CompletedNot Applicable

Pilot Study for Postoperative Machine Learning

United States222 participantsStarted 2021-06-03

Plain-language summary

The objectives of the study are to determine the interpretability, workflow role, and effect on communications of showing report cards containing Machine Learning (ML)-based risk profiles based on pre- and intra-operative data to postoperative providers.

Who can participate

Age range18 Years

SexALL

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Inclusion criteria

✓. Within the TECTONICS contact arm (adults undergoing OR procedures)
✓. Operating room at BJH South campus (including all of "Pod 2", "Pod 3", "Pod 5") (excluding all procedure suites such as Interventional Radiology, Parkview Tower "Pod 1", Center for Advanced Medicine "Pod 4", Labor and Delivery suites)
✓. Surgeon is a member of the Acute and Critical Care Surgery division or the postoperative bed is 16300 observation unit.
✓. Planned non-ICU disposition ("floor" and "observation unit" collectively "ward" patients).

Exclusion criteria

✕. Not enrolled in TECTONICS Study
✕. Randomized to the observation arm in TECTONICS study
✕. Planned ICU admission
✕. Patients are only included once; if previously included a subsequent surgery is not eligible

What they're measuring

Overall Handoff Effectiveness

Timeframe: 8 hours postop

Trial details

NCT IDNCT04877535

SponsorWashington University School of Medicine

Sponsor typeOTHER

Study typeINTERVENTIONAL

Primary completion2023-05-11

Results submitted2025-02-24

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