Obstetric operating room staffing and operating efficiency using queueing theory.
Anesthesia
Efficiency
Obstetric
Operating room
Queueing
Staffing
Journal
BMC health services research
ISSN: 1472-6963
Titre abrégé: BMC Health Serv Res
Pays: England
ID NLM: 101088677
Informations de publication
Date de publication:
25 Oct 2023
25 Oct 2023
Historique:
received:
15
01
2023
accepted:
13
10
2023
medline:
27
10
2023
pubmed:
25
10
2023
entrez:
24
10
2023
Statut:
epublish
Résumé
Strategies to achieve efficiency in non-operating room locations have been described, but emergencies and competing priorities in a birth unit can make setting optimal staffing and operation benchmarks challenging. This study used Queuing Theory Analysis (QTA) to identify optimal birth center operating room (OR) and staffing resources using real-world data. Data from a Level 4 Maternity Center (9,626 births/year, cesarean delivery (CD) rate 32%) were abstracted for all labor and delivery operating room activity from July 2019-June 2020. QTA has two variables: Mean Arrival Rate, λ and Mean Service Rate µ. QTA formulas computed probabilities: P There were 4,017 total activities in the operating room and 3,092 CD in the study period. Arrival rate λ was 0.45 (patients per hour) at peak hours 07:00-19:00 while λ was 0.34 over all 24 h. The service rate per OR team (µ) was 0.87 (patients per hour) regardless of peak or overall hours. The number of server teams (s) dedicated to OR activity was varied between two and five. Over 24 h, the probability of no patients in the system was P QTA is a useful tool to inform birth center OR efficiency while upholding assumed safety standards and factoring peaks and troughs of daily activity. Our findings suggest QTA is feasible to guide staffing for maternity centers of all volumes through varying model parameters. QTA can inform individual hospital-level decisions in setting staffing and space requirements to achieve safe and efficient maternity perioperative care.
Identifiants
pubmed: 37875897
doi: 10.1186/s12913-023-10143-0
pii: 10.1186/s12913-023-10143-0
pmc: PMC10599054
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1147Subventions
Organisme : University of Pittsburgh
ID : Department of Anesthesiology & Perioperative Medicine
Informations de copyright
© 2023. BioMed Central Ltd., part of Springer Nature.
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