical Informatics specialization.
CIS 436 – Big Data Management & Analytics
This course provides an overview of machine learning concepts, techniques, and tools with a practical emphasis on understanding large, complex datasets and building intelligent systems. Insights gleaned from data mining and machine learning can be used to optimize operational processes, identify new business opportunities, and support evidence-based decision making and digital marketing with applications in industries such as finance, retail, and healthcare. (Required: CIS 417-0 or CIS 417-DL and MSDS 430-DL.)
MSGH 417 – Global Health Systems
Overview of the structure of the U.S. health systems followed by a selective international comparison of other health delivery systems including their relationships to social policies and economic factors.
MSGH 458 – Global Health and Technology
This is an introductory course positioning technology in the global health landscape. Health systems of the future will increasingly be dependent on technology; how the technology value-proposition is leveraged will be a critical determinant of health outcomes, nowhere more so than in developing countries and resource-scarce settings (DC&RSS). Topics will include: health technology - what’s in a name (unpacking the term); why health technologies matter (linking technologies to burden of disease, healthcare services, quality of care and health outcomes); health technology innovation, introduction/adoption and utilization challenges in DC&RSS; the complementary roles of health technology assessment, regulation and management; health-related technologies and infrastructure as the new frontier for achievement of improved health status in DC&RSS.
MS_IDS 401 – User-centered System Design
The User-Centered Design course gives students hands-on experience with the latest design frameworks and methodologies that focus on the end user. Students will learn how a user focused design process can be used to solve the most challenging problems facing businesses and organizations today. Students will be introduced to the latest trends in design thinking, the importance of iterative design frameworks, researching user needs, prototyping, collaboration and critical feedback.
MS_IDS 409 – Data Management Principles: the User Perspective
Database systems are at the core of modern information systems. In this course, students will explore the principles of data management and data extraction. Database design, modeling, and implementation concepts will be reviewed and discussed. Students will learn how the different forms of data such as structured data in SQL databases, and unstructured data in NoSQL database systems are stored and accessed. Students will also learn how to query a database and extract useful information to support the decision making process for information design and strategy. The course has hands-on modules that provide the students with SQL and NoSQL programming skills in order to extract and process data from a database engine and present the information in forms suitable for end-users.
MS_IDS 452 – Introduction to Data and Analytics
This course will introduce students to the appropriate uses of analytics and its limitations and define how to approach the various stakeholders within an organization with analytic information. Included will be a review of the ethical, regulatory, and compliance issues related to a given business problem and/or solution. Time will be spent interpreting performance-based organizational issues while concurrently identifying solutions for these same performance-based organizational issues. In addition, time will be spent identifying best practices to plan for engaging, implementing, and sustaining organizational change.
Prerequisites: Students should have a basic understanding of Microsoft Excel.
MSDS 402 – Data Science and Research Practice
This course introduces the field of data science, which combines business strategy, information technology, and modeling methods. The course reviews the benefits and opportunities of data science, organizational and implementation issues, ethical, regulatory, and compliance issues, while providing an overview of modeling methods, analytics software, and information systems. It discusses business problems and solutions regarding traditional and contemporary data management systems and the selection of appropriate tools for data collection and analysis. It also reviews approaches to business research, sampling, and survey design.
MSDS 475 – Project Management
This course introduces best practices in project management, covering the full project life cycle with a focus on globally accepted standards. It reviews traditional methods, including: integration, portfolio and stakeholder management, chartering, scope definition, estimating, the Delphi method and project evaluation and review technique, precedence diagramming and the critical path method, scheduling, risk analysis and management, resource loading and leveling, Gantt charts, earned value analysis and performance indices of project cost/schedule control systems criteria. It shows how the project management maturity model, leadership, team development, and principles of negotiation apply to organizations of various types: hierarchical and matrix organizations, international teams, and virtual teams. Options in project management software systems are included. Using methods and models from this course, analytics managers and team leaders should experience greater project definition and structure. They should be able to execute data science and data engineering projects more effectively.
Health Administration Informatics Specialization
This specialization is designed for students typically involved in health care business, administrative or management roles in a wide variety of settings such as health care organizations, insurers, consulting, technology firms and government, among others.
Health Administration Informatics Specialization – Required CoursesMHI 402 – Introduction to Clinical Thinking
Provides insight into the clinical care process. Designed for students not previously involved in clinical medicine as a nurse, pharmacist, or physician, as well as those trained in medicine outside the U.S. Includes basic medical terminology and introductory psychophysiology. Topics include eliciting information from patients, synthesizing history and physical examination, decision making for ordering tests, establishing diagnoses, treatment planning, integrating evidence-based medicine, and using an intelligent medical record in a complex environment.
MHI 404 – Health Care Organization Operations
This course examines various aspects of healthcare delivery, with a special focus on healthcare operations and its management to confront the many challenges faced by modern healthcare organizations today with the limited resources at their disposal. Students learn about the role of strategic planning and governance, interdisciplinary care, patient safety and quality improvement, emergency preparedness, cybersecurity, finance, change management, information technology and data analytics.
Recommended taking after MHI 401- American Health Care System and MHI 403- Introduction to Health Informatics
MHI 408 – Information System Acquisition & Lifecycle
A practical course on acquiring and assessing new medical technology, either as a vendor who needs to know how to meet the expectations of customers and their acquisition requirements or as a customer/practitioner who must know how to validate technology selections and implementations. Topics include cost analysis and justification, economic models, capital purchase, leasing strategies, the application service provider or risk-sharing model, purchase agreements and contracts, writing a RFP, analyzing a RFP response, and industry business trends.
MHI 413 – Consumer Digital Health
In this course, we will introduce you to the emerging practice area of Consumer eHealth, the aim of which is to empower consumers to better manage and influence their health and wellness, access healthcare services, and improve interactions with their caregivers by leveraging digital health solutions and services. Topics include solutions that emphasize the consumer experience (CX), new consumer access models and modalities, consumer-oriented technologies and systems such as APPs and health and wellness devices and platforms, HIPAA-compliant cloud based services, the use of innovative wearables (i.e., electronic tattoos), internables/ingestibles and consumables, and behavioral management solutions such a Digiceuticals and PHRs. Additional topics include patient generated healthcare data (PGHD) and the evolution of consumer driven healthcare in the United States: specifically, evaluating how a connected society will enable previously unattainable levels of patient/provider inter-activity.
MHI 405 – HIT Standards and Interoperability
This course provides concepts and practical examples of health care information interoperability, standard terminologies, messaging standards, health information exchanges (HIEs), and projects deploying these capabilities. Topics covered by the course include the importance of standards; information architecture and application programming interfaces (APIs); principles and examples of standard terminologies; current messaging standards; and their use in health information exchanges for coordination of care and payment reform. Core principles, challenges, benefits, and limitations will be discussed in each of these topics.
MHI 406 – Decision Support Systems
This course provides an introduction to decision analysis with an emphasis on medical decision-making and elements of human cognition under uncertainty. Topics include structuring decision problems and developing creative decision options, quantifying uncertainty and preferences, and combining them to arrive at optimal decisions. Also provides the foundation needed to apply the methods of decision analysis in decision support systems and intelligent systems. Students become familiar with the graphical display of medical information, decision analysis and modeling, evidence-based medicine, Bayes' theorem, knowledge-based systems, learning systems, lexicons, coding and structured data entry, and data mining techniques.
MSHA 405-DL Data Literacy and Analytics in Healthcare OR CIS 417 – Database Systems Design & Implementation
MSHA 405-DL Data Literacy and Analytics in Healthcare
Students will learn about current and future data trends, relational databases, healthcare data standards, and the basics of utilizing SQL for data and analytics. Becoming familiar with the fundamentals of relational databases and SQL, the most popular language used to query data from relational databases, is an essential part of this class. Students will leave this course with a strong understanding of standard healthcare terminologies (i.e., RxNorm, SNOMED), relational databases, and how to retrieve, analyze, and aggregate relational data for analytics purposes using SQL. Concepts learned in this class can be used to store, prepare, and analyze large data sets using SQL.
CIS 417 Database Systems Design & Implementation
This course covers the fundamentals of database design and management. Topics include the principles and methodologies of database design, database application development, normalization, referential integrity, security, relational database models, and database languages. Principles are applied by performing written assignments and a project using an SQL database system.
MSHA 412 Feature Engineering and Text Mining OR MS_IDS 453 – Techniques of Analytics
MSHA 412 Feature Engineering and Text Mining
This course will provide students with the skills to develop analytical features from health datasets. Students will develop an understanding of healthcare data, particularly electronic health record (EHR) data, and use R & SQL to build features for analytical modeling. In addition to working with continuous and categorical health data, students will understand and develop skills for natural language processing to extract discrete data elements from free-text clinical documentation, such as physician notes, for the development of analytical features. Prerequisite: MSHA 405-DL.
MS_IDS 453 Techniques of Analytics
Students learn to apply statistical techniques to the processing and interpretation of data from various industries and disciplines. This course introduces statistical models as they are used in predictive analytics. It addresses issues of statistical model specification and model selection, as well as best practices in developing models for management.
MS_IDS 401 – User-centered System Design
The User-Centered Design course gives students hands-on experience with the latest design frameworks and methodologies that focus on the end user. Students will learn how a user focused design process can be used to solve the most challenging problems facing businesses and organizations today. Students will be introduced to the latest trends in design thinking, the importance of iterative design frameworks, researching user needs, prototyping, collaboration and critical feedback.
MS_IDS 409 – Data Management Principles: the User Perspective
Database systems are at the core of modern information systems. In this course, students will explore the principles of data management and data extraction. Database design, modeling, and implementation concepts will be reviewed and discussed. Students will learn how the different forms of data such as structured data in SQL databases, and unstructured data in NoSQL database systems are stored and accessed. Students will also learn how to query a database and extract useful information to support the decision making process for information design and strategy. The course has hands-on modules that provide the students with SQL and NoSQL programming skills in order to extract and process data from a database engine and present the information in forms suitable for end-users.
MS_IDS 452 – Introduction to Data and Analytics
This course will introduce students to the appropriate uses of analytics and its limitations and define how to approach the various stakeholders within an organization with analytic information. Included will be a review of the ethical, regulatory, and compliance issues related to a given business problem and/or solution. Time will be spent interpreting performance-based organizational issues while concurrently identifying solutions for these same performance-based organizational issues. In addition, time will be spent identifying best practices to plan for engaging, implementing, and sustaining organizational change.
Prerequisites: Students should have a basic understanding of Microsoft Excel.
MSDS 402 – Data Science and Research Practice
This course introduces the field of data science, which combines business strategy, information technology, and modeling methods. The course reviews the benefits and opportunities of data science, organizational and implementation issues, ethical, regulatory, and compliance issues, while providing an overview of modeling methods, analytics software, and information systems. It discusses business problems and solutions regarding traditional and contemporary data management systems and the selection of appropriate tools for data collection and analysis. It also reviews approaches to business research, sampling, and survey design.
MSDS 475 – Project Management
This course introduces best practices in project management, covering the full project life cycle with a focus on globally accepted standards. It reviews traditional methods, including: integration, portfolio and stakeholder management, chartering, scope definition, estimating, the Delphi method and project evaluation and review technique, precedence diagramming and the critical path method, scheduling, risk analysis and management, resource loading and leveling, Gantt charts, earned value analysis and performance indices of project cost/schedule control systems criteria. It shows how the project management maturity model, leadership, team development, and principles of negotiation apply to organizations of various types: hierarchical and matrix organizations, international teams, and virtual teams. Options in project management software systems are included. Using methods and models from this course, analytics managers and team leaders should experience greater project definition and structure. They should be able to execute data science and data engineering projects more effectively.
CIS 413 – Telecommunication Networks
This course provides an overview of telecommunications and data communications. Course work includes local area network (LAN) and wide area network (WAN) components such as switches, routers, telecommunication circuits, and protocols. Advanced topics such as information security, information assurance, advanced networking technologies, and others will be overviewed as well.
Note for students in the MSIS program: This is a core course for all students pursuing the MSIS degree, with the exception of students specializing in Analytics and Business Intelligence. Students should take this course at their earliest opportunity.
Note for students in the MHI/MMI program: This is a core course for students pursuing the Clinical Informatics specialization.
CIS 436 – Big Data Management & Analytics
This course provides an overview of machine learning concepts, techniques, and tools with a practical emphasis on understanding large, complex datasets and building intelligent systems. Insights gleaned from data mining and machine learning can be used to optimize operational processes, identify new business opportunities, and support evidence-based decision making and digital marketing with applications in industries such as finance, retail, and healthcare. (Required: CIS 417-0 or CIS 417-DL and MSDS 430-DL.)
MSGH 417 – Global Health Systems
Overview of the structure of the U.S. health systems followed by a selective international comparison of other health delivery systems including their relationships to social policies and economic factors.
MSGH 458 – Global Health and Technology
This is an introductory course positioning technology in the global health landscape. Health systems of the future will increasingly be dependent on technology; how the technology value-proposition is leveraged will be a critical determinant of health outcomes, nowhere more so than in developing countries and resource-scarce settings (DC&RSS). Topics will include: health technology - what’s in a name (unpacking the term); why health technologies matter (linking technologies to burden of disease, healthcare services, quality of care and health outcomes); health technology innovation, introduction/adoption and utilization challenges in DC&RSS; the complementary roles of health technology assessment, regulation and management; health-related technologies and infrastructure as the new frontier for achievement of improved health status in DC&RSS.