Show simple item record

dc.contributor.advisorJohn Carroll.en_US
dc.contributor.authorChafac, Melvis Ngemasong Ngimndohen_US
dc.contributor.otherMassachusetts Institute of Technology. Engineering Systems Division.en_US
dc.date.accessioned2017-08-01T13:14:54Z
dc.date.available2017-08-01T13:14:54Z
dc.date.copyright2015en_US
dc.date.issued2015en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/110893
dc.descriptionThesis: S.M. in Engineering Systems, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2015.en_US
dc.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 72-97).en_US
dc.description.abstractIn 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.en_US
dc.description.statementofresponsibilityby Melvis Ngemasong Ngimndoh Chafac.en_US
dc.format.extentvi, 113 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectInstitute for Data, Systems, and Society.en_US
dc.subjectEngineering Systems Division.en_US
dc.titleData analysis and simulation approach to capacity planningen_US
dc.typeThesisen_US
dc.description.degreeS.M. in Engineering Systemsen_US
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Data, Systems, and Society.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Division.en_US
dc.identifier.oclc994684008en_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record