MA in Sports Administration

Curriculum: Sports Analytics Specialization

This specialization, offered only online, provides technical and leadership training required for key positions in sports team management and analytics. It provides an understanding of how to work in sports management roles in today’s data-intensive and data-driven world. Building upon Northwestern University's graduate program in predictive analytics and data science, it reviews key technologies in analytics and modeling, probability theory, applied mathematics, statistics and programming. It shows how analytic techniques may be utilized in evaluating player and team performance and in sports team administration. Students pursuing the Sports Analytics specialization are required to take the four-course, online predictive analytics sequence below to fulfill both core and elective requirements. MSA electives do not qualify for this specialization.

Core Courses

  • 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.

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  • MHI 403-DL  Fundamental 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.

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  • MHI 407-DL  Legal, Ethical & Social Issues

    This course addresses the legal, ethical, and social issues in health care informatics and will equip students with the knowledge and analytic tools needed to spot those key issues, thereby better protecting students and their employers in the medical informatics field. The health care industry is highly regulated, and this course also covers regulatory informatics requirements as they apply to work with health care data and information management systems. The course also covers topics such as privacy and security, fraud and abuse, confidentiality, antitrust law, intellectual property, the Joint Commission, disclosure, and compliance programs.

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Clinical Informatics Specialization

  •           REQUIRED COURSES:
  • MS IDS 452-DL  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.

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  • CIS 413-DL  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.

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  • MHI 405  HIT Integration, Interoperability, & Standards

    This course provides the details of health care technology standards and interoperability. Topics include the value proposition of standards; health information models; the IHE Initiative; HL7, DICOM, CCOW, CorbaMED, and other medical standards. The course also covers the role of nonmedical standards in medical informatics (HTTP, XML, etc.) as well as multi-institutional issues and telemedicine, e-commerce, and Health Insurance Portability and Accountability Act standards compliance.

  • 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 covered include structuring decision problems and developing creative decision options, quantifying uncertainty and preferences, and combining them to arrive at optimal decisions. The course 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.

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  •           ELECTIVES — CHOOSE 3:
  • MHI 402  Introduction to Clinical Thinking

    This course provides an introduction to the clinical environment throughout the health center. It is designed for students not previously involved in clinical medicine and those trained in medicine outside the United States. The course features problem-based learning and traditional medical informatics task domains and covers medical terminology and basic pathophysiology. Topics include the clinical setting, eliciting information from patients, synthesizing the history and physical examination, establishing diagnosis, treatment planning, integrating evidence-based medicine, and using an intelligent medical record in a complex environment.

    This course is assigned upon admission to students with little experience in this topic. It is recommended that students, for whom it is assigned, complete this course before undertaking any of the core courses.

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  • 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 an RFP, analyzing a RFP response, and the industry business trends.

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  • MHI 409  Biostatistics

    This course is designed for the biomedical researcher. Topics include descriptive statistics, hypothesis testing, estimation, t-tests, chi-squared tests, analysis of variance, linear regression, correlation, nonparametric tests, survival analysis, and odds ratio. Biomedical applications are discussed for each topic as well as overall application of statistical methods in the informatics field. 

  • 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.

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  • CIS 435  Practical Data Science Using Machine Learning

    This course provides an introduction to data science with a focus on building real-life business applications using machine learning. Students learn data mining applications, core concepts, algorithms and overview of open source/commercial tools. This course takes a hands-on approach to this topic and prepares students for applying appropriate machine learning modeling techniques (Collaborative Filtering, Association, Clustering and Classification) for given real-world use cases. Students learn via experimentation; they observe the outcome of applying machine learning algorithms to structured and unstructured data using open source software.

    It is highly recommended that all students complete CIS 417 or possess equivalent knowledge and skills prior to taking this course.

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  • CIS 436  Big Data Management & Analytics

    This course reviews concepts behind both centralized and distributed database systems, and relational and not-only-relational database systems. Discussion of open source and commercial solutions, with special attention being paid to large distributed database systems and data warehousing. The course introduces technologies and modeling methods for large-scale, distributed analytics.

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  • CIS 494  Project Management Concepts

    Project Management is increasingly seen as an integral part of the modern workforce. Project Management Concepts will prepare students for effective project management strategies that can be applied to any project, independent of industry. Students will master project management methods and techniques critical to the formation of professional project plans. Team development, communication, stakeholder management, and organization dynamics will be topics covered.

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  • 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.

  • PREDICT 402  Introduction to Predictive Analytics

    This course introduces the field of predictive analytics, 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. 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 reviews approaches to business research, sampling, and survey design.

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  • PREDICT 475  Predictive Analytics 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 on Agile and MS Project are included. Using methods and models from this course, predictive analytics managers should experience greater project definition and structure and be able to execute projects more effectively.

  • 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. This course explores the role of public institutions and NGOs in healthcare delivery in low, middle, and high-income countries from social, political, and economic perspectives. Topics include historical and contemporary international development theory, international aid and its impact on health systems, supply chain management, comparison of health insurance providers and markets, and global health governance.

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  • 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.

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  • MS IDS 409  Data Management Principles: User Perspective

    Databases underlie all electronic systems, from websites and software to video games. This course will introduce students to data management concepts, such as metadata and controlled vocabularies, and demonstrate how these structures affect human-computer interactions. Students will learn how to describe and query different forms of information such as structured data in relational databases, unstructured text, and semi-structured data (XML, web). Students will also learn how to find patterns in data and to perform information mapping, conceptual modeling, and schema design. The course focuses on a user's perspective, rather than how one implements a database system.

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  • 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.

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  • MHI 413  Consumer eHealth

    This course introduces the student to the emerging practice area of Consumer eHealth, the aim of which is to empower consumers to better manage and influence their wellness, access to healthcare services, and healthcare protocols. Topics include access modalities such as consumer-oriented applications and relevant HIT systems, actionable processes and technologies, such as the application of innovative wearables, internables, and consumables, and behavioral management systems, such as PHRs, NwHIN services, and the Blue Button and Sharecare initiatives. Additional topics include the evolution of consumer driven healthcare in the United States, specifically evaluating how a connected society will enable previously unattainable levels of patient / provider interactivity.

  • MHI 414  Emerging Federal Regulation & Policy

    This course addresses emerging developments in the dynamic federal regulation of health care as it impacts health information technology and informatics. The course equips students with the knowledge they need to track key legislation, rules and policy issued by federal legislators and regulatory agencies, thereby preparing students and their employers to make proactive business and compliance decisions. Health care is highly regulated, and this course examines effects on quality of care, payment methodologies, care delivery systems, and information management. The course explores the roles of public and private sector bodies in shaping health information technology as a driver of health care services delivery and financing.

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Final Project

  • About the final project   

    The final project combines research with hands-on experience and provides an opportunity for students to take advantage of the resources of Northwestern University and the Feinberg School of Medicine. Students may pursue their capstone experience independently or as part of a team. As their final course, students take either the individual research project in an independent study format or the classroom final project class in which students integrate the knowledge they have gained in the core curriculum in a project presented by the instructor. In both cases students are guided by faculty in exploring the body of knowledge on medical informatics while contributing research of practical value to the field. The capstone independent project and capstone class project count as one unit of credit.

  • MHI 498-DL  Capstone Project 

    The capstone project course is the culmination of the MHI program and provides students the opportunity to demonstrate mastery of the core competencies in the medical informatics field. Students, working in small groups, will also complete a comprehensive project provided by the instructor at the beginning of the course. Students are individually assessed and graded throughout the duration of class. Students may choose this course to fulfill their capstone requirement.

    Prerequisite: the earliest students may take MHI 498 is in the quarter of their final class.

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  • MHI 590-DL  Thesis Research 

    This final project is meant to represent the culmination of students’ experience in the program and must demonstrate mastery of the curriculum and ability to conduct sustained independent research and analysis. The project may be applied or may be a traditional scholarly paper, in both cases a write-up following the paper’s program-specific guidelines is required. Students must submit a proposal and secure a first reader in order to register; for further details students are advised to review the student handbook and contact their academic adviser.