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Background: Controlling escalating costs of hip (THA) and knee arthroplasty (TKA) without compromising quality of care has created the need for innovative system reorganization to inform sustainable solutions.Questions/purposes: The purpose of this study was to inform estimates of the value of THA and TKA by determining: (1) the data sources data required to obtain costs across the care continuum; (2) the data required for different analytical perspectives; and (3) the relative costs across the continuum of care.Methods: Within the context of a pragmatic randomized controlled trial comparing alternative care pathways, we captured healthcare resource use: (1) 12 months before surgery; (2) inpatient; (3) acute recovery; and (4) long-term recovery 3 and 12 months postsurgery. We established a standardized costing model to reflect both the healthcare payer and patient perspectives.Results: Multiple data sources from regional health authorities, administrative databases, and patient questionnaire were required to estimate costs across the care continuum. Inpatient and acute care costs were approximately 60% of the total with the remaining 40% incurred 12 months presurgery and 12 months postsurgery. Regional health authorities bear close to 60%, and patient costs are approximately 30% of the mean total costs, most of which were incurred after the acute inpatient stay.Conclusions: To fully understand the value of an orthopaedic intervention such as THA and TKA, a broader perspective than one limited to the payer should be considered using a standardized measurement framework over a relevant time horizon and from multiple viewpoints to reflect the substantial patient burden and support sustainable improvement over the care continuum.Level Of Evidence: Level III, economic and decision analyses study. See Guidelines for Authors for a complete description of levels of evidence. [ABSTRACT FROM AUTHOR]

Context: Adjusted survival curves are often presented in medical research articles. The most commonly used method for calculating such curves is the mean of covariates method, in which average values of covariates are entered into a proportional hazards regression equation. Use of this method is widespread despite published concerns regarding the validity of resulting curves.Objective: To compare the mean of covariates method to the less widely used corrected group prognosis method in an analysis evaluating survival in patients with and without diabetes. In the latter method, a survival curve is calculated for each level of covariates, after which an average survival curve is calculated as a weighted average of the survival curves for each level of covariates.Design, Setting, and Patients: Analysis of cohort study data from 11 468 Alberta residents undergoing cardiac catheterization between January 1, 1995, and December 31, 1996.Main Outcome Measures: Crude and risk-adjusted survival for up to 3 years after cardiac catheterization in patients with vs without diabetes, analyzed by the mean of covariates method vs the corrected group prognosis method.Results: According to the mean of covariates method, adjusted survival at 1044 days was 94.1% and 94.9% for patients with and without diabetes, respectively, with misleading adjusted survival curves that fell above the unadjusted curves. With the corrected group prognosis method, the corresponding survival values were 91.3% and 92.4%, with curves that fell more appropriately between the unadjusted curves.Conclusions: Misleading adjusted survival curves resulted from using the mean of covariates method of analysis for our data. We recommend using the corrected group prognosis method for calculating risk-adjusted curves. [ABSTRACT FROM AUTHOR]