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Bone & Joint Open
Vol. 5, Issue 8 | Pages 715 - 720
23 Aug 2024
Shen TS Cheng R Chiu Y McLawhorn AS Figgie MP Westrich GH

Aims

Implant waste during total hip arthroplasty (THA) represents a significant cost to the USA healthcare system. While studies have explored methods to improve THA cost-effectiveness, the literature comparing the proportions of implant waste by intraoperative technology used during THA is limited. The aims of this study were to: 1) examine whether the use of enabling technologies during THA results in a smaller proportion of wasted implants compared to navigation-guided and conventional manual THA; 2) determine the proportion of wasted implants by implant type; and 3) examine the effects of surgeon experience on rates of implant waste by technology used.

Methods

We identified 104,420 implants either implanted or wasted during 18,329 primary THAs performed on 16,724 patients between January 2018 and June 2022 at our institution. THAs were separated by technology used: robotic-assisted (n = 4,171), imageless navigation (n = 6,887), and manual (n = 7,721). The primary outcome of interest was the rate of implant waste during primary THA.


Bone & Joint Open
Vol. 3, Issue 9 | Pages 684 - 691
1 Sep 2022
Rodriguez S Shen TS Lebrun DG Della Valle AG Ast MP Rodriguez JA

Aims

The volume of ambulatory total hip arthroplasty (THA) procedures is increasing due to the emphasis on value-based care. The purpose of the study is to identify the causes for failed same-day discharge (SDD) and perioperative factors leading to failed SDD.

Methods

This retrospective cohort study followed pre-selected patients for SDD THA from 1 August 2018 to 31 December 2020. Inclusion criteria were patients undergoing unilateral THA with appropriate social support, age 18 to 75 years, and BMI < 37 kg/m2. Patients with opioid dependence, coronary artery disease, and valvular heart disease were excluded. Demographics, comorbidities, and perioperative data were collected from the electronic medical records. Possible risk factors for failed SDD were identified using multivariate logistic regression.