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Leveraging Overtime Hours to Fit an Additional Arthroplasty Surgery Per Day: A Feasibility Study

dc.contributor.authorKhalaf, Georges
dc.contributor.supervisorFallavollita, Pascal
dc.date.accessioned2023-06-30T19:46:55Z
dc.date.available2023-06-30T19:46:55Z
dc.date.issued2023-06-30en_US
dc.description.abstractThe COVID-19 pandemic resulted in the cancellation of many hip and knee replacements, creating a backlog of patients on top of an existing long waiting list. To reduce wait lists with no financial burden, we aim to evaluate the possibility of leveraging our previous efficiency-improving work to add an additional case to a typical 4-joint day with no extra cost. To do this, 761 total operation days were analyzed from 2012 to 2019, capturing variables such as case number, success (completion of 4 cases before 3:45pm), and patient out of room time. Linear regression was used on 301 successful days to predict 5th cases, while overtime hours saved were calculated from the remaining unsuccessful days. Different cost distributions were then analyzed for a 77% 4-joint day success rate (our baseline), and a 100% 4-joint day success rate. Our predictions show that increasing performance to a 77% success rate can lead to approximately 35 extra cases per year at our institution, while a 100% success rate can produce 56 extra cases per year. Overall, this shows the extent of resources wasted by overtime costs, and the potential for their use in reducing wait times. Future work can explore optimal staffing procedures to account for these extra cases.en_US
dc.identifier.urihttp://hdl.handle.net/10393/45110
dc.identifier.urihttp://dx.doi.org/10.20381/ruor-29316
dc.language.isoenen_US
dc.publisherUniversité d'Ottawa / University of Ottawaen_US
dc.rightsCC0 1.0 Universal*
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.subjectArthroplastyen_US
dc.subjectMachine Learningen_US
dc.subjectOR Efficiencyen_US
dc.subjectLinear Regressionen_US
dc.subjectHip and Knee Replacementsen_US
dc.titleLeveraging Overtime Hours to Fit an Additional Arthroplasty Surgery Per Day: A Feasibility Studyen_US
dc.typeThesisen_US
thesis.degree.disciplineGénie / Engineeringen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMAen_US
uottawa.departmentGénie mécanique / Mechanical Engineeringen_US

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