Courses
BMI 500 Research Methods in Biomedical Informatics (3)
Catalog Description
The course presents an introduction to the conduct of scientific research in biomedical informatics: hypothesis formulation, observation and measurement, design of experiments, execution of protocols, development of essential research skills, and sensitivity to ethical issues that arise in research.
Prerequisites
Admission to any SCI graduate program
Textbook and Other Materials
Critical Appraisal of Epidemiological Studies and Clinical Trials (3rd edition - paperback) by Mark Elwood. Oxford Medical Publications 2007 978-0-19-852955-2.
Course Learning Outcomes
The course covers both quantitative and qualitative approaches. For the quantitative approaches, it focuses on the evaluation of data from systematic reviews of the literature, epidemiological studies, and clinical trials. Topics include the foundation of science, including the basics of probability and statistics, the use of statistical methods for decision-making,, and the roles of data mining, Bayesian methods and meta-analysis in data evaluation. For the qualitative approaches, it focuses on the foundations of qualitative research and on design for data collection and analysis in both laboratory-based and naturalistic environments. Topics include the history of scientific methods and the role of qualitative research, the study of cognition at the individual and group level, representative sampling methods, the use of expert systems and expert consensus, and qualitative models of decision making. These approaches are tied together by an overall focus on the notions of a gold standard and the elements common to critical appraisal in both approaches. Some knowledge of basic statistics and health care domain may be helpful.
Major Topics and Time Covered
Foundations of science
- Logical Empiricism as the root of modern science
- The history of science in medicine: traditional and more modern views
- The role of biostatistics in science
- The role of cognition in science – the “Cognitive Revolution”
- Thought process as valid research data
- Cognitive roots of computer science.
- Hypothesis formulation
- Relationship of theory, frameworks and models in investigative studies
- The use of models to test hypotheses
The role of science in biomedical informatics
- The distinction between making decisions and drawing conclusions
- Statistical models as decision models in bioinformatics
- Decision making and reasoning models based on empirical evidence of human decision making vs. normative models of correct decisions.
- Relationship between evidence and practice: qualitative perspective
- Strengths and limitations of various approaches
Foundations of probability
- The origins of schools of probability
- Subjective versus Frequency approaches to probability
Traditional statistical inference
- T-tests
- Regression analysis
- Fitting multiple regression models
- Bayesian versus Frequency approaches to inference
- Statistical assessment of uncertainty in each approach
- Qualitative trend assessment
Time to event analysis
- Fitting survival curves to data
- Cox proportional hazard models
- Time–series analysis
Data mining
- The relationships among biostatistics, data modeling,
- Epidemiology, evidence-based medicine and decision analysis
- Distinguishing apriori inference from post-hoc inference
- Exploratory data analysis versus classical statistical inference
- Statistical and cognitive learning theories
Study designs: Traditional epidemiological and single subject
- Randomized clinical trials
- Cohort studies
- Case-control studies
- Cross-sectional studies
- Database studies
- Single subject designs: Rationale and theory
- Representative sampling methods
- Cross sectional and longitudinal studies
Study design in applied BMI research
- “Gold standards”
- Experts as a reference standard
- Evaluation metrics: laboratory-based and naturalistic studies
Qualitative and quasi-experimental design
- Differences between qualitative and quantitative approach Validation across experiments and different domains.
- Representative sampling
- Data modeling
- Studying cognition: individual vs. distributed, laboratory vs. naturalistic studies
Approaches to critical appraisals of published studies or databases
- Hierarchy of studies
- Assessing quality within a fixed level
- Issues of reliability and validity
Meta-analysis
- Models of meta-analysis
- Underlying statistical theory and comparative benefits of competing statistical approaches
Evidence-based medicine in Biomedical informatics
- Using epidemiological evidence in the clinical setting
- Use of decision support systems in evidence-based medicine
- Emerging new paradigms for evaluating evidence in decision making
BMI 505 Foundations of Biomedical Informatics Methods II (3)
Catalog Description
The second semester of a two semester course surveying the methods and theories underlying the field of biomedical informatics.
Prerequisites
BMI 502
Textbook and Other Materials
Shortliffe EH and Cimino JJ (eds). Biomedical Informatics Computer Applications in Health Care and Biomedicine, 3rd edition. 2006.
Course Learning Outcomes
Students who complete this course will be able to:
- Understand theoretical foundations and current applications of informatics in health sciences and health care delivery systems.
- Clinical information systems (includes telemedicine).
- Biological information systems (includes Bioinformatics, Pharmacy informatics, and Computation Biology).
- Imaging systems
- Population health information systems (includes consumer health systems).
- Health care management and reimbursement systems.
Major Topics and Time Covered
The course explores techniques in mathematics, logic, decision science, computer science, engineering, cognitive science, management science and epidemiology, and demonstrates the application to health care and biomedicine.
- Language Processing: Information seeking, Information retrieval, Grammars, Parsing, representation
- Cognitive Modeling of Biological Data
- Evaluation and Measurement (Survey instruments, Focus group interviews, etc., usability evaluation of systems).
- Topics in Population and Public Health
- Evidence based medicine theory including guideline development and application
- Heuristic rules in biomedical decision making
- Decision Science (probability, Bayes analysis, information theory, decision analysis, Markov models) and decision support systems.
- Pharmacogenomics
- Medical Imaging and Data Visualization
- Biostatistics (Rates, Ratios, Tables and Graphs, Descriptive Statistics, Correlation Analysis, Probability and Probability Models, Estimation of a Mean, Introduction to Hypothesis Testing). These methods will be taught in connection with the above topics and sequenced through BMI 502 and BMI 505.
BMI 541 Cognition and Decision Making in Healthcare (3)
Catalog Description
Conceptual and methodological issues in cognitive science and medical informatics, including design and use of technology in medical settings.
Prerequisites
Admission to any SCI graduate program
Textbook and Other Materials
D.A. Evans and V.L. Patel (Eds.), Cognitive Science in Medicine: Biomedical Modeling. Cambridge, MA: The MIT Press, 1989.
Course Learning Outcomes
Students who complete this course can expect to:
- Familiarize participants with concepts, methods, and theories of cognitive science.
- Introduce students to issues at the interface between cognitive science and medical informatics.
- Elucidate through readings and discussions the different ways in which cognitive theory can be relevant to the practice of medical informatics and in turn, how medical informatics can meaningfully inform cognitive theory.
- Provide a forum for students to explore the ways in which cognitive science can illuminate aspects of their own research.
Major Topics and Time Covered
Cognitive science is a multidisciplinary field incorporating theories and methods from psychology, linguistics, philosophy, anthropology, and computer science in the study of cognition. Cognitive science provides a framework for analysis and modeling of complex human performance and has considerable applicability to address a range of issues in informatics. Developments in biomedical informatics research have afforded possibilities for great advances in healthcare delivery. These exciting opportunities also present formidable challenges in terms of implementation and integration of technologies in the workplace. As in most domains, there is a gap between technologies and end-users. Since medical practice is a human endeavor, there is a need for bridging disciplines to enable clinicians to benefit from rapid technological advances. This necessitates a broadening of disciplinary boundaries to consider cognitive and social factors pertaining to the design and use of technology.
- Cognitive Science and Biomedical Informatics: Issues at the interface
- Introduction to the Theories and Methods of Cognitive Science
- The Nature of Expertise
- Diagnostic Reasoning
- Decision-making
- Cognition in Context: Naturalistic Decision Making
- Collaborative Cognition: Distributed Cognition
- Cognitive Approaches to the study of Medical Error
- Human Computer Interaction
- Electronic Medical Records: A Cognitive Perspective
- Comprehension and Medical Expertise
- Health Literacy
- Cognitive Usability Evaluation
- Usability and Patient Safety
BMI 591 Human Computer Interaction in Biomedicine (3)
Catalog Description
User interface design, development and evaluation for health information systems, medical simulation systems, medical devices, consumer health web sites, and other healthcare related systems.
Prerequisites
Admission to graduate program in BMI
Course Learning Outcomes
Students will have the opportunity to learn the fundamental principles of human-computer interaction and human factors and learn how to apply them to real world problems through class projects, homework and real-world design. The focus is on learning why user-friendly interfaces can greatly improve work productivity and enhance the quality of healthcare without radically changing the underlying technology.
At the end of the course, students should be able to:
- Identify good and bad aspects of a user interface as related to medical applications
- Understand the fundamentals of multimodal HCI Design
- Perform user analysis to identify user characteristics that need to be addressed in HCI design
- Explain the benefits of HCI guidelines, principle, and theories and adoption of these principles in hospitals and medical centers
- Use various HCI design and prototyping techniques
- Understand the importance of the interdisciplinary cooperation in HCI design
- Identify and implement several formal usability testing techniques, and compare their costs and benefits
- Describe factors that need to be taken into consideration when creating groupware
- Implement user-friendly Graphic User Interfaces in a team environment
- esign a user interface that promotes ease of localization
Major Topics and Time Covered
- Human Side of Human-Computer Interaction
- The Life Cycle of Interface Design
- User and Task Analysis
- Representational Analysis
- Usability Evaluation
- Design for Graphical User Interface
- Design for Web
- Design for Natural Language Interface and Input Devices
- Simulation Design
- Design for Medical Errors
- Design for Multimedia
- Design for Groups: CSCW
- Design for EMR
- Design for PDA