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dc.contributor.advisorRetsef Levi and David Simchi-Levi.en_US
dc.contributor.authorUgarph, Elizabethen_US
dc.contributor.otherLeaders for Global Operations Program.en_US
dc.date.accessioned2017-09-15T15:38:30Z
dc.date.available2017-09-15T15:38:30Z
dc.date.copyright2017en_US
dc.date.issued2017en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/111536
dc.descriptionThesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, 2017.en_US
dc.descriptionThesis: S.M. in Engineering Systems, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, in conjunction with the Leaders for Global Operations Program at MIT, 2017.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 119-120).en_US
dc.description.abstractIn 2015, there were approximately 17,000 General Medicine admissions in the Department of Medicine (DOM) at MGH. General Medicine patients regularly experience significant non-clinical delays caused by bed and care team unavailability, with approximately 25% of patients waiting ten hours or more for a bed. Delays in bed and care team assignments result in decreased patient satisfaction, congestion in the ED and ICUs, and increased overall hospital length-of-stay. This project studies General Medicine patient flow, develops and evaluates interventions to improve this flow, and provides recommendations to hospital leadership. To this end, we construct a discrete-event simulation based on historical data. Intervention effectiveness is measured primarily based on patient-wait-for-bed, the time from when patient is medically ready for an inpatient bed until the bed is assigned to and ready for the patient. We find that the simulation model accurately represents the wait times of General Medicine patients. We propose a new algorithm, which when implemented could reduce overall average patient-wait-for-bed by 9% from 7.36 to 6.67 hours. Implementation of additional capacity and reorganization of the physician care teams (known as the DOM redesign) is shown to result in a further 31% reduction in average wait time (from 6.67 to 4.59 hours). Other interventions tested such as early assignment of patients to care teams based on predicted discharges, and increased flexibility of care teams to cover different units are shown to have modest effects on overall patient-wait-for-bed.en_US
dc.description.statementofresponsibilityby Elizabeth Ugarph.en_US
dc.format.extent120 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.subjectSloan School of Management.en_US
dc.subjectInstitute for Data, Systems, and Society.en_US
dc.subjectEngineering Systems Division.en_US
dc.subjectLeaders for Global Operations Program.en_US
dc.titlePatient flow optimization in the Department of Medicine at MGHen_US
dc.title.alternativePatient flow optimization in the DOM at Massachusetts General Hospitalen_US
dc.typeThesisen_US
dc.description.degreeM.B.A.en_US
dc.description.degreeS.M. in Engineering Systemsen_US
dc.contributor.departmentSloan School of Management.en_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.contributor.departmentLeaders for Global Operations Program.en_US
dc.identifier.oclc1003324821en_US


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