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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
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT03471377
Enrollment
683
Registered
2018-03-20
Start date
2018-03-05
Completion date
2022-03-15
Last updated
2022-03-17

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Operative Time

Keywords

Planned Surgical Case, Predictive Modeling, 18-115

Brief 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.

Interventions

OTHERstandard 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.

OTHERassigned 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.

Sponsors

Memorial Sloan Kettering Cancer Center
Lead SponsorOTHER

Study design

Observational model
CASE_CONTROL
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Healthy volunteers
Yes

Inclusion criteria

* A surgeon or OR staff member in the Department of Surgery Gynecology and Colorectal service

Exclusion criteria

* Any new surgeon that starts their practice during the study * Surgery will take place at a location other than the Main hospital or Josie Robertson Surgical Center * Cases where input data was not available prior to the prediction generation including late add-on cases such as urgent and emergent cases that are placed on the schedule less than 24 hours before the surgery

Design outcomes

Primary

MeasureTime frameDescription
duration it takes surgeons to complete their respective surgical cases1 yearAll Gynecology (GYN) and Colorectal (CRS) Surgeons at MSKCC will be included. To test the hypothesis that the developed surgical case duration prediction model compared to the current process of estimating surgical case durations, will show improved prediction accuracy, measured by mean absolute error.

Countries

United States

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 16, 2026