In November 2017, the Center for Medicare and Medicaid Services (CMS) finalized the 2018 Medicare Outpatient Prospective Payment System rule that removed total knee arthroplasty (TKA) procedures from the Medicare inpatient-only (IPO) list of procedures. This action had significant and unexpected consequences. For several years, CMS has utilized a rule called the “Two-Midnight Rule” to define outpatient status for all procedures not on the IPO list. CMS made TKA subject to the “Two-Midnight Rule” in conjunction with the decision to move TKA off the IPO list. According to the “Two-Midnight Rule,” a hospital admission should be expected to span at least two midnights in order to be covered as an inpatient procedure. If it can be reliably expected that the patient will not require at least two midnights in the hospital, the “Two-Midnight Rule” suggests that the patient is considered an outpatient and is therefore subject to outpatient payment policies. Under prior guidance related to the “Two-Midnight Rule;” however, CMS also states that Medicare We looked at 3 different levels of the IPO rule impact on TKA for Medicare beneficiaries: a national comparison of fee for service (FFS) inpatient and outpatient classification for 2017 vs 2018; a survey of AAHKS surgeons completed in April of 2019; and an in-depth analysis of a large academic medical center experience. An analysis of change in inpatient classification of TKA patients over time, number of Quality Improvement Organization (QIO) audits, compliance solutions of organizations for the new rule and cost implications of those compliance solutions were evaluated.Introduction
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Aims. The purpose of this study was to determine the impact of the removal of total knee arthroplasty (TKA) from the Medicare
At our tertiary, large, academic healthcare system, we have access to an academic medical center (AMC), a community based, orthopedic friendly, efficient hospital (CBH) and several ambulatory care centers (ASC) which are being prepared to provide same day discharge (SDD) TJA and UKA. We had a near-capacity AMC with an excellent ability to care for medically and technically complicated TJA patients. However, efficiency was less than desired regardless of case complexity with an average effective case time of 4 hours. Concurrently, the orthopaedically, under-utilized community-based hospital (CBH) wanted to increase volume, improve margins, and become a TJA Center of Excellence with the ability to provide an efficient Hospital Outpatient Department (HOPD) and SDD TJA surgery experience. Methods. The CBH had a main operating floor and a separate floor of four OR suites which were repurposed with the goal of utilizing these rooms for TJA four days per week with an average of 3.5 cases per room per day. We preferentially performed primary, uncomplicated TJA, UKA, and minimally invasive TJA at the CBH. Revision surgeries, patients with extensive medical comorbidities, and complex primary surgeries would be performed at the AMC. Our goals were to decrease costs, readmissions, length of stay, and increase margins at the CBH while increasing efficiency, revenue and volume. Protocols were developed to facilitate SDD UKA and THA at both hospitals as well as rapid recovery protocols for TKA at both hospitals with the understanding that the CBH would perform more of these cases but the efficiency could also be implemented at the AMC when possible. We also needed a strategy to deal with TKA and eventually THA being removed from the
To identify variables independently associated with same-day discharge (SDD) of patients following revision total knee arthroplasty (rTKA) and to develop machine learning algorithms to predict suitable candidates for outpatient rTKA. Data were obtained from the American College of Surgeons National Quality Improvement Programme (ACS-NSQIP) database from the years 2018 to 2020. Patients with elective, unilateral rTKA procedures and a total hospital length of stay between zero and four days were included. Demographic, preoperative, and intraoperative variables were analyzed. A multivariable logistic regression (MLR) model and various machine learning techniques were compared using area under the curve (AUC), calibration, and decision curve analysis. Important and significant variables were identified from the models.Aims
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There is concern that aggressive target pricing in the new Bundled Payment for Care Improvement Advanced (BPCI-A) penalizes high-performing groups that had achieved low costs through prior experience in bundled payments. We hypothesize that this methodology incorporates unsustainable downward trends on Target Prices and will lead to groups opting out of BPCI Advanced in favour of a traditional fee for service. Using the Centers for Medicare and Medicaid Services (CMS) data, we compared the Target Price factors for hospitals and physician groups that participated in both BPCI Classic and BPCI Advanced (legacy groups), with groups that only participated in BPCI Advanced (non-legacy). With rebasing of Target Prices in 2020 and opportunity for participants to drop out, we compared retention rates of hospitals and physician groups enrolled at the onset of BPCI Advanced with current enrolment in 2020.Aims
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