NCT03471377

Improving Planned Surgical Case Duration Accuracy by Leveraging the EHR and Predictive Modeling

Improving Planned Surgical Case Duration Accuracy by Leveraging the EHR and Predictive Modeling - A Randomized Control Trial

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 683 (actual)
• Sponsor: Memorial Sloan Kettering Cancer Center · Academic / Other
• Sex: All
• Age: —
• Healthy volunteers: Accepted

Summary

The investigators are studying the duration it takes surgeons to complete their respective surgical cases. The hospital hopes to improve the overall operating room scheduling accuracy from this project.

Conditions

• Operative Time

Interventions

Type	Name	Description
OTHER	standard scheduling process	Scheduling office assigns start time and room for case and places case on schedule. At this point a default case duration is evaluated by the scheduling office, to see if the value is considered excessively short or excessively long. Depending on the assessment, the scheduling office will either keep the default value, use the value that the surgeon placed in the notes (if available), or the scheduling office provides their own estimation.
OTHER	assigned a planned case duration value from predictive model	Predictive model calculates new duration for case at 3AM the day before surgery, and the predictions are made available on a SecureShare-site. Model predictions are then read by scheduling manager sometime between 7am-10am from the SecureShare site, and the scheduling manager will in EPIC/OpTime, overwrite the current estimate with the new duration value that was generated by the predictive model.

Timeline

• Start date: 2018-03-05
• Primary completion: 2022-03-15
• Completion: 2022-03-15
• First posted: 2018-03-20
• Last updated: 2022-03-17

Locations

1 site across 1 country: United States