Research
The breadth of research topics considered by SDSCSM researchers mirrors our interdisciplinary membership.
Click on a topic for more detail about individual lines of research.
Statistical/Analytic Methods for Decision Making
Mathematical models require numerical data for calibration, and certain kinds of simulation models such as individual microsimulation and agent-based or discrete event models require estimates of individual behaviors, more aggregated models require estimates of average behavior. The Section collaborates with the Department of Biostatistics (developing robust survival estimates for simulation models), Department of Industrial Engineering (simulation modeling and operations research), and the Center for Biomedical Informatics (Bayesean inference and networks). Faculty efforts focus on advancing current knowledge and methodological capabilities in terms of the operational characteristics of these models and their application to calibration of mathematical models and their use in informing practical policy questions.
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Mathematical Modeling of Diseases
The Section is actively involved in the application of multiple types of modeling and simulation techniques to represent biologically or clinically based disease progression. Traditional descriptions of "natural history" that are found in textbooks are not useful for mathematical representations: for most analytic models, diseases need to be represented by the longitudinal progression of the predictors of important clinical outcomes. We have expertise in using discrete event simulation, integer programming, Markov models, Markov Decision Processes, and infectious disease modeling techniques to represent various illnesses and their progression.
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Psychology of Medical Decision Making
An area of growing interest to our Section is the psychological foundation of how patients and providers actually make decisions. In exploring patients' judgments of risk and uncertainty, members of the Section seek to improve decision making by studying the underlying cognitive and emotional processes that interfere with or promote optimal decision making.
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Health State Utilities and Patient Preferences
Since a decision can only be termed "optimal" in the context of a specified goal or value of an outcome, a major area of focus of several members of the Section is improving methods to evaluate and measure individual patient preferences for outcomes. In addition to research on the technical aspects of measurement tools such as the standard gamble and time trade-off, Section members play active roles in developing and evaluating measures of patient and societal quality of life and utility for alcohol use disorders, drug problems, chronic health conditions, and end-of-life care.
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Cost-effectiveness Analysis
The Section has significant expertise in building integrated models of resource use and effectiveness for conducting cost-effectiveness analyses. Clinical topics addressed include alcohol problems, pulmonary artery catheterization, breast cancer, venous thromboembolic disease, and diabetes.
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Health Services Research
Optimal decision making at a societal or health policy level is a major area of interest for the Section. Section members participate in many health services research projects, examining the organization, delivery, and financing of health care from the perspectives of patients, caregivers, and providers. Faculty interests range from assessments of health disparities and system-level outcomes such as cost and access to care to the development of evidence-based healthcare delivery systems.
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Educational Programs
Through the Clinical Research Training Program, Section faculty have developed and teach several courses related to the decision sciences. Independent study with members of the Section is also available. In addition, Section faculty teach national and international courses in decision sciences for the Society for Medical Decision Making, The International Society for Pharmacoeconomics and Outcomes Research, as well as other organizations.
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Miscellaneous
The Section engages in several research projects that do not easily fit into the specific research areas noted above.
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