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Operational strategies to manage non-elective orthopaedic surgical flows: a simulation modelling study.

Operational strategies to manage non-elective orthopaedic surgical flows: a simulation modelling study.
Author Information (click to view)

Persson M, Hvitfeldt-Forsberg H, Unbeck M, Sköldenberg OG, Stark A, Kelly-Pettersson P, Mazzocato P,


Persson M, Hvitfeldt-Forsberg H, Unbeck M, Sköldenberg OG, Stark A, Kelly-Pettersson P, Mazzocato P, (click to view)

Persson M, Hvitfeldt-Forsberg H, Unbeck M, Sköldenberg OG, Stark A, Kelly-Pettersson P, Mazzocato P,

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BMJ open 2017 04 077(4) e013303 doi 10.1136/bmjopen-2016-013303
Abstract
OBJECTIVES
To explore the value of simulation modelling in evaluating the effects of strategies to plan and schedule operating room (OR) resources aimed at reducing time to surgery for non-elective orthopaedic inpatients at a Swedish hospital.

METHODS
We applied discrete-event simulation modelling. The model was populated with real world data from a university hospital with a strong focus on reducing waiting time to surgery for patients with hip fracture. The system modelled concerned two patient groups that share the same OR resources: hip-fracture and other non-elective orthopaedic patients in need of surgical treatment. We simulated three scenarios based on the literature and interaction with staff and managers: (1) baseline; (2) reduced turnover time between surgeries by 20 min and (3) one extra OR during the day, Monday to Friday. The outcome variables were waiting time to surgery and the percentage of patients who waited longer than 24 hours for surgery.

RESULTS
The mean waiting time in hours was significantly reduced from 16.2 hours in scenario 1 (baseline) to 13.3 hours in scenario 2 and 13.6 hours in scenario 3 for hip-fracture surgery and from 26.0 hours in baseline to 18.9 hours in scenario 2 and 18.5 hours in scenario 3 for other non-elective patients. The percentage of patients who were treated within 24 hours significantly increased from 86.4% (baseline) to 96.1% (scenario 2) and 95.1% (scenario 3) for hip-fracture patients and from 60.2% (baseline) to 79.8% (scenario 2) and 79.8% (scenario 3) for patients with other non-elective patients.

CONCLUSIONS
Healthcare managers who strive to improve the timelines of non-elective orthopaedic surgeries may benefit from using simulation modelling to analyse different strategies to support their decisions. In this specific case, the simulation results showed that the reduction of surgery turnover times could yield the same results as an extra OR.

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