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dc.contributor.advisorBickel, J. Eric
dc.creatorSahoo, Swarup
dc.date.accessioned2018-08-09T20:36:04Z
dc.date.available2018-08-09T20:36:04Z
dc.date.created2018-05
dc.date.issued2018-06-19
dc.date.submittedMay 2018
dc.identifierdoi:10.15781/T2MG7GD66
dc.identifier.urihttp://hdl.handle.net/2152/67516
dc.description.abstractHealthcare costs can be astronomical when it comes to cancer treatment. Given the steep costs of treatment, it is expected for a patient to learn about the cost estimates before starting the treatment process. Having this information would be immensely helpful for the patient to avoid debt and the debt related stress at the end of the treatment cycle. This would also help MD Anderson Cancer Center to improve patient experience and payer performance. Therefore, it is crucial for the Cancer Center to have a robust analytical tool to predict the stages and costs of treatment for a given set of conditions and patient attributes. By analyzing the various factors driving the costs and the attributes affecting the condition of the patient, the treatment costs can be predicted more accurately than the state of the art. This paper analyzes the various factors affecting the costs by measuring the variance of expenses at different stages of treatment. Further, the condition of the patient was modelled as a stochastic process to have an in-depth knowledge of the likelihood of the patient’s condition getting better or worse given the stage at which the patient entered the system.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.subjectHealthcare
dc.subjectCancer
dc.subjectRevenue cycle
dc.subjectCancer treatment costs
dc.subjectCancer treatment cost estimates
dc.subjectCancer treatment cost factors
dc.subjectCancer treatment cost prediction
dc.subjectCancer treatment cost analysis
dc.subjectMD Anderson Cancer Center
dc.titleLife cycle cost analysis for cancer patients at the University of Texas MD Anderson Cancer Center
dc.typeThesis
dc.date.updated2018-08-09T20:36:04Z
dc.description.departmentOperations Research and Industrial Engineering
thesis.degree.departmentOperations Research and Industrial Engineering
thesis.degree.disciplineOperations Research & Industrial Engineering
thesis.degree.grantorThe University of Texas at Austin
thesis.degree.levelMasters
thesis.degree.nameMaster of Science in Engineering
dc.creator.orcid0000-0001-7281-1935
dc.type.materialtext


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