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      Cost-Effectiveness Analysis Comparing Proximal Row Carpectomy and Four-Corner Arthrodesis

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          Abstract

          Background:

          The optimal surgical treatment for scapholunate advanced collapse (SLAC) and scaphoid nonunion advanced collapse (SNAC) remains unclear. To inform clinical decision-makers, we conducted a cost-effectiveness analysis comparing proximal row carpectomy (PRC) and four-corner arthrodesis (FCA).

          Methods:

          A Markov microsimulation model was used to compare clinical outcomes, costs, and health utilities between PRC and FCA. The model used a 10-year time horizon and a 1-month cycle length, and it was evaluated from the societal perspective. Utilities and clinical parameters including transition probabilities for debridement for infection, removal of implants, conversion to total wrist arthrodesis, revision FCA, and revision total wrist arthrodesis were obtained from published literature. Timing of complications was estimated from the literature. Direct medical costs were derived from Medicare ambulatory surgical cost data, and indirect costs for missed work due to surgical procedures and complications were included. The effectiveness outcome was quality-adjusted life years (QALYs). Probabilistic sensitivity analysis and 1-way threshold analysis for utilities were performed.

          Results:

          In the base-case model, PRC dominated FCA (i.e., PRC had lower cost and greater effectiveness). The mean (and standard deviation) for the total cost and QALYs per patient were $30,970 ± $5,931 and 8.24 ± 1.28, respectively, for PRC and $44,526 ± $11,205 and 8.23 ± 1.26, respectively, for FCA. In the probabilistic sensitivity analysis, PRC dominated FCA in 57% of the 1 million iterations. The cost-effectiveness acceptability curve indicated that PRC is the most cost-effective strategy regardless of the willingness-to-pay threshold up to $100,000/QALY.

          Conclusions:

          PRC dominated FCA in the base-case analysis and in the probabilistic sensitivity analysis. These results suggest that PRC is the optimal strategy for Stage-I or II SLAC and for SNAC in patients ≥55 years of age.

          Level of Evidence:

          Economic Level IV. See Instructions for Authors for a complete description of levels of evidence.

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          Most cited references51

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          Recommendations for Conduct, Methodological Practices, and Reporting of Cost-effectiveness Analyses: Second Panel on Cost-Effectiveness in Health and Medicine.

          Since publication of the report by the Panel on Cost-Effectiveness in Health and Medicine in 1996, researchers have advanced the methods of cost-effectiveness analysis, and policy makers have experimented with its application. The need to deliver health care efficiently and the importance of using analytic techniques to understand the clinical and economic consequences of strategies to improve health have increased in recent years.
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            An introduction to Markov modelling for economic evaluation.

            Markov models are often employed to represent stochastic processes, that is, random processes that evolve over time. In a healthcare context, Markov models are particularly suited to modelling chronic disease. In this article, we describe the use of Markov models for economic evaluation of healthcare interventions. The intuitive way in which Markov models can handle both costs and outcomes make them a powerful tool for economic evaluation modelling. The time component of Markov models can offer advantages of standard decision tree models, particularly with respect to discounting. This paper gives a comprehensive description of Markov modelling for economic evaluation, including a discussion of the assumptions on which the type of model is based, most notably the memoryless quality of Markov models often termed the 'Markovian assumption'. A hypothetical example of a drug intervention to slow the progression of a chronic disease is employed to demonstrate the modelling technique and the possible methods of analysing Markov models are explored. Analysts should be aware of the limitations of Markov models, particularly the Markovian assumption, although the adept modeller will often find ways around this problem.
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              Implementation of a Value-Driven Outcomes Program to Identify High Variability in Clinical Costs and Outcomes and Association With Reduced Cost and Improved Quality.

              Transformation of US health care from volume to value requires meaningful quantification of costs and outcomes at the level of individual patients.
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                Author and article information

                Journal
                JB JS Open Access
                JB JS Open Access
                JBJSOA
                JBJS Open Access
                Journal of Bone and Joint Surgery, Inc.
                2472-7245
                Apr-Jun 2020
                2 June 2020
                : 5
                : 2
                : e0080
                Affiliations
                [1 ]Departments of Economics (M.Y.) and Orthopaedics (D.A.I., B.I.M., A.R.T., and N.H.K.), and Division of Epidemiology (R.E.N.), University of Utah, Salt Lake City, Utah
                [2 ]VA Salt Lake City Health Care System, Salt Lake City, Utah
                Author notes
                [a ]Email address for N.H. Kazmers: nkazmers@ 123456gmail.com
                Article
                JBJSOA-D-19-00080 00015
                10.2106/JBJS.OA.19.00080
                7418915
                37e4b924-f114-408c-99eb-63139d41231d
                Copyright © 2020 The Authors. Published by The Journal of Bone and Joint Surgery, Incorporated. All rights reserved.

                This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

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