Accepted for/Published in: JMIR Perioperative Medicine
Date Submitted: Dec 16, 2022
Date Accepted: Dec 22, 2023
“Comparing Anesthesia and Surgery Controlled Time for Primary Total Knee and Hip Arthroplasty Between an Academic Medical Center and a Community Hospital: A Retrospective Cohort Study”
ABSTRACT
Background:
Establishing benchmarks that more accurately predict surgical duration could help to decrease healthcare cost, maximize efficiency in the operating room (OR) and improve patient experience. We compared the anesthesia-controlled time (ACT) and surgery-controlled time (SCT) of primary total knee and total hip arthroplasties between an academic center and a community hospital for two orthopedic surgeons.
Objective:
To validate and compare benchmarking times for ACTs and SCTs in a single patient population in both an academic center and community hospital
Methods:
This retrospective two-center observational cohort study was conducted at the University of Colorado Hospital (UCH) and UCHealth Broomfield Hospital (BFH). Cases with CPT codes for THA and TKA were assessed. Multivariable linear regression was used to assess the association of ACT and SCT with procedure location, type of anesthesia and ASA classification.
Results:
Two surgeons performed 1,256 cases at UCH and BFH. After controlling for surgeon the ACT time was greater at UCH for both THA by 3.77 minutes and TKA by 3.58 minutes (p<0.001). SCT time was greater at UCH for THA by 11.14 minutes and for TKA by 14.04 minutes (p<0.001). ASA III/IV Classification increased ACT time by 3.76 minutes for THA (p<0.001) and increased SCT time by 6.33 minutes for TKA after adjusting for surgeon and location (p=0.008). No statistically significant difference was noted between neuraxial and general anesthesia.
Conclusions:
We observed lower ACT/SCT at the community hospital for both TKA and THA as compared with UCH after controlling for surgeon and ASA classification. Establishing more accurate benchmarks to improve the prediction of surgical duration for THA and TKA in different perioperative environments can increase reliability of surgical duration predictions and optimize scheduling.
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