Flow disruptions in robotic-assisted abdominal sacrocolpopexy: does robotic surgery introduce unforeseen challenges for gynecologic surgeons?


Journal

International urogynecology journal
ISSN: 1433-3023
Titre abrégé: Int Urogynecol J
Pays: England
ID NLM: 101567041

Informations de publication

Date de publication:
12 2019
Historique:
received: 07 12 2018
accepted: 13 03 2019
pubmed: 2 5 2019
medline: 21 5 2020
entrez: 2 5 2019
Statut: ppublish

Résumé

The purpose of this study was to apply a human factors research approach to identify flow disruptions, deviations in the optimal course of care, in robotic abdominal sacrocolpopexy procedures with the ultimate goal of developing system interventions to improve the safety and efficiency of robotic surgery. Twenty-four robotic abdominal sacrocolpopexy procedures were observed for flow disruptions. Surgeries were divided into four phases: (1) patient arrival and induction of anesthesia; (2) port placement and robot docking; (3) console time; (4) undocking of robot, incision closure, and patient exiting the OR. Flow disruptions were observed at a rate of 10.9 ± 5.1 per hour. The most frequently observed flow disruptions involved training issues (2.8 ± 2.4 flow disruptions per hour), equipment (2.2 ± 1.6 flow disruptions per hour), and poor coordination (2.0 ± 1.3 flow disruptions per hour). The rate of flow disruptions was highest in phase 2 (19.2 ± 14.4 flow disruptions per hour). Cases with more experienced surgeons involved shorter console times by 1.5 h (95% CI: 0.1, 3.0, p = 0.033) and 1.8 fewer (95% CI: 1.2, 2.6, p = 0.001) flow disruptions per hour. Surgeries were 1 h shorter on average (95% CI: 0.1, 1.9, p = 0.034) in cases in which the patient was > 65 years old. Da Vinci S console times were 0.8 h longer (95% CI: 0.01, 1.5, p = 0.047) than Si. Flow disruptions in robotic abdominal sacrocolpopexy surgery occur about every 6 min. Flow disruption rates are highest during the most complex portions of the surgery. More experienced surgeons have lower flow disruption rates and operate more quickly.

Identifiants

pubmed: 31041500
doi: 10.1007/s00192-019-03929-6
pii: 10.1007/s00192-019-03929-6
pmc: PMC6821560
mid: NIHMS1027883
doi:

Types de publication

Journal Article Observational Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

2177-2182

Subventions

Organisme : NIBIB NIH HHS
ID : R03 EB017447
Pays : United States
Organisme : NIA NIH HHS
ID : T35 AG026736
Pays : United States
Organisme : UCLA Medical Student Training in Aging Research Program-the National Institute on Aging
ID : T35AG026736
Pays : International
Organisme : National Institute of Biomedical Imaging & Biomedical Engineering Award
ID : R03EB017447
Pays : International

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Auteurs

Colby P Souders (CP)

Cedars-Sinai Medical Center, Los Angeles, CA, USA.

Ken Catchpole (K)

Medical University of South Carolina, Charleston, SC, USA.

Alex Hannemann (A)

Cedars-Sinai Medical Center, Los Angeles, CA, USA.

Ronit Lyon (R)

Cedars-Sinai Medical Center, Los Angeles, CA, USA.

Karyn S Eilber (KS)

Cedars-Sinai Medical Center, Los Angeles, CA, USA.

Catherine Bresee (C)

Cedars-Sinai Medical Center, Los Angeles, CA, USA.

Tara Cohen (T)

Cedars-Sinai Medical Center, Los Angeles, CA, USA.

Matthias Weigl (M)

Ludwig-Maximilians-University of Munich, Munich, Germany.

Jennifer T Anger (JT)

Cedars-Sinai Medical Center, Los Angeles, CA, USA. Jennifer.Anger@cshs.org.
, Beverly Hills, USA. Jennifer.Anger@cshs.org.

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Classifications MeSH