Improving the efficiency of the operating room environment with an optimization and machine learning model.
The operating room is a major cost and revenue center for most hospitals. Thus, more effective operating room management and scheduling can provide significant benefits. In many hospitals, the post-anesthesia care unit (PACU), where patients recover after their surgical procedures, is a bottleneck....
| Publicado en: | Health Care Management Science Vol. 22; no. 4; pp. 756 - 768 |
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| Autores principales: | , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Dec2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=139568161&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 139568161 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13869620 BSE jtl: Health Care Management Science issn: 13869620 maglogo: N pubinfo: dt: Dec2019 vid: 22 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 139568161 139568161 144184873 NLM30387040 10.1007/s10729-018-9457-3 NLM30387040 139568161 ppf: 756 ppct: 12 formats: tig: atl: Improving the efficiency of the operating room environment with an optimization and machine learning model. aug: au: Fairley, Michael Scheinker, David Brandeau, Margaret L. affil: Department of Management Science and Engineering, Stanford University, 94305, Stanford, CA, USA sug: subj: Operating Rooms Administration Personnel Staffing and Scheduling Administration Organizational Efficiency Post Anesthesia Care Units Administration Program Evaluation Hospitals, Pediatric Operating Rooms Economics Post Anesthesia Care Units Economics California Computer Simulation ab: The operating room is a major cost and revenue center for most hospitals. Thus, more effective operating room management and scheduling can provide significant benefits. In many hospitals, the post-anesthesia care unit (PACU), where patients recover after their surgical procedures, is a bottleneck. If the PACU reaches capacity, patients must wait in the operating room until the PACU has available space, leading to delays and possible cancellations for subsequent operating room procedures. We develop a generalizable optimization and machine learning approach to sequence operating room procedures to minimize delays caused by PACU unavailability. Specifically, we use machine learning to estimate the required PACU time for each type of surgical procedure, we develop and solve two integer programming models to schedule procedures in the operating rooms to minimize maximum PACU occupancy, and we use discrete event simulation to compare our optimized schedule to the existing schedule. Using data from Lucile Packard Children's Hospital Stanford, we show that the scheduling system can significantly reduce operating room delays caused by PACU congestion while still keeping operating room utilization high: simulation of the second half of 2016 shows that our model could have reduced total PACU holds by 76% without decreasing operating room utilization. We are currently working on implementing the scheduling system at the hospital. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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