Aims. To 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). Methods. This 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
To assess the cost-effectiveness of a two-layer compression bandage versus a standard wool and crepe bandage following total knee arthroplasty, using patient-level data from the Knee Replacement Bandage Study (KReBS). A cost-utility analysis was undertaken alongside KReBS, a pragmatic, two-arm, open label, parallel-group, randomized controlled trial, in terms of the cost per quality-adjusted life year (QALY). Overall, 2,330 participants scheduled for total knee arthroplasty (TKA) were randomized to either a two-layer compression bandage or a standard wool and crepe bandage. Costs were estimated over a 12-month period from the UK NHS perspective, and health outcomes were reported as QALYs based on participants’ EuroQol five-dimesion five-level questionnaire responses. Multiple imputation was used to deal with missing data and sensitivity analyses included a complete case analysis and testing of costing assumptions, with a secondary analysis exploring the inclusion of productivity losses.Aims
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The aims of this study were to assess mapping models to predict the three-level version of EuroQoL five-dimension utility index (EQ-5D-3L) from the Oxford Knee Score (OKS) and validate these before and after total knee arthroplasty (TKA). A retrospective cohort of 5,857 patients was used to create the prediction models, and a second cohort of 721 patients from a different centre was used to validate the models, all of whom underwent TKA. Patient characteristics, BMI, OKS, and EQ-5D-3L were collected preoperatively and one year postoperatively. Generalized linear regression was used to formulate the prediction models.Aims
Methods