Improving access through stochastic modeling in Veterans Affairs Mental Health Services

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.

Department dc:contributor.department

Massachusetts Institute of Technology. Engineering Systems Division

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2016

Author dc:creator

• Collin, Anne (Anne Claire)

Advisor dc:contributor.advisor

• Richard C. Larson.

• Institute for Data, Systems, and Society.
• Engineering Systems Division.
• Technology and Policy Program.

Statement dc:rights

• 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.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/104817

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/104817