Cost-utility analysis of robotic arm-assisted medial compartment knee arthroplasty

Abstract

AimsTo perform an incremental cost-utility analysis and assess the impact of differential costs and case volume on the cost-effectiveness of robotic arm-assisted unicompartmental knee arthroplasty (rUKA) compared to manual (mUKA).MethodsThis was a five-year follow-up study of patients who were randomized to rUKA (n = 64) or mUKA (n = 65). Patients completed the EuroQol five-dimension questionnaire (EQ-5D) preoperatively, and at three months and one, two, and five years postoperatively, which was used to calculate quality-adjusted life years (QALYs) gained. Costs for the primary and additional surgery and healthcare costs were calculated.ResultsrUKA was associated with a relative 0.012 QALY gain at five years, which was associated with an incremental cost per QALY of £13,078 for a unit undertaking 400 cases per year. A cost per QALY of less than £20,000 was achieved when ≥ 300 cases were performed per year. However, on removal of the cost for a revision for presumed infection (mUKA group, n = 1) the cost per QALY was greater than £38,000, which was in part due to the increased intraoperative consumable costs associated with rUKA (£626 per patient). When the absolute cost difference (operative and revision costs) was less than £240, a cost per QALY of less than £20,000 was achieved. On removing the cost of the revision for infection, rUKA was cost-neutral when more than 900 cases per year were undertaken and when the consumable costs were zero.ConclusionrUKA was a cost-effective intervention with an incremental cost per QALY of £13,078 at five years, however when removing the revision for presumed infection, which was arguably a random event, this was no longer the case. The absolute cost difference had to be less than £240 to be cost-effective, which could be achieved by reducing the perioperative costs of rUKA or if there were increased revision costs associated with mUKA with longer follow-up.Cite this article: Bone Jt Open 2023;4(11):889–899.