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About the courseCourse Title and NumberHAP 730 Decision Analysis in Healthcare (3:3:0) Course DescriptionStudents integrate scientific evidence, patients' preferences, and experts' opinions to analyze managerial decisions and identify optimal alternatives. Included are applications to analysis of practice patterns, benchmarking, probabilistic risk assessment, cost analysis, conflict analysis and measurement of severity of illness. Decision analytical tools such as Multi-Attribute Value Models, Bayesian Probability Networks, and Decision Trees are covered. Course ObjectivesWe live in a fast changing society where analysis is of paramount importance. Our hope is to help students solve pressing problems in our organizations and society. Good decisions based on a systematic consideration of all relevant factors and stakeholder opinions and values lead to good outcomes, both for those involved in the decision making process, and for the customers who are directly impacted by the consequences and effects of such decisions. At the conclusion of the course participants should be able to:
Students are expected to use subjective opinions of experts to construct analytical models that could help managers make important organizational decisions.
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Distribution of the grade |
Letter grades will correspond to the
following numerical grades: |
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You are asked to complete 5 bi-weekly projects. In each project you are asked to interview an expert or a decision maker and construct a model of them. These interviews are time consuming and you should arrange for them as soon as possible. In completing these tasks please note the following:
Week Starting on Date |
Reading |
Bi-weekly
project Due 2 weeks after listed date |
Assignments Due within 5 days of listed date |
Session 1 |
About the
course
Review Excel if you do not know how to use this tool |
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Read
Introduction to Decision Analysis
pages 1 through 20. Read Rapid Policy Analysis pages 319 to 329. |
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Session 2 | Read Modeling Preferences pages 21 through 64 |
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Session 3
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Teach One: Discussion of Student Project for Modeling Preferences |
Comment on work of other students using the rubric provided. |
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Session 4 |
Read Measuring Uncertainty pages 67 through 90. |
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Session 5 |
Read Modeling Uncertainty pages 91 through 116.
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Session 6 | Teach One: Discussion of Student Project for Modeling Uncertainty |
Comment on work of other students using the rubric provided. |
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Session 7 |
Read Decision Trees pages 117 through 148. |
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Session 8 |
Read Cost Effectiveness of Clinics pages 187 through 214. |
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Session 9 | Teach One: Discussion of Student Project for Decision Trees |
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Session 10 |
Read Root Cause Analysis pages 169 through 186 |
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Session 11 | Teach One: Discussion of Student Project for Root Cause Analysis |
Comment on work of other students using the rubric provided. |
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Session 12 |
Read Benchmarking Clinicians pages 299 through 319 |
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Session 13 | Teach One: Discussion of Student Project for Benchmarking |
Comment on work of other students using the rubric provided. |
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Exit
Interview Take final exam if invited by the instructor to do so |
Catch up with your work. Meet with the instructor and review your progress in projects to date. Show that you have corrected assignments based on input from peers and the instructor. Present a portfolio of all of your work. |
If you are enrolled in this course, you may receive communications from the course faculty. In order to make sure that you receive the information on time, please provide us with your email address.
: “To promote a stronger sense of mutual responsibility, respect, trust, and fairness among all members of the George Mason University community and with the desire for greater academic and personal achievement, we, the student members of the university community, have set forth this honor code: Student members of the George Mason University community pledge not to cheat, plagiarize, steal, or lie in matters related to academic work” (George Mason University Catalog, 2006-2007, p. 31).
If you are a student with a disability and you need academic accommodations, please see Debbie Wyne and contact the Disability Resource Center at 703 993-2474. All academic accommodations must be arranged through the Disability Resource Center.
George Mason University is committed to complying with the Rehabilitation Act of 1973 and the Americans with Disabilities Act of 1990 by providing reasonable accommodations for disabled applicants for admission, students, applicants for employment, employees, and visitors. Applicants for admission and students requiring specific accommodations for a disability should contact the Disability Resource Center at 703-993-2474, or the Equity Office at 703-993-8730. Applicants for employment and employees should contact Human Resources at 703-993-2600 or the Equity Office. Students and employees are responsible for providing appropriate documentation and requesting reasonable accommodation in a timely manner (George Mason University Catalog, 2006-2007, p. 55).
See more information about course instructors. For more information contact Farrokh Alemi, Ph.D. This page is part of the course on Decision Analysis, the section on "About the course." It was first created in 2004. It was last edited on 10/21/2011 © Copyright protected.