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AN INTELLIGENT MODEL FOR THE OPERATIVE BLOCK

NEW MODEL OF ORGANIZATION OF AN OPERATIVE BLOCK (BLOC-OP)

Status
UNKNOWN
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT05106621
Acronym
BLOC-OP
Enrollment
142
Registered
2021-11-04
Start date
2021-11-01
Completion date
2022-11-30
Last updated
2022-05-17

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

Conditions

Artificial Intelligence in Operating Room

Keywords

Perioperative Medicine, Artificial Intelligence, Machine Learning, Operating Room

Brief summary

Perioperative medicine is characterized by a very delicate path; it is composed, in fact, of a series of highly specialized clinical measures managed by various professionals (surgeons, anesthetists, intensivists, nurses, etc.), who work together to ensure the best quality of all phases of the path (preoperative , intra and postoperative). On the other hand, it is necessary to underline the huge resources needed to provide surgical services. Organizational optimization, based on specific analyzes, could lead to a more careful management of resources in this area, avoiding waste due to early closure of the operating room or unexpected extension of the same. In recent years, precisely to respond to the need to analyze large quantities of information, the use of artificial intelligence techniques, and in particular of machine learning, is becoming increasingly popular, a branch of artificial intelligence that aims, through the use of algorithms and statistical model, to infer new knowledge in a way automatic. Such technologies appear to possess excellent analytical skills both in the clinical and, above all, organizational fields. The data that are emerging in the literature on this issue, although still the first in this regard, seem to confirm this hypothesis.

Interventions

None listed

Sponsors

University of Parma
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

Inclusion criteria

all patients undergoing surgery who sign the informed consent form will be included.

Exclusion criteria

refusal of the patient to the study in question.

Design outcomes

Primary

MeasureTime frameDescription
Surgical Time Prediction1 yearPrediction of time spend in oprating room

Secondary

MeasureTime frameDescription
Outcome evaluation1 yearICU admission

Countries

Italy

Contacts

Primary ContactElena Bignami
elenagiovanna.bignami@unipr.it390521703567

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 9, 2026