Patient flow optimization in the Department of Medicine at MGH
Patient flow optimization in the DOM at Massachusetts General Hospital
Leaders for Global Operations Program.
Retsef Levi and David Simchi-Levi.
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In 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.
Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, 2017.Thesis: 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.Cataloged from PDF version of thesis.Includes bibliographical references (pages 119-120).
DepartmentSloan School of Management.; Massachusetts Institute of Technology. Institute for Data, Systems, and Society.; Massachusetts Institute of Technology. Engineering Systems Division.; Leaders for Global Operations Program.
Massachusetts Institute of Technology
Sloan School of Management., Institute for Data, Systems, and Society., Engineering Systems Division., Leaders for Global Operations Program.