A Preoperative Risk Prediction Tool for Discharge to a Skilled Nursing or Rehabilitation Facility After Total Joint Arthroplasty

High Risk of Readmission After THA Regardless of Functional Status in Patients Discharged to Skilled Nursing Facility

BACKGROUND

The postoperative period and subsequent discharge planning are critical in our continued efforts to decrease the risk of complications after THA. Patients discharged to skilled nursing facilities (SNFs) have consistently exhibited higher readmission rates compared with those discharged to home healthcare. This elevated risk has been attributed to several factors but whether readmission is associated with patient functional status is not known.

QUESTIONS/PURPOSES

After controlling for relevant confounding variables (functional status, age, gender, caregiver support available at home, diagnosis [osteoarthritis (OA) versus non-OA], Charlson comorbidity index [CCI], the Area Deprivation Index [ADI], and insurance), are the odds of 30- and 90-day hospital readmission greater among patients initially discharged to SNFs than among those treated with home healthcare after THA?

METHODS

This was a retrospective, comparative study of patients undergoing THA at any of 11 hospitals in a single, large, academic healthcare system between 2017 and 2022 who were discharged to an SNF or home healthcare. During this period, 13,262 patients were included. Patients discharged to SNFs were older (73 ± 11 years versus 65 ± 11 years; p < 0.001), less independent at hospital discharge (6-click score: 16 ± 3.2 versus 22 ± 2.3; p < 0.001), more were women (71% [1279 of 1796] versus 56% [6447 of 11,466]; p < 0.001), insured by Medicare (83% [1497 of 1796] versus 52% [5974 of 11,466]; p < 0.001), living in areas with greater deprivation (30% [533 of 1796] versus 19% [2229 of 11,466]; p < 0.001), and had less assistance available from at-home caregivers (29% [527 of 1796] versus 57% [6484 of 11,466]; p < 0.001). The primary outcomes assessed in this study were 30- and 90-day hospital readmissions. Although the system automatically flags readmissions occurring within 90 days at the various facilities in the overall healthcare system, readmissions occurring outside the system would not be captured. Therefore, we were not able to account for potential differential rates of readmission to external healthcare systems between the groups. However, given the large size and broad geographic coverage of the healthcare system analyzed, we expect the readmissions data captured to be representative of the study population. The focus on a single healthcare system also ensures consistency in readmission identification and reporting across subjects. We evaluated the association between discharge disposition (home healthcare versus SNF) and readmission. Covariates evaluated included age, gender, primary payer, primary diagnosis, CCI, ADI, the availability of at-home caregivers for the patient, and the Activity Measure for Post-Acute Care (AM-PAC) 6-clicks basic mobility score in the hospital. The adjusted relative risk (ARR) of readmission within 30 and 90 days of discharge to SNF (versus home healthcare) was estimated using modified Poisson regression models.

RESULTS

After adjusting for the 6-clicks mobility score, age, gender, ADI, OA versus non-OA, living environment, CCI, and insurance, patients discharged to an SNF were more likely to be readmitted within 30 and 90 days compared with home healthcare after THA (ARR 1.46 [95% CI 1.01 to 2.13]; p= 0.046 and ARR 1.57 [95% CI 1.23 to 2.01]; p < 0.001, respectively).

CONCLUSION

Patients discharged to SNFs after THA had a slightly higher likelihood of hospital readmission within 30 and 90 days compared with those discharged with home healthcare. This difference persisted even after adjusting for relevant factors like functional status, home support, and social determinants of health. These results indicate that for suitable patients, direct home discharge may be a safer and more cost-effective option than SNFs. Clinicians should carefully consider these risks and benefits when making postoperative discharge plans. Policymakers could consider incentives and reforms to improve care transitions and coordination across settings. Further research using robust methods is needed to clarify the reasons for higher SNF readmission rates. Detailed analysis of patient complexity, care processes, and causes of readmission in SNFs versus home health could identify areas for quality improvement. Prospective cohorts or randomized trials would allow stronger conclusions about cause-and-effect. Importantly, no patients should be unfairly "cherry-picked" or "lemon-dropped" based only on readmission risk scores. With proper support and care coordination, even complex patients can have good outcomes. The goal should be providing excellent rehabilitation for all, while continuously improving quality, safety, and value across settings.

LEVEL OF EVIDENCE

Level III, therapeutic study.

Validation of a Discharge Risk Calculator for Rural Patients Following Total Joint Arthroplasty

BACKGROUND

As the volume of total joint arthroplasty in the US continues to grow, new challenges surrounding appropriate discharge surface. Arthroplasty literature has demonstrated discharge disposition to postacute care facilities carries major risks regarding the need for revision surgery, patient comorbidities, and financial burden. To quantify, categorize, and mitigate risks, a decision tool that uses preoperative patient variables has previously been published and validated using an urban patient population. The aim of our investigation was to validate the same predictive model using patients in a rural setting undergoing total knee arthroplasty (TKA) and total hip arthroplasty.

METHODS

All TKA and THA procedures that were performed between January 2012 and September 2022 at our institution were collected. A total of 9,477 cases (39.6% TKA, 60.4% THA) were included for the validation analysis. There were 9 preoperative variables that were extracted in an automated fashion from the electronic medical record. Included patients were then run through the predictive model, generating a risk score representing that patient's differential risk of discharge to a skilled nursing facility versus home. Overall accuracy, sensitivity and specificity were calculated after obtaining risk scores.

RESULTS

Score cutoff equally maximizing sensitivity and specificity was 0.23, and the proportion of correct classifications by the predictive tool in this study population was found to be 0.723, with an area under the curve of 0.788 - both higher than previously published accuracy levels. With the threshold of 0.23, sensitivity and specificity were found to be 0.720 and 0.723, respectively.

CONCLUSIONS

The risk calculator showed very good accuracy, sensitivity, and specificity in predicting discharge location for rural patients undergoing TKA and THA, with accuracy even higher than in urban populations. The model provides an easy-to-use interface, with automation representing a viable tool in helping with shared decision-making regarding postoperative discharge plans.

A balance focused biometric does not predict rehabilitation needs and outcomes following total knee arthroplasty

BACKGROUND

Both length of hospital stay and discharge to a skilled nursing facility are key drivers of total knee arthroplasty (TKA)-associated spending. Identifying patients who require increased postoperative care may improve expectation setting, discharge planning, and cost reduction. Balance deficits affect patients undergoing TKA and are critical to recovery. We aimed to assess whether a device that measures preoperative balance predicts patients' rehabilitation needs and outcomes after TKA.

METHODS

40 patients indicated for primary TKA were prospectively enrolled and followed for 12 months. Demographics, KOOS-JR, and PROMIS data were collected at baseline, 3-months, and 12-months. Single-leg balance and sway velocity were assessed preoperatively with a force plate (Sparta Science, Menlo Park, CA). The primary outcome was patients' discharge facility (home versus skilled nursing facility). Secondary outcomes included length of hospital stay, KOOS-JR scores, and PROMIS scores.

RESULTS

The mean preoperative sway velocity for the operative leg was 5.7 ± 2.7 cm/s, which did not differ from that of the non-operative leg (5.7 ± 2.6 cm/s, p = 1.00). Five patients (13%) were discharged to a skilled nursing facility and the mean length of hospital stay was 2.8 ± 1.5 days. Sway velocity was not associated with discharge to a skilled nursing facility (odds ratio, OR = 0.82, 95% CI = 0.27-2.11, p = 0.690) or longer length of hospital stay (b = -0.03, SE = 0.10, p = 0.738). An increased sway velocity was associated with change in PROMIS items from baseline to 3 months for global07 ("How would you rate your pain on average?" b = 1.17, SE = 0.46, p = 0.015) and pain21 ("What is your level of pain right now?" b = 0.39, SE = 0.17, p = 0.025) at 3-months.

CONCLUSION

Preoperative balance deficits were associated with postoperative improvements in pain and function after TKA, but a balance focused biometric that measured single-leg sway preoperatively did not predict discharge to a skilled nursing facility or length of hospital stay after TKA making their routine measurement cost-ineffective.

Postoperative Discharge to Acute Rehabilitation or Skilled Nursing Facility Compared With Home Does Not Reduce Hospital Readmissions, Return to Surgery, or Improve Outcomes Following Adult Spine Deformity Surgery

STUDY DESIGN

Retrospective review of a prospective multicenter adult spinal deformity (ASD) study.

OBJECTIVE

The aim of this study was to evaluate 30-day readmissions, 90-day return to surgery, postoperative complications, and patient-reported outcomes (PROs) for matched ASD patients receiving nonhome discharge (NON), including acute rehabilitation (REHAB), and skilled nursing facility (SNF), or home (HOME) discharge following ASD surgery.

SUMMARY OF BACKGROUND DATA

Postoperative disposition following ASD surgery frequently involves nonhome discharge. Little data exists for longer term outcomes for ASD patients receiving nonhome discharge versus patients discharged to home.

MATERIALS AND METHODS

Surgically treated ASD patients prospectively enrolled into a multicenter study were assessed for NON or HOME disposition following hospital discharge. NON was further divided into REHAB or SNF. Propensity score matching was used to match for patient age, frailty, spine deformity, levels fused, and osteotomies performed at surgery. Thirty-day hospital readmissions, 90-day return to surgery, postoperative complications, and 1-year and minimum 2-year postoperative PROs were evaluated.

RESULTS

A total of 241 of 374 patients were eligible for the study. NON patients were identified and matched to HOME patients. Following matching, 158 patients remained for evaluation; NON and HOME had similar preoperative age, frailty, spine deformity magnitude, surgery performed, and duration of hospital stay ( P >0.05). Thirty-day readmissions, 90-day return to surgery, and postoperative complications were similar for NON versus HOME and similar for REHAB (N=64) versus SNF (N=42) versus HOME ( P >0.05). At 1-year and minimum 2-year follow-up, HOME demonstrated similar to better PRO scores including Oswestry Disability Index, Short-Form 36v2 questionnaire Mental Component Score and Physical Component Score, and Scoliosis Research Society scores versus NON, REHAB, and SNF ( P <0.05).

CONCLUSIONS

Acute needs must be considered following ASD surgery, however, matched analysis comparing 30-day hospital readmissions, 90-day return to surgery, postoperative complications, and PROs demonstrated minimal benefit for NON, REHAB, or SNF versus HOME at 1- and 2-year follow-up, questioning the risk and cost/benefits of routine use of nonhome discharge.

LEVEL OF EVIDENCE

Level III-prognostic.

Antibiotic Prophylaxis in the Management of Distal Fingertip Amputation and Crush Injury

Purpose

We sought to investigate the role of prophylactic antibiotics for distal fingertip crush injury or transphalangeal amputation treated outside of an operating room and better understand the factors that contribute to antibiotic-prescribing decisions. We hypothesized that prophylactic antibiotics do not meaningfully reduce the incidence of infection and that antibiotics are prescribed in a predictable way.

Methods

This is a retrospective review of all patients treated in a MedStar-affiliated emergency department or urgent care for nonsurgical distal fingertip trauma in 2019. Patient demographics, comorbidities, injury characteristics, interventions, and follow-up details were recorded. Exclusion criteria included signs of infection at the time of presentation, minor injuries not requiring intervention, bite wounds, one-time intravenous antibiotic administration without oral course, and surgical intervention. Outcomes included infection and interventions at follow-up. Chi-square analysis was performed, comparing antibiotic and no-antibiotic groups. A stepwise binomial regression was used to evaluate for variables predictive of antibiotic prescription.

Results

We identified eight infections in 323 patients included in the study (2.5% incidence of infection). There was no statistically significant difference in the incidence of infection between patients treated with antibiotics (2.7%) and those who did not receive antibiotics (2.2%). However, due to the low incidence of infections, we were likely underpowered for this analysis. We also created a model to predict antibiotic prescribing, which achieved an area under the receiver operating characteristic curve of 0.86 (P < .0001) based on age, bleeding disorders, depressive disorders, open wound status, amputation, fractures, and encounter type.

Conclusions

The low incidence of infection (2.5%) and lack of a meaningful difference between the groups call into question prophylactic antibiotic prescribing after these distal fingertip injuries. Our model does predict provider prescribing habits, identifying areas for potential practice pattern change.

Type of study/level of evidence

Therapeutic III.

Predicting Hospital Readmissions After Total Shoulder Arthroplasty Within a Bundled Payment Cohort

INTRODUCTION

Given the rising demand for shoulder arthroplasty, understanding risk factors associated with unplanned hospital readmission is imperative. No study to date has examined the influence of patient and hospital-specific factors as a predictive model for 90-day readmissions within a bundled payment cohort after primary shoulder arthroplasty. The purpose of this study was to determine predictive factors for 90-day readmissions after primary shoulder arthroplasty within a bundled payment cohort.

METHODS

After obtaining IRB approval, a retrospective review of a consecutive series of Medicare patients undergoing primary shoulder arthroplasty from 2014 to 2020 at a single academic institution was conducted. Patient demographic data, surgical variables, medical comorbidity profiles, medical risk scores, and social risk scores were collected. Postoperative variables included length of hospital stay, discharge location, and 90-day readmissions. Multivariate analysis was conducted to determine the independent risk factors of 90-day readmission.

RESULTS

Overall, 3.6% of primary shoulder arthroplasty patients (127/3,523) were readmitted within 90 days. Readmitted patients had a longer hospital course (1.75 versus 1.45 P = 0.006), higher comorbidity profile (4.64 versus 4.24 P = 0.001), higher social risk score (7.96 versus 6.9 P = 0.008), and higher medical risk score (10.1 versus 6.96 P < 0.001) and were more likely to require a home health aide or be discharged to an inpatient rehab facility or skilled nursing facility ( P = 0.002). Following multivariate analysis, an elevated medical risk score was associated with an increased risk of readmission (odds ratio = 1.05, P < 0.001).

DISCUSSION

This study demonstrates medical risk scores to be an independent risk factor of increased risk of 90-day hospital readmissions after primary shoulder arthroplasty within a bundled payment patient population. Additional incorporation of medical risk scores may be a beneficial adjunct in preoperative prediction for readmission and the potentially higher episode-of-care costs.

LEVEL OF EVIDENCE

Level III, retrospective cohort.

Validation of a Predictive Tool for Discharge to Rehabilitation or a Skilled Nursing Facility After TJA

BACKGROUND

Cost excess in bundled payment models for total joint arthroplasty (TJA) is driven by discharge to rehabilitation or a skilled nursing facility (SNF). A recently published preoperative risk prediction tool showed very good internal accuracy in stratifying patients on the basis of likelihood of discharge to an SNF or rehabilitation. The purpose of the present study was to test the accuracy of this predictive tool through external validation with use of a large cohort from an outside institution.

METHODS

A total of 20,294 primary unilateral total hip (48%) and knee (52%) arthroplasty cases at a tertiary health system were extracted from the institutional electronic medical record. Discharge location and the 9 preoperative variables required by the predictive model were collected. All cases were run through the model to generate risk scores for those patients, which were compared with the actual discharge locations to evaluate the cutoff originally proposed in the derivation paper. The proportion of correct classifications at this threshold was evaluated, as well as the sensitivity, specificity, positive and negative predictive values, number needed to screen, and area under the receiver operating characteristic curve (AUC), in order to determine the predictive accuracy of the model.

RESULTS

A total of 3,147 (15.5%) of the patients who underwent primary, unilateral total hip or knee arthroplasty were discharged to rehabilitation or an SNF. Despite considerable differences between the present and original model derivation cohorts, predicted scores demonstrated very good accuracy (AUC, 0.734; 95% confidence interval, 0.725 to 0.744). The threshold simultaneously maximizing sensitivity and specificity was 0.1745 (sensitivity, 0.672; specificity, 0.679), essentially identical to the proposed cutoff of the original paper (0.178). The proportion of correct classifications was 0.679. Positive and negative predictive values (0.277 and 0.919, respectively) were substantially better than those of random selection based only on event prevalence (0.155 and 0.845), and the number needed to screen was 3.6 (random selection, 6.4).

CONCLUSIONS

A previously published online predictive tool for discharge to rehabilitation or an SNF performed well under external validation, demonstrating a positive predictive value 79% higher and number needed to screen 56% lower than simple random selection. This tool consists of exclusively preoperative parameters that are easily collected. Based on a successful external validation, this tool merits consideration for clinical implementation because of its value for patient counseling, preoperative optimization, and discharge planning.

LEVEL OF EVIDENCE

Prognostic Level III . See Instructions for Authors for a complete description of levels of evidence.

Application and the Effect of the Triple Prerehabilitation Nursing Model in the Perioperative Period of Knee Arthroplasty in Diabetic Patients

Objective

The aim of the study was to explore the application and the effect of the triple prerehabilitation nursing model in the perioperative period of knee arthroplasty in diabetic patients.

Methods

The prospectively included 60 patients with diabetes who underwent total knee replacement were admitted from August 2021 to April 2022 and were divided into 2 groups according to the (1 : 1) ratio. The control group was mainly given routine nursing care. On the basis of the control group, the observation group received triple prerehabilitation nursing. The postoperative knee flexion, hospital for the special surgery knee score (HSS), the daily living ability (Barthel) score, the modified fall efficacy scale (MFES) score, the recovery of the lower-limb muscle strength, and the incidence of complications were compared between the two groups.

Results

The knee flexion degree and lower-limb muscle recovery of the observation group were better than those of the control group at 3 d, 7 d, and 14 d after operation (P < 0.05). The HSS score, Barthel score, and MFES score of the observation group were higher than those of the control group (P < 0.05). There was no significant difference in postoperative complications between the two groups (P > 0.05).

Conclusion

The triple prerehabilitation nursing care for diabetic patients undergoing total knee replacement can promote the recovery of limb function.

Enhanced Preoperative Education Pathways: A Step Toward Reducing Disparities in Total Joint Arthroplasty Outcomes

BACKGROUND

Patients with increased comorbidities, lower socioeconomic status, and African American (AA) race have been shown to be at increased risk for suboptimal outcomes after total joint arthroplasty (TJA). Despite the body of evidence highlighting these disparities, few interventions aimed at improving outcomes specifically in high-risk patients have been evaluated. This study evaluates the impact of an enhanced preoperative education pathway (EPrEP) on outcomes after TJA.

METHODS

All patients included underwent unilateral primary total hip or knee arthroplasty at a single institution from September 1, 2020 to September 31, 2021. This is a retrospective observational cohort study comparing demographics, comorbidities, and outcomes of patients treated through EPrEP with those receiving routine care. Subgroup analysis of outcome differences by race was performed.

RESULTS

In total, 1,716 patients were included in the study: 802 went through the EPrEP and 914 did not. EPrEP patients had a higher comorbidity burden as measured by the Charlson Comorbidity Index (3.54 ± 1.71 vs 3.25 ± 1.75, P < .001). After risk adjustment, there was no significant relationship among EPrEP utilization and length of stay, home discharge, or 30-day readmissions. However, EPrEP patients were less likely to return to the emergency department 30 days postoperatively (odds ratio 0.49, 95% confidence interval 0.27-0.86, P = .016). No significant differences in outcomes between AA and non-AA patients were observed.

CONCLUSION

High-risk patients receiving individualized nurse navigator counseling experienced similar outcomes to the broader patient population undergoing TJA. Implementation of EPrEPs may be an effective means of enhancing the equity of care quality across all patients undergoing TJA.

Artificial intelligence in knee arthroplasty: current concept of the available clinical applications

Background

Artificial intelligence (AI) is defined as the study of algorithms that allow machines to reason and perform cognitive functions such as problem-solving, objects, images, word recognition, and decision-making. This study aimed to review the published articles and the comprehensive clinical relevance of AI-based tools used before, during, and after knee arthroplasty.

Methods

The search was conducted through PubMed, EMBASE, and MEDLINE databases from 2000 to 2021 using the 2009 Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol (PRISMA).

Results

A total of 731 potential articles were reviewed, and 132 were included based on the inclusion criteria and exclusion criteria. Some steps of the knee arthroplasty procedure were assisted and improved by using AI-based tools. Before surgery, machine learning was used to aid surgeons in optimizing decision-making. During surgery, the robotic-assisted systems improved the accuracy of knee alignment, implant positioning, and ligamentous balance. After surgery, remote patient monitoring platforms helped to capture patients’ functional data.

Conclusion

In knee arthroplasty, the AI-based tools improve the decision-making process, surgical planning, accuracy, and repeatability of surgical procedures.

A validated preoperative risk prediction tool for discharge to skilled nursing or rehabilitation facility following anatomic or reverse shoulder arthroplasty

BACKGROUND

As bundled payment models continue to spread, understanding the primary drivers of cost excess helps providers avoid penalties and ensure equal health care access. Recent work has shown discharge to rehabilitation and skilled nursing facilities (SNFs) to be a primary cost driver in total joint arthroplasty, and an accurate preoperative risk calculator for shoulder arthroplasty would not only help counsel patients in clinic during shared decision-making conversations but also identify high-risk individuals who may benefit from preoperative optimization and discharge planning.

METHODS

Anatomic and reverse total shoulder arthroplasty cohorts from 2 geographically diverse, high-volume centers were reviewed, including 1773 cases from institution 1 (56% anatomic) and 3637 from institution 2 (50% anatomic). The predictive ability of a variety of candidate variables for discharge to SNF/rehabilitation was tested, including case type, sociodemographic factors, and the 30 Elixhauser comorbidities. Variables surviving parameter selection were incorporated into a multivariable logistic regression model built from institution 1's cohort, with accuracy then validated using institution 2's cohort.

RESULTS

A total of 485 (9%) shoulder arthroplasties overall were discharged to post-acute care (anatomic: 6%, reverse: 14%, P < .0001), and these patients had significantly higher rates of unplanned 90-day readmission (5% vs. 3%, P = .0492). Cases performed for preoperative fracture were more likely to require post-acute care (13% vs. 3%, P < .0001), whereas revision cases were not (10% vs. 10%, P = .8015). A multivariable logistic regression model derived from the institution 1 cohort demonstrated excellent preliminary accuracy (area under the receiver operating characteristic curve [AUC]: 0.87), requiring only 11 preoperative variables (in order of importance): age, marital status, fracture, neurologic disease, paralysis, American Society of Anesthesiologists physical status, gender, electrolyte disorder, chronic pulmonary disease, diabetes, and coagulation deficiency. This model performed exceptionally well during external validation using the institution 2 cohort (AUC: 0.84), and to facilitate convenient use was incorporated into a freely available, online prediction tool. A model built using the combined cohort demonstrated even higher accuracy (AUC: 0.89).

CONCLUSIONS

This validated preoperative clinical decision tool reaches excellent predictive accuracy for discharge to SNF/rehabilitation following shoulder arthroplasty, providing a vital tool for both patient counseling and preoperative discharge planning. Further, model parameters should form the basis for reimbursement legislation adjusting for patient comorbidities, ensuring no disparities in access arise for at-risk populations.

PLAN and AM-PAC "6-Clicks" Scores to Predict Discharge Disposition After Primary Total Hip and Knee Arthroplasty

BACKGROUND

Determination of the appropriate post-discharge disposition after total hip (THA) and knee (TKA) arthroplasty is a challenging multidisciplinary decision. Algorithms used to guide this decision have been administered both preoperatively and postoperatively. The purpose of this study was to simultaneously evaluate the predictive ability of 2 such tools-the preoperatively administered Predicting Location after Arthroplasty Nomogram (PLAN) and the postoperatively administered Activity Measure for Post-Acute Care (AM-PAC) "6-Clicks" basic mobility tools-in accurately determining discharge disposition after elective THA and TKA.

METHODS

The study included 11,672 patients who underwent THA (n = 4,923) or TKA (n = 6,749) at a single large hospital system from December 2016 through March 2020. PLAN and "6-Clicks" basic mobility scores were recorded for all patients. Regression models and receiver operator characteristic curves were constructed to evaluate the tools' prediction concordance with the actual discharge disposition (home compared with a facility).

RESULTS

PLAN scores had a concordance index of 0.723 for the THA cohort and 0.738 for the TKA cohort. The first "6-Clicks" mobility score (recorded within the first 48 hours postoperatively) had a concordance index of 0.813 for the THA cohort and 0.790 for the TKA cohort. When PLAN and first "6-Clicks" mobility scores were used together, a concordance index of 0.836 was observed for the THA cohort and 0.836 for the TKA cohort. When the PLAN and "6-Clicks" agreed on home discharge, higher rates of discharge to home (98.0% for THA and 97.7% for TKA) and lower readmission rates (5.1% for THA and 7.0% for TKA) were observed, compared with when the tools disagreed.

CONCLUSIONS

PLAN and "6-Clicks" basic mobility scores were good-to-excellent predictors of discharge disposition after primary total joint arthroplasty, suggesting that both preoperative and postoperative variables influence discharge disposition. We recommend that preoperative variables be collected and used to generate a tentative plan for discharge, and the final decision on discharge disposition be augmented by early postoperative evaluation.

CLINICAL RELEVANCE

The determination of post-discharge needs after THA and TKA remains a complex clinical decision. This study shows how simultaneously exploring the predictive ability of preoperative and postoperative assessment tools on discharge disposition after total joint arthroplasty may be a useful aid in a value-driven health-care model.

Characteristics and risk factors for 90-day readmission following shoulder arthroplasty

BACKGROUND

Anatomic total shoulder arthroplasty (TSA) and reverse TSA are the standard of care for end-stage shoulder arthritis. Advancements in implant design, perioperative management, and patient selection have allowed shorter inpatient admissions. Unplanned readmissions remain a significant complication. Identification of risk factors for readmission is prudent as physicians and payers prepare for the adoption of bundled care reimbursement models. The purpose of this study was to identify characteristics and risk factors associated with readmission following shoulder arthroplasty using a large, bi-institutional cohort.

METHODS

A total of 2805 anatomic TSAs and 2605 reverse TSAs drawn from 2 geographically diverse, tertiary health systems were examined for unplanned inpatient readmissions within 90 days following the index operation (primary outcome). Forty preoperative patient sociodemographic and comorbidity factors were tested for their significance using both univariable and multivariable logistic regression models, and backward stepwise elimination selected for the most important associations for 90-day readmission. Readmissions were characterized as either medical or surgical, and subgroup analysis was performed. A short length of stay (discharge by postoperative day 1) and discharge to a rehabilitation or skilled nursing facility were also examined as secondary outcomes. Parameters associated with increased readmission risk were included in a predictive model.

RESULTS

Within 90 days of surgery, 175 patients (3.2%) experienced an unanticipated readmission, with no significant difference between institutions (P = .447). There were more readmissions for surgical complications than for medical complications (62.9% vs. 37.1%, P < .001). Patients discharged to a rehabilitation or skilled nursing facility were significantly more likely to be readmitted (13.1% vs. 8.8%, P = .049), but a short inpatient length of stay was not associated with an increased rate of 90-day readmission (42.9% vs. 41.3%, P = .684). Parameter selection based on predictive ability resulted in a multivariable logistic regression model composed of 16 preoperative patient factors, including reverse TSA, revision surgery, right-sided surgery, and various comorbidities. The area under the receiver operator characteristic curve for this multivariable logistic regression model was 0.716.

CONCLUSION

Risk factors for unplanned 90-day readmission following shoulder arthroplasty include reverse shoulder arthroplasty, surgery for revision and fracture, and right-sided surgery. Additionally, there are several modifiable and nonmodifiable risk factors that can be used to ascertain a patient's readmission probability. A shorter inpatient stay is not associated with an increased risk of readmission, whereas discharge to post-acute care facilities does impose a greater risk of readmission. As scrutiny around health care cost increases, identifying and addressing risk factors for readmission following shoulder arthroplasty will become increasingly important.

Short stay after shoulder arthroplasty does not increase 90-day readmissions in Medicare patients compared with privately insured patients

BACKGROUND

As of January 1, 2021, total shoulder arthroplasty was removed from the Medicare inpatient-only list, reflecting a growing belief in the potential merits of same-day discharge regardless of insurance type. It is yet unknown whether Medicare populations, which frequently have more severe comorbidity burdens, would experience higher complication rates relative to privately insured patients, who are often younger with fewer comorbidities. Given the limited number of true outpatient cohorts available to study, discharge at least by postoperative day 1 may serve as a useful proxy for true same-day discharge, and we hypothesized that these Medicare patients would have increased 90-day readmission rates compared with their privately insured counterparts.

METHODS

Data on 4723 total shoulder arthroplasties (anatomic in 2459 and reverse in 2264) from 2 large, geographically diverse health systems in patients having either Medicare or private insurance were collected. The unplanned 90-day readmission rate was the primary outcome, and patients were stratified into those who were discharged at least by postoperative day 1 (short inpatient stay) and those who were not. Patients with private insurance (n = 1845) were directly compared with those with Medicare (n = 2878), whereas cohorts of workers' compensation (n = 198) and Medicaid (n = 58) patients were analyzed separately. Forty preoperative variables were examined to compare overall health burden, with the χ² and Wilcoxon rank sum tests used to test for statistical significance.

RESULTS

Medicare patients undergoing short-stay shoulder arthroplasty were not significantly more likely than those with private insurance to experience an unplanned 90-day readmission (3.6% vs. 2.5%, P = .14). This similarity existed despite a substantially worse comorbidity burden in the Medicare population (P < .05 for 26 of 40 factors). Furthermore, a short inpatient stay did not result in an increased 90-day readmission rate in either Medicare patients (3.6% vs. 3.4%, P = .77) or their privately insured counterparts (2.5% vs. 2.4%, P = .92). Notably, when the analysis was restricted to a single insurance type, readmission rates were significantly higher for reverse shoulder arthroplasty compared with total shoulder arthroplasty (P < .001 for both), but when the analysis was restricted to a single procedure (anatomic or reverse), readmission rates were similar between Medicare and privately insured patients, whether undergoing a short or extended length of stay.

CONCLUSIONS

Despite a substantially more severe comorbidity profile, Medicare patients undergoing short-stay shoulder arthroplasty did not experience a significantly higher rate of unplanned 90-day readmission relative to privately insured patients. A higher incidence of reverse shoulder arthroplasty in Medicare patients does increase their overall readmission rate, but a similar increase also appears in privately-insured patients undergoing a reverse indicating that Medicare populations may be similarly appropriate for accelerated-care pathways.