Data analysis and simulation approach to capacity planning
Name
994684008-MIT.pdf
Description
Full printable version
Size
11.4 MB
Format
Adobe PDF
Checksum (MD5)
4e5dba68b45da1b0ce28d7e21e393ff7
Author(s)
Chafac, Melvis Ngemasong Ngimndoh
Advisor(s)
John Carroll.
Date Issued
2015
Publisher
Massachusetts Institute of Technology
Abstract
In 2012, President Obama signed an Executive Order to improve access to mental health service for active duty members and for veterans. Two years later, in 2014, the President outlined 19 new executive actions to improve the lives of service members with a focus on improving access to mental health care. These actions placed a priority on improving the capacity to provide mental health care. This thesis examines ways of improving the capacity of the mental health system with a focus on system redesign. I review capacity planning, provide a literature review of simulation methods and present a simulation, and data analysis of Site Alpha, a U.S. Army Installation. I also use causal loop diagrams to explore other feasible scenarios that affect care capacity. The key take-away from this work is that system inefficiencies should be dealt with before more resources can be effectively added and used in the system. Another pertinent finding is that the distribution of the providers in the system should be improved. The system also contains high utilizer patients who must be considered when planning for care. The mental health system is extremely complex and risks becoming even more complex. However, by adopting a holistic, systems approach to capacity planning the complexity can be managed.
Description
Thesis: S.M. in Engineering Systems, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2015.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 72-97).
Subjects
Institute for Data, Systems, and Society.
Engineering Systems Division.
MIT Department
Massachusetts Institute of Technology. Engineering Systems Division
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
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