Causes, risk factors, and costs associated with ninety-day readmissions following primary total hip arthroplasty for femoral neck fractures

A preoperative risk assessment tool for predicting adverse outcomes among total shoulder arthroplasty patients

BACKGROUND

With the increased utilization of Total Shoulder Arthroplasty (TSA) in the outpatient setting, understanding the risk factors associated with complications and hospital readmissions becomes a more significant consideration. Prior developed assessment metrics in the literature either consisted of hard-to-implement tools or relied on postoperative data to guide decision-making. This study aimed to develop a preoperative risk assessment tool to help predict the risk of hospital readmission and other postoperative adverse outcomes.

METHODS

We retrospectively evaluated the 2019-2022(Q2) Medicare fee-for-service inpatient and outpatient claims data to identify primary anatomic or reserve TSAs and to predict postoperative adverse outcomes within 90 days postdischarge, including all-cause hospital readmissions, postoperative complications, emergency room visits, and mortality. We screened 108 candidate predictors, including demographics, social determinants of health, TSA indications, prior 12-month hospital, and skilled nursing home admissions, comorbidities measured by hierarchical conditional categories, and prior orthopedic device-related complications. We used two approaches to reduce the number of predictors based on 80% of the data: 1) the Least Absolute Shrinkage and Selection Operator logistic regression and 2) the machine-learning-based cross-validation approach, with the resulting predictor sets being assessed in the remaining 20% of the data. A scoring system was created based on the final regression models' coefficients, and score cutoff points were determined for low, medium, and high-risk patients.

RESULTS

A total of 208,634 TSA cases were included. There was a 6.8% hospital readmission rate with 11.2% of cases having at least one postoperative adverse outcome. Fifteen covariates were identified for predicting hospital readmission with the area under the curve of 0.70, and 16 were selected to predict any adverse postoperative outcome (area under the curve = 0.75). The Least Absolute Shrinkage and Selection Operator and machine learning approaches had similar performance. Advanced age and a history of fracture due to orthopedic devices are among the top predictors of hospital readmissions and other adverse outcomes. The score range for hospital readmission and an adverse postoperative outcome was 0 to 48 and 0 to 79, respectively. The cutoff points for the low, medium, and high-risk categories are 0-9, 10-14, ≥15 for hospital readmissions, and 0-11, 12-16, ≥17 for the composite outcome.

CONCLUSION

Based on Medicare fee-for-service claims data, this study presents a preoperative risk stratification tool to assess hospital readmission or adverse surgical outcomes following TSA. Further investigation is warranted to validate these tools in a variety of diverse demographic settings and improve their predictive performance.

Higher Comorbidities are Correlated With Readmission Following Arthroplasty for Femoral Neck Fracture

Background

A desire to control cost and improve patient outcomes following arthroplasty led to the introduction of the Center for Medicare and Medicaid Service Comprehensive Care for Joint Replacement Program. Hemi and total hip arthroplasty for femoral neck fracture has been shown to have worse outcomes than those for osteoarthritis. However, little has been studied about the effect of comorbidities on costs associated with arthroplasty for femoral neck fracture. This study investigates how the number of comorbidities influence 90-day outcomes and cost following hemi or total hip arthroplasty for displaced femoral neck fracture in patients covered by the Comprehensive Care for Joint Replacement bundle.

Methods

We reviewed all Medicare hip fracture patients undergoing hemi or total hip arthroplasty at our institution between April 2016 and November 2020. Basic demographic and perioperative information was collected. The primary outcome was hospital readmission within 90 days. The data set captured 90-day readmission to any institution, not just within our system. Secondary outcomes included 90-day reoperation and outpatient complications. Multiple logistic regression was used to examine the influence of number of comorbidities on the primary and secondary outcomes while controlling for other variables.

Results

The cohort comprised 378 patients (72% female), mean age 82 (±9) years, mean body mass index 23.4 (±4.7) kg/m2. For every additional comorbidity, the odds of related readmission without reoperation increased by 1.261 (95% confidence interval [1.055-1.507], P = .011). Odds of reoperation and odds of outpatient complication did not show statistical significance with the available numbers.

Conclusions

Increasing preoperative comorbidities results in a higher odd of readmission within 90 days following arthroplasty for femoral neck fracture in this Medicare population.

Complications and Healthcare Cost of Total Hip Arthroplasty in Patients with Depressive Disorder

Purpose

The purpose of this study was to determine whether the rates of (1) in-hospital lengths of stay (LOS), (2) readmissions, (3) medical complications, and (4) costs of care are higher for patients with depressive disorder (DD) undergoing primary total hip arthroplasty (THA) for treatment of femoral neck fractures (FNFs).

Materials and Methods

A retrospective query of a national administrative claims database for patients undergoing primary THA from 2006 to 2014 was conducted. Patients with DD undergoing THA for treatment of FNF were 1:5 ratio propensity score matched to a cohort (DD=6,758, controls=33,708). Primary endpoints included LOS, 90-day medical complications, 90-day readmissions, and healthcare reimbursements. A P-value less than 0.05 was considered statistically significant.

Results

Longer LOS were observed for patients with DD compared to those without DD (5.6 days vs. 5.4 days, P<0.001). Similar readmission rates (29.9% vs. 25.0%, odds ratio [OR] 1.03, P=0.281) were observed between groups. The odds of 90-day medical complications were higher for patients with DD compared to control subjects (60.6% vs. 21.4%, OR 1.57, P<0.0001). Within the 90-day episode of care interval, patients with a history of DD incurred significantly higher healthcare expenditures ($21,382 vs. $19,781, P<0.001).

Conclusion

Our findings showed longer LOS, higher odds of 90-day medical complications, and higher healthcare expenditures within the 90-day episode of care following a primary THA for treatment of FNF for patients with DD compared to the matched cohort. Thus, accordingly, patients with DD should receive counseling prior to undergoing surgery.