Periprosthetic joint infection (PJI) is a common cause of revision total knee surgery. Although debridement and implant retention (DAIR) has lower success rates in the chronic setting, it is an accepted treatment for acute PJI. There are two broad DAIR strategies: single debridement or a planned double debridement performed days apart. The purpose of this study is to evaluate the cost-effectiveness of single versus double DAIR with antibiotic beads for acute PJI in total knee arthroplasty (TKA). A decision tree using single or double DAIR as treatment strategies for acute PJI was constructed. Quality Adjusted Life Years (QALYs) and costs associated with the two treatment arms were calculated. Treatment success rates, failure rates, and mortality rates were derived from the literature. Medical costs were derived from both the literature and Medicare data. A cost-effectiveness plane was constructed from multiple Monte Carlo trials. A sensitivity analysis identified parameters most influencing the optimal strategy decision.Abstract
Introduction
Methodology
Quality measures play a substantial role in the Centers for Medicare and Medicaid Services' hospital payment and public reporting programs. The purpose of this study was to assess whether public measurement of total hip and knee arthroplasty risk-standardized readmission (RSRRs) and complication rates (RSCRs) was temporally associated with decreasing rates of adverse outcomes among Medicare beneficiaries. We evaluated annual trends in hospital-level risk-standardized complication and readmission rates in the fiscal years 2010–11 and 2016–17 for patients undergoing hospital-based inpatient hip/knee replacement procedures. We calculated hospital-level rates using the same measures and methodology used in public reporting. We examined annual trends in the distribution of hospital-level outcomes through density plots (similar to histograms).Introduction
Methods
Prior research has shown that depression negatively impacts outcomes after total hip arthroplasty (THA); however, arthroplasty patients may also have depressive symptoms without an established diagnosis. The purpose of this study was to determine whether the Patient Health Questionnaire-2 (PHQ-2), a two-question depression screener, correlates with joint-specific symptom improvement after primary THA. This was a prospective cohort study. Patients completed the PHQ-2 and the Hip Disability and Osteoarthritis Outcome Score - Joint Replacement (HOOS-JR) prior to THA, with follow-up at 6 weeks and 6 months. An a priori power analysis determined a sample size of 31 would detect an effect size of 0.5 with a power of 0.80. We used previously established minimum clinically important difference (MCID) values for HOOS-JR. Continuous variables were analyzed with t-tests or Mann-Whitney tests while categorical variables were analyzed with Chi square or Fisher exact tests.Background
Methods
Patient-reported outcome (PRO) data are variably collected before and after total hip/knee arthroplasty (THA/TKA). We assessed the generalizability of incentivized, prospectively collected PRO data for THA/TKA patient-reported outcome performance measure (PRO-PM) development. The Centers for Medicare & Medicaid Services (CMS) received PRO data voluntarily submitted by hospitals in a bundled payment model for THA/TKA procedures. Participating hospitals who collected and successfully submitted these data received an increase in their overall quality score, possibly resulting in a positive impact on model reconciliation payments. PRO data were collected from Medicare Fee-For-Service beneficiaries >= 65 years undergoing elective primary THA/TKA procedures from July 1 to August 31, 2016 at hospitals participating in the model. Pre-operative PRO and risk variable data were collected 0 – 90 days prior to surgery, while post-operative PRO data were collected 270 – 365 days following elective THA/TKA. PRO pre-op and post-op data were matched to Medicare claims data for determination of clinically eligible procedures and clinical comorbidities. We compared the characteristics of patients submitting PRO data to other elective primary THA/TKA recipients in the US.Introduction
Methods
Use of large databases for orthopaedic research has increased exponentially. Each database represents unique patient populations and vary in methodology of data acquisition. The purpose of this study was to evaluate differences in reported demographics, comorbidities and complications following total hip arthroplasty (THA) amongst four commonly used databases. Patients who underwent primary THA during 2010–2012 were identified within National Surgical Quality Improvement Programs (NSQIP), Nationwide Inpatient Sample (NIS), Medicare Standard Analytic Files (MED) and Humana Claims Database (HAC). NSQIP definitions for comorbidities and surgical complications were queried in NIS, MED, and HAC using coding algorithms. Age, sex, comorbidities, inpatient and 30-day postoperative complications were compared (NIS has inpatient data only). Primary THAs from each database were 22,644 (HAC), 371,715 (MED), 188,779 (NIS) and 27,818 (NSQIP). Age and gender distribution were similar between databases. There was variability in the prevalence of comorbidities and complications depending upon the database and duration of post-operative follow-up. HAC and MED had twice the prevalence of COPD, coagulopathy and diabetes than NSQIP. NSQIP had more than twice the obesity than NIS. HAC had more than twice the rates of 30-day complications at all endpoints compared to NSQIP and more than twice the DVTs, strokes and deep infection as MED at 30-days post-op. Comparison of inpatient and 30-day complications rates demonstrated more than twice the amount of infections and DVTs are captured when analysis is extended from inpatient stay to 30-days post-op. Amongst databases commonly used in orthopaedic research, there is considerable variation in complication rates following THA depending upon the database. It will be important to consider these differences when critically evaluating database research. Additionally, with the advent of bundled payments, these differences must be considered in risk adjustment models.