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Richard C. Larson. Collin, Anne (Anne Claire) Technology and Policy Program. Massachusetts Institute of Technology. Engineering Systems Division Massachusetts Institute of Technology. Institute for Data, Systems, and Society Technology and Policy Program 2016-10-14T14:41:47Z 2016-10-14T14:41:47Z 2016 2016 http://hdl.handle.net/1721.1/104817 959234012 Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, Technology and Policy Program, 2016. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student-submitted PDF version of thesis. Includes bibliographical references (pages 85-88). In this thesis, I created a tool for a particular VA clinic to simulate the delays veterans face in a network of mental health programs. Based on queueing theory, including blocking and reneging, different operations management strategies are compared using this discrete event simulation tool. To simulate wait times, users input arrival rates, service times, patience, probabilities of relapses and probabilities to go from one program to another. We determine that blocking is one of the main drivers of the delays. This model is not only useful for direct decision making, such as increasing capacity in one of the programs, but also to enable systems thinking in the VA. Indeed, if more quantitative methods were used at different levels of the organization, managers could take more informed decisions faster. This also prompts for rigorous data collection, which is something the VA needs, especially wait times for mental health clinics. by Anne Collin. S.M. in Technology and Policy 88 pages eng Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 Institute for Data, Systems, and Society. Engineering Systems Division. Technology and Policy Program. Improving access through stochastic modeling in Veterans Affairs Mental Health Services Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="27d661d2-96d2-461a-a4bd-74e3325f7b7a"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Improving access through stochastic modeling in Veterans Affairs Mental Health Services</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2016</PublicationDate> <Authors> <Author> <DisplayName>Collin, Anne (Anne Claire)</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Institute for Data, Systems, and Society.</Keyword> <Keyword>Engineering Systems Division.</Keyword> <Keyword>Technology and Policy Program.</Keyword> <Abstract>In this thesis, I created a tool for a particular VA clinic to simulate the delays veterans face in a network of mental health programs. Based on queueing theory, including blocking and reneging, different operations management strategies are compared using this discrete event simulation tool. To simulate wait times, users input arrival rates, service times, patience, probabilities of relapses and probabilities to go from one program to another. We determine that blocking is one of the main drivers of the delays. This model is not only useful for direct decision making, such as increasing capacity in one of the programs, but also to enable systems thinking in the VA. Indeed, if more quantitative methods were used at different levels of the organization, managers could take more informed decisions faster. This also prompts for rigorous data collection, which is something the VA needs, especially wait times for mental health clinics.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>