Description: This course introduces the students to the use of spreadsheets and relational databases for decision-making. It covers data manipulation and analysis, formatting and charting using Microsoft Excel; as well as design and implementation of, and data retrieval from, small-to-medium relational database systems using Microsoft Access.
Prerequisites: Biostat 501 or Biostat 521 or equiv and Grad Status
Description: Provides rational framework for decision making for both operating and control systems in the hospital environment. Emphasizes basic modeling techniques and examples of actual hospital applications. Aims at thorough understanding of concepts of total value analysis, objective function formation, and exception reporting. Students become familiar with operations research techniques of inventory modeling, queuing, computer simulation, PERT/CPM, mathematical programming, and quality control. Presentation emphasizes objectives, constraints, and required assumptions of each of these techniques as applied to specific hospital examples.
Description: Application of computer models for decision making in the health care sector. The students will be exposed to Monte Carlo Simulation, Process Simulation, Multiple Regression analysis, Discriminant Analysis, Project Management, Inventory Control, Integer Linear Programming, and Multi-Criteria Optimization. Use of computers and spreadsheet modeling will be emphasized throughout the class.