Efficiency of a Neurosurgical Operating Room According to Nursing Characteristics in a University Hospital: From Operating Times to a Cost-Benefit Analysis.


Journal

Operative neurosurgery (Hagerstown, Md.)
ISSN: 2332-4260
Titre abrégé: Oper Neurosurg (Hagerstown)
Pays: United States
ID NLM: 101635417

Informations de publication

Date de publication:
01 Oct 2024
Historique:
received: 06 02 2024
accepted: 06 02 2024
medline: 17 9 2024
pubmed: 17 9 2024
entrez: 16 9 2024
Statut: ppublish

Résumé

The primary objective of this study was to evaluate the influence of operating room nurse (ORN) characteristics on the duration of elective neurosurgical procedures in adults. In addition, we conducted a cost-benefit analysis of various strategies for organizing the workflow of ORNs. We collected and analyzed operating times for adult elective neurosurgical procedures, categorizing them by surgeon, procedure complexity (dichotomized as technologically complex and simple), and ORN characteristics (dichotomized as ORN dedicated to neurosurgery [dORN] and ORN not dedicated to neurosurgery [ndORN]). The monetary valuation of operating times is based on the unitary cost per minute of the operating room, including opportunity costs of ORN, as well as their training costs and salaries. Cost-benefit analysis adopted the hospital perspective. Analysis of operating times reveals an approximately 20-minute difference for complex procedures when performed with ndORN. However, there is no significant difference in operating times for simple procedures, whether they are conducted by dORN or ndORN. The additional annual cost incurred by complex procedures performed with ndORN is estimated at CHF 68 144.4 for the Geneva University Hospitals. Complex neurosurgical procedures exhibit shorter durations when performed by dORNs. We explore several hypotheses to explain this difference. By adapting available human resources and optimizing workflow organization, hospitals can potentially achieve a net benefit.

Sections du résumé

BACKGROUND AND OBJECTIVES OBJECTIVE
The primary objective of this study was to evaluate the influence of operating room nurse (ORN) characteristics on the duration of elective neurosurgical procedures in adults. In addition, we conducted a cost-benefit analysis of various strategies for organizing the workflow of ORNs.
METHODS METHODS
We collected and analyzed operating times for adult elective neurosurgical procedures, categorizing them by surgeon, procedure complexity (dichotomized as technologically complex and simple), and ORN characteristics (dichotomized as ORN dedicated to neurosurgery [dORN] and ORN not dedicated to neurosurgery [ndORN]). The monetary valuation of operating times is based on the unitary cost per minute of the operating room, including opportunity costs of ORN, as well as their training costs and salaries. Cost-benefit analysis adopted the hospital perspective.
RESULTS RESULTS
Analysis of operating times reveals an approximately 20-minute difference for complex procedures when performed with ndORN. However, there is no significant difference in operating times for simple procedures, whether they are conducted by dORN or ndORN. The additional annual cost incurred by complex procedures performed with ndORN is estimated at CHF 68 144.4 for the Geneva University Hospitals.
CONCLUSION CONCLUSIONS
Complex neurosurgical procedures exhibit shorter durations when performed by dORNs. We explore several hypotheses to explain this difference. By adapting available human resources and optimizing workflow organization, hospitals can potentially achieve a net benefit.

Identifiants

pubmed: 39283097
doi: 10.1227/ons.0000000000001145
pii: 01787389-202410000-00001
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

407-414

Informations de copyright

Copyright © Congress of Neurological Surgeons 2024. All rights reserved.

Références

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Auteurs

Andrea Bartoli (A)

Department of Clinical Neurosciences, Division of Neurosurgery, Geneva University Hospitals, Geneva, Switzerland.

Christophe Pinget (C)

Health Technology Assessment Unit, University Hospital of Lausanne, Lausanne, Switzerland.

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Classifications MeSH