BACKGROUND: An aim of the use of computer navigation is to reduce rates of revisions of total knee replacements by improving the alignment achieved at the surgery. However, the decision to adopt this technology may be difficult for some centers, especially low-volume centers, where the cost of purchasing this equipment may be high. The purpose of this study was to examine the impact of hospital volume on the cost-effectiveness of this new technology in order to determine its feasibility and the level of evidence that should be sought prior to its adoption. METHODS: A Markov decision model was used to evaluate the impact of hospital volume on the cost-effectiveness of computer-assisted knee arthroplasty in a theoretical cohort of sixty-five-year-old patients with end-stage arthritis of the knee to coincide with the peak incidence of knee arthroplasty in the United States. RESULTS: Computer-assisted surgery becomes less cost-effective as the annual hospital volume decreases, as the cost of the navigation increases, and as the impact on revision rates decreases. Centers at which 250, 150, and twenty-five computer-navigated total knee arthroplasties are performed per year will require a reduction of the annual revision rate of 2%, 2.5%, and 13%, respectively, per year over a twenty-year period for computer navigation to be cost-effective. CONCLUSIONS: Computer navigation is less likely to be a cost-effective investment in health-care improvement in centers with a low volume of joint replacements, where its benefit is most likely to be realized. However, it may be a cost-effective technology for centers with a higher volume of joint replacements, where the decrease in the rate of knee revision needed to make the investment cost-effective is modest, if improvements in revision rates with the use of this technology can be realized.
BACKGROUND: An aim of the use of computer navigation is to reduce rates of revisions of total knee replacements by improving the alignment achieved at the surgery. However, the decision to adopt this technology may be difficult for some centers, especially low-volume centers, where the cost of purchasing this equipment may be high. The purpose of this study was to examine the impact of hospital volume on the cost-effectiveness of this new technology in order to determine its feasibility and the level of evidence that should be sought prior to its adoption. METHODS: A Markov decision model was used to evaluate the impact of hospital volume on the cost-effectiveness of computer-assisted knee arthroplasty in a theoretical cohort of sixty-five-year-old patients with end-stage arthritis of the knee to coincide with the peak incidence of knee arthroplasty in the United States. RESULTS: Computer-assisted surgery becomes less cost-effective as the annual hospital volume decreases, as the cost of the navigation increases, and as the impact on revision rates decreases. Centers at which 250, 150, and twenty-five computer-navigated total knee arthroplasties are performed per year will require a reduction of the annual revision rate of 2%, 2.5%, and 13%, respectively, per year over a twenty-year period for computer navigation to be cost-effective. CONCLUSIONS: Computer navigation is less likely to be a cost-effective investment in health-care improvement in centers with a low volume of joint replacements, where its benefit is most likely to be realized. However, it may be a cost-effective technology for centers with a higher volume of joint replacements, where the decrease in the rate of knee revision needed to make the investment cost-effective is modest, if improvements in revision rates with the use of this technology can be realized.
Authors: Rolf G Haaker; Martin Stockheim; Michael Kamp; Gunnar Proff; Johannes Breitenfelder; Andreas Ottersbach Journal: Clin Orthop Relat Res Date: 2005-04 Impact factor: 4.176
Authors: Steven Kurtz; Fionna Mowat; Kevin Ong; Nathan Chan; Edmund Lau; Michael Halpern Journal: J Bone Joint Surg Am Date: 2005-07 Impact factor: 5.284
Authors: Nizar N Mahomed; Jane Barrett; Jeffrey N Katz; John A Baron; John Wright; Elena Losina Journal: J Bone Joint Surg Am Date: 2005-06 Impact factor: 5.284
Authors: Kevin J Bozic; Patricia Katz; Miriam Cisternas; Linda Ono; Michael D Ries; Jonathan Showstack Journal: J Bone Joint Surg Am Date: 2005-03 Impact factor: 5.284
Authors: D G Fryback; E J Dasbach; R Klein; B E Klein; N Dorn; K Peterson; P A Martin Journal: Med Decis Making Date: 1993 Apr-Jun Impact factor: 2.583
Authors: A Laupacis; R Bourne; C Rorabeck; D Feeny; C Wong; P Tugwell; K Leslie; R Bullas Journal: J Bone Joint Surg Am Date: 1993-11 Impact factor: 5.284
Authors: Alfonso Manzotti; Pietro Cerveri; Elena De Momi; Chris Pullen; Norberto Confalonieri Journal: Int Orthop Date: 2009-06-10 Impact factor: 3.075
Authors: Benedict U Nwachukwu; Kevin J Bozic; William W Schairer; Jaime L Bernstein; David S Jevsevar; Robert G Marx; Douglas E Padgett Journal: Clin Orthop Relat Res Date: 2014-09-30 Impact factor: 4.176
Authors: Joseph F Konopka; Andreas H Gomoll; Thomas S Thornhill; Jeffrey N Katz; Elena Losina Journal: J Bone Joint Surg Am Date: 2015-05-20 Impact factor: 5.284