We use basic and advanced statistical models to understand cause and effect, test hypotheses and evaluate interventions, as well as predict and prepare for potential system breakdowns.
Key elements of statistical decision support include:
- Making decisions with multiple objectives and shared goals
- Leveraging the value of data and information
Statistical tools include:
- Discrete Simulation using FlexSim software
- Operations Research
- Differential Equations
Examples of our work in statistical decision support include:
- Optimizing Preceptor Scheduling using 4-factor analysis
- Evaluating an urgent care area in the ED: see simulation video