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Course Catalog

Analytics for Healthcare - BMI 524/624

Seminar Instructors: Abhijit Pandit, M.B.A., Tracy Edinger, N.D. 

Credits: 3.0

Content: This course is a broad overview of how analytics is used in healthcare settings. While analytics can take many forms we primarily focus on the use of this framework to advance the goals of healthcare organizations. We attempt to cover the process, infrastructure needs, tools, skills, organization, people and governance to effectively perform this work in a healthcare organization. We do not focus on particular quantitative methodologies and therefore our course should be considered 'non-technical'. Instead we provide a broad overview of the field with exposure to several common tools and software packages. This course is designed for CI-major students.

Prerequisites: None

Offering: Online: Spring

Instructors: Steven Chamberlin, N.D., William Hersh, M.D.

Credits: 3.0

Content: This course is an overview of the application of data science, machine learning, and artificial intelligence in health care settings. Students will be introduced to a wide range of machine learning topics, including identifying health care issues that can be addressed with machine learning solutions, machine learning model development and data source identification, machine learning model implementation, critical appraisal of machine learning literature, and ethical considerations for the application of machine learning and artificial intelligence in health care. Students will also identify an issue in health and develop their own machine learning model to address this issue.

Prereq: BMI 540 or instructor's permission

Offering: Online, Winter

Business of Healthcare Informatics- BMI 519/619

Instructor: Vishnu Mohan, M.D., M.B.I.

Credits: 3.0

Content: This course is designed to provide the health informatics student an overview of the business principles and practices related to the operational informatics environment. At its highest level, the course answers the question: what do clinical informaticians need to know about the business of health care delivery to make them effective in their professional careers?  Specifically, this course presents a systematic, organized approach to health care information technology business solutions, from high-level strategic planning to the tactical system development life cycle, with a focus on clinical information systems and the electronic health record. The course introduces common business-related healthcare IT concepts and tools, such as requirements for development, the request for proposal, hardware and software vendor selection, negotiation, and contracting. Additionally, the course exposes students to commonly utilized information technology governance and management practices, discusses methods to create business plans, addresses strategies to understand and compile clinical informatics budgets, and other relevant fiscal topics. Upon successful completion of the course, students will understand how effective business practices play a critical role in the informatics component of health care organizations. 

Prerequisite: None

Offering: Online: Summer

Capstone Project- BMI 581

Instructor: Varies

Credits: 6.0

Content: A two to three-term capstone project in biomedical informatics is a non-independent project that will be performed under the close supervision of the capstone advisor. Project possibilities include, but are not limited to: developing a project that fits into a larger framework, systematic review, piece of an ongoing research project, substantial background literature review, assisting in grant writing, curriculum revision, or project with an IT organization, such as ITG. For more information, see the Capstone Project Requirements.

Prerequisite: Consent of instructor, Advisor Assignment Form, proposal outline.

Computer Science and Programming for Clinical Informatics- BMI 540/640

Instructor: Lorne Walker, M.D., Ph.D.

Credits: 3.0

Content: An introduction to computer science focusing on data science—the representation and storage of data, computer architecture, algorithms, and Python programming with applications to clinical informatics problems and data. Students must demonstrate knowledge of basic structured programming techniques for admission to the class. Prerequisite: Prior college-level computer programming course and successful completion of a pretest.

Offering: Online: Fall

Note: Enrollment limited to admitted Biomedical Informatics students who have completed an introduction to computer programming prerequisite. Contact BMIgrad@ohsu.edu for options.

Consumer Health Informatics- BMI 520/620

Instructor: Julie Doberne, M.D, Ph.D.

Credits: 3.0

Content: This course focuses on the intersection between consumers, information technologies and health care. We explore the design, use and impact of emerging technologies that aim to engage consumers to participate in their health and health care. Concepts discussed arise from various informatics disciplines as well as health communication, behavioral science, quality improvement, psychology and public health. We will review trends, opportunities and challenges in consumer-facing health information technology, taking the perspective of various stakeholders. Topics include: U.S. trends; information quality; access and usage; clinical integration; online peers; and prevention and chronic illness care.

Prerequisites: None

Note: Enrollment limited to admitted Biomedical Informatics students. Non-BMI students need instructor and department permission

Offering: Online: TBD

Databases- BMI 544/644

Instructor: Michael Lieberman, M.D., M.S., FACP, FAMIA

Credits: 3.0 credits.

Content: An in-depth look at databases and database management systems. Topics covered will include data modeling, hierarchical and relational databases, query languages (SQL), database optimization, and OLAP and data warehousing.

Prerequisite: No prerequisite, but prior completion of BMI 540 suggested.

Offering: Online: Winter

Note: Enrollment limited to admitted Biomedical Informatics students.

Design and Evaluation in Health Informatics- BMI 560/660

Instructor: Vishnu Mohan, M.D., M.B.I., FACP, FAMIA

Credits: 3.0

Content: Research and development projects in the broad field of biomedical informatics can take many forms, from field studies that improve understanding of the tasks and information needs of users, to development projects that design, build, and deploy information systems, to studies that assess the impact of information systems on health care processes and outcomes. This course provides an overview of the concepts, vocabularies, and strategies needed to design and evaluate projects in biomedical informatics, including a breadth of methodologies drawn from qualitative research, quantitative research, and software engineering. This is a required course in the MS and PhD HCIN and is recommended for students in their first year of the program. It is an elective in the graduate certificate.

Prerequisite: BSTA 525 (formerly PHPM 524) or BSTA 511/611, and working knowledge of Excel or consent of instructor.

Offering: Online: Winter

Evidence-Based Medicine - BMI 536/636

Instructor: William Hersh, M.D.

Credits: 3.0

Content: This hybrid course provides a rigorous introduction to the principles of evidence-based medicine (EBM). It begins with an overview of how to frame an answerable clinical question and then find the best evidence to answer it. The major categories of questions that arise in clinical practice - treatment, diagnosis, harm (etiology), and prognosis - are each covered, with instruction on what is the best type of evidence to answer questions, how to find that evidence, and how to apply it to a given patient. This is followed by units on summarizing evidence (e.g., through systematic reviews and meta-analysis), putting evidence into practice (e.g., implementing clinical practice guidelines), and the limitations of the EBM approach. Some pre-campus coursework is required. See syllabus for details.

Prerequisite: BMI 510/610

Offering: Hybrid: Summer (odd years only)

Healthcare Quality - BMI 537/637

Instructor: Michael Lieberman, M.D., M.S., FACP, FAMIA

Credits: 3.0

Content: This course covers methods for measuring, managing and improving the quality of health care. A general overview of the health care system in the United States and beyond is followed by the quality challenges and issues in these systems. Students are also taught the principles of quality improvement and are expected to be able to apply them in practical settings. Current national efforts in performance measures, financial incentives and quality are also covered.

Prerequisite: None

Offering: Online: Spring

Human Computer Interaction in Biomedicine - BMI 548/648

Instructor: Michele Hribar, Ph.D.

Credits: 3.0

Content: This hybrid course will provide an overview of the principles and tools of HCI design and evaluation techniques. It will begin with 6-8 weeks of directed readings with small assignments or quizzes followed by one week on campus and then completion of a project. The on-campus portion of the course will have lectures in the morning and lab sessions in the afternoon, for 5 days. Topics to be covered include: Principles of good interface design, The iterative process of design, Surveying techniques, Discount usability testing, Cognitive processes affecting usability, Think-aloud protocols, Physiological processes that affect usability, Eye-tracking techniques, Quantitative evaluative measures, and Research topics in HCI. Some pre-campus coursework is required.

Prerequisite: None

Offering: Online: Winter

Independent Study- BMI 502/602

Instructor: Varies

Credits: Varies

Prerequisite: Completed 50X/60X form

Information Retrieval- BMI 514/614

Instructor: William Hersh, M.D.

Credits: 3.0

Content: An introduction to text information retrieval in health and biomedicine. After an introduction of models and knowledge-based information, the course covers state-of-the-art approaches to on-line content, indexing, retrieval and evaluation methods. The course then continues with research topics in information retrieval, including automated indexing and retrieval, user interfaces and digital libraries.

Prerequisite: BMI 510/610.

Offering: TBD

Introduction to Biomedical and Health Informatics- BMI 510/610

Instructor: William Hersh, M.D.

Credits: 3.0

Content:  An introduction to the fundamental principles of biomedical and health informatics, the field concerned with the acquisition, storage, and use of data and information in biomedicine and health. The course begins with a basic overview of the field, its terminology, and its resources. It then surveys electronic and personal health records, standards and interoperability, and artificial intelligence, including machine learning, large language models, and their applications in biomedical and health. The course also covers privacy and security, information retrieval, translational bioinformatics, public health informatics, nursing informatics, and consumer health informatics.

Prerequisite: None.

Offering: Online: Fall, Winter, Spring, Summer

Machine Learning - BMI 543/643

Instructor: Xubo Song, Ph.D.

Credits: 3.0

Content: This course aims to provide theoretical foundations and practical experience in machine learning. It will give an overview of many models and algorithms used in modern machine learning, including linear models, multi-layer neural networks, support vector machines, density estimation methods, graphical models, mixture models, clustering,  ensemble methods, and convolutional neural networks. The course will give the student the intuition as well as a more formal understanding of how and why these methods work. Students will have an opportunity to experiment with these techniques and apply them a selected problem in the context of a term project.

Prerequisites: Linear algebra, multivariable calculus, probability, programming language.

Offering: Spring

Managing Ethics in Biomedical Informatics - BMI 576/676

Instructor: Joanne Valerius, M.P.H., R.H.I.A., Ph.D.

Credits: 3.0

Content: The goal of this course is to introduce and sensitize students to the ethical, legal, and social issues arising in the electronic uses of data focusing on research in health informatics. Students will become familiar with managing and implementing legal and regulatory requirements mandated by HIPAA and other rules or laws when needed. Topics will include critical thinking in ethical decision-making; federal rules and regulations in health informatics research, e. g., HIPAA privacy and security rules; ethical issues in genomics, authorship and whistle blowing, funding research, use of informatics technology to inform public health issues, data provenance and data sharing, diversity and discrimination in health care research, and international research, e.g. GDRP. At the end of this course, students will be able to: Perform and communicate ethical decision-making by applying critical thinking in biomedical informatics research issues; identify sources to inform ethical decision-making and change management when needed. Prerequisite: None

Offering: Online: Spring

Medical Decision Making - BMI 538/638

Instructor: Karen Eden, Ph.D.

Credits: 3.0

Content: This course introduces the student to decision analysis (modeling of decisions). Given uncertain information and limited resources, students will learn to model uncertainty and expected outcomes of various decisions. Course will cover Bayesian theory, decision trees, patient utilities, quality of life and cost related to health outcomes. Students will apply decision analysis techniques in addressing real world problems using software (by TreeAge, Inc.) and participate in online discussion of decision analyses in the medical literature.

Offering: Online: Winter

Mentored Teaching Prep- BMI 654

Instructor: Varies

Credits: 1.0

Content: Development of contract with mentor for teaching experience. Decisions will be made regarding lectures, deadlines, scope and topics to be covered. Prepare lesson plans, course materials with Mentor (syllabus, calendar, lectures).

Prerequisite: Doctoral student status

Mentored Teaching- BMI 655

Instructor: Varies

Credits: 3.0

Content: Students teach a subject area course under the mentorship of a faculty member.

Prerequisite: Doctoral student status, BMI 654

Network Science and Biology- BMI 567/667

Instructor: Guanming Wu, Ph.D.

Credits: 3.0

Content: Networks are everywhere: the Internet, social networks, epidemiological networks, protein-protein interaction networks, gene regulatory networks, etc. This course will introduce students to basic concepts shared by many different kinds of networks, with focus on biological networks as examples. Students will learn how to program against networks, search for patterns hidden in networks, and visualize networks generated from real biological data sets.

Prerequisite: Background in linear algebra and calculus and knowledge in statistics are expected. Some programming experience using an object-oriented programming language will be needed in order to complete the course projects.

Offering: On campus: Winter (even years only)

Organizational Behavior and Management- BMI 517/617

Instructor: Chris Hoekstra, Ph.D.

Credits: 3.0

Content: The most important functions of managers in an organization include understanding and motivating individuals and organizing structural systems within which they can work in a productive manner. This course will review the concepts, issues and practices of organizational behavior at the individual, group and organizational levels. Students will practice applying these concepts in simulated situations to improve personal effectiveness in groups or organizations. At the individual level, topics will include perception, decision-making, values, attitudes, job satisfaction, and motivation. The group level topics are work teams, communication, leadership, power and politics, conflict and negotiation. Organizational level topics include organizational structure, work design, human resources policies, organizational culture and change. 

Prerequisite: None.

Offering: Online: Fall, Spring.

Practice of Health Care - BMI 530/630

Instructor: Craig S. McDougall, M.D.

Credits: 3.0

Content: This course introduces the biomedical informatics student to clinical practice, including the underlying biology and manifestations of selected disease states, the information gathering and reasoning processes used to detect, understand and treat diseases, the health professionals who provide and support care and the clinical settings in which care occurs. In addition to class time, students will observe clinicians caring for patients in real world settings. Clinicians are exempt from taking this class. Students in the master's and PhD programs (Medical Informatics track) will need to substitute a different 3-credit class in its place.

Prerequisite: Offsite students must have a laptop with a webcam, an internet connection and a telephone.

Offering: Online: Fall. All students are required to participate in a weekly synchronous online discussion via Sakai Thursday 5:15-7:15 PST. All students are required to participate remotely for 8 or more sessions.

Practicum: Biomedical Informatics- BMI 509/609

Instructor: Varies

Credits: 3.0

Content: A practical hands-on experience in an operational biomedical informatics setting at OHSU, a local health software vendor, or a hospital/health system.

Prerequisite: 50X Form, Consent of Internship Coordinator.

Principles and Practice of Data Visualization - BMI 525/625

Instructor: Steven Bedrick, Ph.D.

Credits: 3.0

Content: This course will give students a foundation in the principles of data visualization, particularly as applied to scientific and technical data, as well as provide students with hands-on experience using modern software tools for developing visualizations. Lecture topics will include an overview of visual perception, color theory and practice, different types of graphs and their purposes, visualizations for specialized forms of data including time-series and geospatial data sets, strategies for working with multidimensional data, etc. There will also be lecture content on ethical issues surrounding data visualization. Weekly lab sessions will introduce students to popular data visualization tools such as R’s ggplot and Shiny, etc.

Prerequisite: Ready for R

Offering:  On Campus: Spring

Project Management in Informatics- BMI 518/618

Instructor: James McCormack, PhD, MT(ASCP)

Credits: 3.0

Content: This course introduces informatics students to the profession and practice of traditional project management. It exposes learners to the concepts, tools, and techniques project managers use to define, plan, control, and close projects, with attention given to the development of both individual and team skills.

Prerequisite: None.

Offering: Online: Winter

Public Health Informatics- BMI 521/621

Instructor: TBD

Credits: 3.0

Content: Recent events underscore the need for a strong public health information infrastructure. Public Health Informatics is the study of how public health information is generated, collected, transferred, and shared. This course is designed to introduce both biomedical informatics and public health students to public health informatics. Course topics will include the information needs of public health professionals; barriers and requirements of a public health information infrastructure; data and process standards; electronic health records; electronic data exchange, including security issues; data registries and sources; evidence-based public health and community health assessment; public health informatics tools, such as GIS; public health reporting and surveillance, including communicable disease, environmental, syndromic, and bioterrorism surveillance.

Prerequisite: None

Offering: TBD

Qualitative Research Methods- BMI 561/661

Instructor: Chris Hoekstra, Ph.D.

Credits: 3.0

Content: Qualitative research methods are used to address why, what, how questions and often triangulated with quantitative methods. This hybrid course will be useful for students taking Organizational Behavior and Management in Informatics when writing their cases. Informaticians who evaluate or conduct research within organizations will find this course a useful foundation when considering data gathering options. Required reading prior to first on-campus session: Crabtree, Miller textbook (see textbook list for details).

Prerequisite: BMI 510/610

Note: Enrollment limited to admitted Biomedical Informatics students.

Offering: Virtual Hybrid: Summer, even years only.  See syllabus for specific virtual participation dates and times (PDT).

Syllabus

Quantitative Research Methods- BMI 562/662

Instructor: TBD

Credits: 3.0

Content: The aim of this course is to help students apply the knowledge gained in previous biostatistics courses to quantitative research problems in biomedical informatics. Students are expected to have a sound understanding of basic techniques in biostatistics including descriptive statistics, t-tests, chi-squared, ANOVA, use of contingency tables, correlation and regression analysis, non-parametric methods and modeling. Each week, we will begin with a research question from the informatics literature (or a student's own research). We will identify appropriate research designs, generate hypotheses (if appropriate), select appropriate test statistics, and use software to analyze the data. At the end of the term, we will have covered ten of the most commonly used statistical techniques in the recent informatics literature.

Upon completion of this course, students should be able to:

1. Generate study designs and hypothesis for common research questions in medical informatics
2. Given a research question and a data set, analyze the data and provide results
3. Provide an interpretation of data analysis that is easily understood by a non-statistician.
4. Critique (and suggest alternatives to) study designs and analyses found in the informatics literature.

Prerequisite: (BSTA 525 or Biostats I & II) and BMI 560 Or consent of instructor.

Offering: TBD

R Boot-camp

Credits: 0.0

Content: This non-credit, self-directed course is intended to introduce the novice programmer to the basics of R programming. The emphasis of this course is on useful R programming skills including loading and manipulating data within R, and secondarily simple visualization, data QC, and statistics. The structure of this course is meant to introduce you to data structures in R such as vectors, lists, matrices, and data frames along with immediate tasks to learn how they work and how to manipulate them. This course is self-paced. You may begin it at any time and proceed at any pace as long as you complete modules in order. For more sophisticated programmers, each module contains a self-evaluation problem and quiz in order to assess whether you need to complete a module or not. Students may register at any time, class is open to everyone at no charge.

Link to R-bootcamp: https://rstudio.cloud/ to create an account. Then https://r-bootcamp.netlify.app/.

Reading and Conference - BMI 505/605

Instructor: Varies

Credits: 1.0-6.0

Content: Students are assigned readings, the meet with instructor to discuss.

Reading and Conference: PhD/Postdoctoral Meeting - BMI 505F/605F

Instructor: Varies

Credits: 1.0

Content: This is a journal club style course in which students are required to present a key paper or research method in their particular field of research. The course is designed to allow the Biomedical Informatics (BMI) PhD students, postdoctoral and clinical fellows to participate in respectful, scholarly discourse in a safe academic learning environment.

Prerequisites: Restricted to BMI PhD students, postdoctoral and clinical fellows. Signature required.

Readings in Bioinformatics and Computational Biology - BMI 553/653

Instructor: James Jacobs, M.D.

Credits: 1.0

Content: This is a seminar style course requiring significant student participation that addresses new and emerging technologies and/or methodologies.

Prerequisites: 550 and 551

Offering: On Campus: Spring

Ready for R

Credits: 0

Content: This course is meant to be a gentle introduction to using R/Rstudio in your daily work. It aims to teach useful skills (visualization, data loading, data filtering and manipulation, simple statistics) that students can immediately use in their work. No prerequisites or previous experience required. It is not meant to be a substitute for a full programming course or a full course in statistics. In the end, students will apply these skills to a final project. To gain access to course materials, go to https://ready4r.netlify.app/mailing. This course is a prerequisite for BSTA 525 Intro to Biostatistics and BMI 569 Data Analytics. 

Prerequisite: None

Offering: Students may begin this self-directed course at any time.

Research in Bioinformatics and Computational Biology-BMI 552A/652A and BMI 552B/652B

Instructor: Eilis Boudreau, M.D., Ph.D.

Credits: 2.0 over 2 quarters

Content: Winter term will focus on developing an independent idea, delving into the lineage of ideas and concepts, managing a bibliography, the basics of project management, introduction to preparing a grant and career development strategies. Spring term will consist primarily of developing research projects. Required of all PhD students; required of all BCB students (PhD and masters).

Prerequisite: None

Offering: On Campus: Winter (1 cr.) and Spring (1 cr.)

Scientific Writing and Communication for Informatics Students - BMI 570/670

Instructor: Kathryn Pyle, A.M.L.S.

Credits: 3.0

Content: The focus of this course is technical writing and communication. Students will draft abstracts and papers; write for their courses and theses; and learn about writing for publication in scientific journals and grant proposals. Topics also include bibliographic database searching and presentations and posters for scientific meetings. Students will complete and present both individual and group writing projects. Students are encouraged to take this course early in their programs prior to beginning their capstones, theses or dissertations.

Prerequisite: None

Note: Enrollment limited to 20 admitted Biomedical Informatics students. Course offered on a Pass/Fail basis. Registration priority given to master's and PhD students.

Offering: Online: Fall

Seminar - BMI 507/607

Instructor: Varies

Credits: 1.0 - 4.0

Content: Special topics in biomedical informatics organized by a group of students or faculty.

Note: Course offered on a Pass/No Pass basis.

Offering: TBA

Software Engineering - BMI 546/646

Instructor: Aaron Cohen, M.D.

Credits: 3.0

Content: This course covers the basic principles of software engineering geared towards providing students with a solid understanding of the process of producing quality software systems on time and on budget. The main activities in software process models are covered in detail, including: proposal creation, requirements gathering and specification, architecture design, software development methodologies, verification and testing, quality management and maintenance. Students will be expected to demonstrate their mastery of the material by the creation of written documentation for several of these main activities on a hypothetical software project of their choice, as well as by answering homework questions based on assigned reading and passing written exams.

Prerequisite: BMI 540/640 OR consent of instructor.

Offering: Online and On-campus: Spring. 

Standards for Interoperability - BMI 516/616

Instructor: Ben Orwoll, M.D.

Credits: 3.0

Content: This course will explore the details of healthcare information technology (HIT) interoperability and standards. The evolution of technology in healthcare, along with the impact on clinical information systems, will be studied. The benefits of integrating healthcare information systems will be investigated, as will the challenges of integrating systems across disparate organizations, healthcare disciplines, and technologies. The value proposition of a standards-based approach to integration will be presented. Students will learn the process of HIT integration projects, and how that parallels the development process of interoperability standards. The course will present an in depth look at standards critical to HIT interoperability – HL7 v2, HL7 v3 RIM, CDA, and SNOMED – and at the use of those standards in national regulations and industry-wide efforts such as IHE. Students will gain experience in navigating through standards documents and tools. Students will utilize the skills and knowledge gained to design a standards-based interoperability project addressing a real-world need.

Prerequisite: BMI 510 or instructor's permission

Offering: Online: Winter

Symposium - BMI 657

Instructor: Varies

Credits: 3.0

Content: State-of-the-art literature synthesis in an area of research from which the student will be questioned and graded during a student symposium. Student symposia will be scheduled during several weeks during the quarter and each student presentation can last no longer than 20 minutes.

Prerequisite: Doctoral student status

Thesis/Dissertation - BMI 503/603

Instructor: Varies

Note: The information included in this catalog was accurate at the time of publication. Information described in this catalog may change without notice. Not all courses are offered each academic year and faculty assignments may change.