- The Duke MMCi curriculum is made up of 13 required courses, including a practicum.
- Each course represents two or three credits, for a total of 36 credits.
- All students are required to complete a non-credit ethics and equity seminar that meets four times throughout the year.
- There are no elective courses, and no exemptions or substitutions are permitted.
- Clinical Informatics Certificate Courses are marked with an asterisk (517, 533, 537, 538, 540, & 541)
This course focuses on the design of management accounting systems for analyzing costs in the context of a firm’s business model, as well as the use of managerial accounting data in planning and controlling operations.
This course examines important issues in corporate finance from the perspective of financial managers. The concept of net present value, suitably adapted to account for taxes, uncertainty, and strategic concerns is used to analyze how investment and financing decisions interact to affect the value of a firm.
Using information strategically to transform the delivery of care requires an understanding of the relationship between organizational design and processes. Explore how technology can be a catalyst for organizational change and transformation.
This course introduces the principles, processes, and tools necessary to analyze markets, including customers, competitors, and companies (the 3 Cs) and to design optimal marketing programs via strategies for pricing, promotion, place, and product (the 4 P’s).
Learn the basic facts and principles comprising the processes and activities involved with product delivery – from the extraction of raw materials, through transportation and processing, to the delivery of finished products to the customer.
This course explores business opportunities in dynamic competitive environments to develop the skills necessary to become an effective strategy analyst. You will explore the complexity of analyzing competition and assessing strategy in an era of globalization and increasing uncertainty.
Clinical Informatics Courses
In health care, data comes from many sources including electronic health records, government agencies and clinical research organizations. This course covers the types of analyses that are required to make informed decisions with data. It also demonstrates the tools available to process data. This course prepares students to turn data into knowledge.
Data science, machine learning, and artificial intelligence are now beginning to impact clinical medicine, with performance on some tasks (e.g. detection of skin cancer) exceeding that of experienced clinicians. This course is designed to introduce students to the data science techniques poised to disrupt clinical practice through foundational material and clinical case studies. It will emphasize current methods for analyzing medical images, processing text data (e.g. patient notes), modeling clinical time series, and making sequential decisions based on clinical data. Course content will provide students with an intuitive, applications-oriented foundation in these techniques while highlighting both their capabilities and current limitations. Students will be introduced to pitfalls commonly encountered when developing models for clinical data as well as relevant practical and ethical considerations. (27 CME credits for physicians)
Healthcare is highly regulated and associated with special needs and risks not present in other sectors. The health information system industry echoes this specialization. This course provides an overview of principles and concepts of information technology with a focus on healthcare systems used in the healthcare setting and the industry seeking to serve these uses. You will identify the critical needs of the current health information systems including vendor and healthcare organization perspectives. The course includes an examination of electronic health records, current and emerging use of clinical information systems and applications in clinical health information systems, technologies that support health care information systems, and system design, implementation, maintenance and overview and their impact on organizational resources and efficiency. (27 CME credits for physicians)
This course addresses different strategies for representing data, information and knowledge including description logic, information models, data elements, terminologies and ontologies. Emphasis is placed on the data, information, and knowledge framework for solving problems in health informatics. Declarative and procedural knowledge acquisition, modeling, representation and use will be explored. (27 CME credits for physicians)
Health IT (HIT) solutions have been promoted as a means to reduce the cost and increase the quality of health care delivery in the US and globally. The question we try to assess in this course is how we can deploy health informatics technology to achieve its promise. This question is addressed from a strategic rather than technical perspective. You will develop exploratory frameworks to help analyze potential for impact of IT implementation efforts: scale economics, network economics, and organizational innovation. You will also assess the adoption of technology within existing organizations as well as barriers to adoption. Additionally, you will explore the development of killer apps — how are health IT firms financed and what are successful business models and concepts. Overall, you will grasp the potential for the technology to achieve the cost and quality goals that have been proposed, and the barriers to achieving this success.
Organizational decisions, including accreditation, quality management, and reimbursement would be improved by relevant, timely, accurate, and complete analyses of available data for decision support. This course is designed to introduce theoretical knowledge and practical skills to evaluate and conduct analysis for secondary data available in health care settings. Using epidemiology methods as a framework, you will learn how one can evaluate or conduct secondary data analysis. You will recognize the principles of epidemiology methods applicable to health services and outcome analyses, and understand the terminology and methods for research using secondary data. Threats to validity including selection bias, confounding, information bias, and methods for their control will be discussed in a variety of settings emphasizing practical considerations.
Through a team-based project approach, this capstone course applies the core concepts of the clinical informatics and management courses to a “real world” situation at Duke Health Technology Solutions or in a similar clinical environment. You will explore the relationship between organizational strategy, implementation, and technical applications of health informatics. The practicum usually entails joining an ongoing real-world health IT project and project team, and requires a written, publication quality report of the practicum and related results.
Ethics & Equity Seminar
Each term, a case-based ethics seminar addresses ethical issues in health information technology. Topics may include health disparities; ownership of personal health records; data security breaches and organizational responses, and health literacy and access to electronic medical records.