OR black box and surgical control tower: Recording and streaming data and analytics to improve surgical care.

OR black box Surgical Data Science Surgical control tower Surgical safety

Journal

Journal of visceral surgery
ISSN: 1878-7886
Titre abrégé: J Visc Surg
Pays: France
ID NLM: 101532664

Informations de publication

Date de publication:
Jun 2021
Historique:
pubmed: 14 3 2021
medline: 29 10 2021
entrez: 13 3 2021
Statut: ppublish

Résumé

Effective and safe surgery results from a complex sociotechnical process prone to human error. Acquiring large amount of data on surgical care and modelling the process of surgery with artificial intelligence's computational methods could shed lights on system strengths and limitations and enable computer-based smart assistance. With this vision in mind, surgeons and computer scientists have joined forces in a novel discipline called Surgical Data Science. In this regard, operating room (OR) black boxes and surgical control towers are being developed to systematically capture comprehensive data on surgical procedures and to oversee and assist during operating rooms activities, respectively. Most of the early Surgical Data Science works have focused on understanding risks and resilience factors affecting surgical safety, the context and workflow of procedures, and team behaviors. These pioneering efforts in sensing and analyzing surgical activities, together with the advent of precise robotic actuators, bring surgery on the verge of a fourth revolution characterized by smart assistance in perceptual, cognitive and physical tasks. Barriers to implement this vision exist, but the surgical-technical partnerships set by ambitious efforts such as the OR black box and the surgical control tower are working to overcome these roadblocks and translate the vision and early works described in the manuscript into value for patients, surgeons and health systems.

Identifiants

pubmed: 33712411
pii: S1878-7886(21)00016-3
doi: 10.1016/j.jviscsurg.2021.01.004
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

S18-S25

Informations de copyright

Copyright © 2021 Elsevier Masson SAS. All rights reserved.

Auteurs

P Mascagni (P)

ICube, University of Strasbourg, CNRS, IHU Strasbourg, Strasbourg, France; Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.

N Padoy (N)

ICube, University of Strasbourg, CNRS, IHU Strasbourg, Strasbourg, France. Electronic address: npadoy@unistra.fr.

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Classifications MeSH