Learning curve for active robotic total knee arthroplasty.

PURPOSE: Total Knee Arthroplasty (TKA) procedures incorporate technology in an attempt to improve outcomes. The Active Robot (ARo) performs a TKA with automated resections of the tibia and femur in efforts to optimize bone cuts. Evaluating the Learning Curve (LC) is essential with a novel tool. The purpose of this study was to assess the associated LC of ARo for TKA. METHODS: A multi-center prospective FDA cohort study was conducted from 2017 to 2018 including 115 patients that underwent ARo. Surgical time of the ARo was defined as Operative time (OT), segmented as surgeon-dependent time (patient preparation and registration) and surgeon-independent time (autonomous bone resection by the ARo). An average LC for all surgeons was computed. Complication rates and patient-reported outcome (PRO) scores were recorded and examined to evaluate for any LC trends in these patient related factors. RESULTS: The OT for the cases 10-12 were significantly quicker than the OT time of cases 1-3 (p < 0.028), at 36.5 ± 7.4 down from 49.1 ± 17 min. CUSUM and confidence interval analysis of the surgeon-dependent time showed different LCs for each surgeon, ranging from 12 to 19 cases. There was no difference in device related complications or PRO scores over the study timeframe. CONCLUSION: Active Robotic total knee arthroplasty is associated with a short learning curve of 10-20 cases. The learning curve was associated with the surgical time dedicated to the robotic specific portion of the case. There was no learning curve-associated device-related complications, three-dimensional component position, or patient-reported outcome scores. LEVEL OF EVIDENCE: Level II.

The Implications of Aging Population Demographics on the Delivery of Primary Total Joint Arthroplasty in a Bundled Payment System.

BACKGROUND: The Centers for Medicare & Medicaid Services (CMS)'s Bundled Payments for Care Improvement (BPCI) program provides a set payment for the provision of primary total joint arthroplasty (TJA) care regardless of age and risk factors. Published literature indicates that the cost of care per episode of TJA increases with age. We examined the implication of this relationship and the effect of projected changes of age demographics on our center's BPCI experience. METHODS: A retrospective review of prospectively collected data on 1,662 Medicare BPCI patients undergoing primary total knee arthroplasty (TKA) and total hip arthroplasty (THA) from 2013 to 2016 at a single orthopaedic institution was performed. The relationship between age and cost of care was first determined in our analysis of our BPCI experience. We then performed a cost analysis by age group with respect to our institution's profit or loss per episode of care. A forecast for shifting age demographics in our region, modeled by the U.S. Census Bureau's Federal-State Cooperative for Population Estimates (FSCPE) and Projections (FSCPP), was used to evaluate the financial implications for our BPCI program. RESULTS: Our institution sustains a significant loss of $1,934 (p < 0.001) per case for patients 85 to 99 years of age, which is offset by profits associated with treating patients in younger age groups. This age group (85 to 99 years of age) will double by the year 2040 in our region, whereas the youngest age group (65 to 69 years of age) is projected to marginally increase by 12%. The average cost of care per primary TJA will rise because of the predicted shifting age demographics, compounded by an estimated 3% inflation rate. Utilizing the current BPCI reimbursement rate, we project an inflection point of declining profits after the year 2030 with the given projections for our regional population. CONCLUSIONS: The regional population served by our institution is aging. This shift will lead to an increased cost of care and diminishing profits for TJA after 2030. The CMS's BPCI initiative and novel alternative payment models (APMs) should consider age as a modifier for reimbursement to incentivize care for the vulnerable and older age groups. CLINICAL RELEVANCE: The findings of the present study are clinically relevant for decision-making regarding the allocation of resources in the setting of an aging population.