Racial and sex disparities in utilization rates for shoulder arthroplasty in the United States disparities in shoulder arthroplasty

Racial and ethnic disparities in short-stay primary total shoulder arthroplasty

Background

There is a paucity of literature evaluating the utilization of short-stay total shoulder arthroplasty (TSA) in different racial groups. The purpose of this study is to compare short-stay TSA utilization and postoperative outcomes across racial groups.

Methods

The National Surgical Quality Improvement Program (NSQIP) database was queried from 2010 to 2018 to identify patients who underwent primary short-stay TSA, defined as a length of stay of less than 2 midnights. Annual proportions of short-stay TSA, demographic variables, preoperative comorbidities, and postoperative complications were compared across groups.

Results

All racial groups showed increases in the proportion of short-stay TSA cases over time, but this increase was most evident in Whites. Hispanics had increased rates of pneumonia (0.8% vs. 0.2%; p = 0.002) and transfusion (2.0% vs 1.0%; p = 0.015) compared to Whites, but no other differences in outcomes were observed between groups.

Discussion

Postoperative outcomes were similar across groups despite differing comorbidity profiles, suggesting that short-stay TSA is being implemented appropriately based on perceived preoperative risk. However, differences in utilization across groups suggest that underlying disparities may exist. Given the continued increase in short-stay TSA procedures, opportunities to resolve racial disparities are essential in mitigating the effects of social determinants of health in minority patient groups.

Racial and gender disparities in utilization of outpatient total shoulder arthroplasties

BACKGROUND

Utilization in outpatient total shoulder arthroplasties (TSAs) has increased significantly in recent years. It remains largely unknown whether utilization of outpatient TSA differs across gender and racial groups. This study aimed to quantify racial and gender disparities both nationally and by geographic regions.

METHODS

168,504 TSAs were identified using Medicare fee-for-service inpatient and outpatient claims data and beneficiary enrollment data from 2020 to 2022Q4. The percentage of outpatient cases, defined as cases discharged on the same day of surgery, was evaluated by racial and gender groups and by different census divisions. A multivariate logistics regression model controlling for patient sociodemographic information (White vs. non-White race, age, gender, and dual eligibility for both Medicare and Medicaid), hierarchical condition category (HCC) score, hospital characteristics, year fixed effects, and patient residency state fixed effects was performed.

RESULTS

The TSA volume per 1000 beneficiaries was 2.3 for the White population compared with 0.8, 0.6, and 0.3 for the Black, Hispanic, and Asian population, respectively. A higher percentage of outpatient TSAs were in White patients (25.6%) compared with Black patients (20.4%) (P < .001). The Black TSA patients were also younger, more likely to be female, more likely to be dually eligible for Medicaid, and had higher HCC risk scores. After controlling for patient sociodemographic characteristics and hospital characteristics, the odds of receiving outpatient TSAs were 30% less for Black than the White group (odds ratio 0.70). Variations were observed across different census divisions, with South Atlantic (0.67, P < .01), East North Central (0.56, P < .001), and Middle Atlantic (0.36, P < .01) being the 4 regions observed with significant racial disparities. Statistically significant gender disparities were also found nationally and across regions, with an overall odds ratio of 0.75 (P < .001).

DISCUSSION

Statistically significant racial and gender disparities were found nationally in outpatient TSAs, with Black patients having 30% (P < .001) fewer odds of receiving outpatient TSAs than White patients, and female patients with 25% (P < .001) fewer odds than male patients. Racial and gender disparities continue to be an issue for shoulder arthroplasties after the adoption of outpatient TSAs.

The impact of social deprivation on healthcare utilization patterns following rotator cuff repair

BACKGROUND

Disparities in social determinants of health have been linked to worse patient reported outcomes, higher pain, and increased risk of revision surgery following rotator cuff repair. Identification of perioperative predictors of increased healthcare utilization is of particular interest to surgeons to improve outcomes and mitigate the total cost of care. The effect of social deprivation on healthcare utilization has not been fully characterized.

METHODS

This is a retrospective review of a single institution's experience with primary rotator cuff repair between 2012 and 2020. Demographic variables (age, race, gender, American Society of Anesthesiologists (ASA) score) and healthcare utilization (hospital readmission, emergency department visits, follow-up visits, telephone calls) were recorded within 90 days of surgery. The Area Deprivation Index (ADI) was recorded, and patients were separated into terciles according to their relative level of social deprivation. Outcomes were then stratified based on ADI tercile and compared.

RESULTS

A total of 1695 patients were included. The upper, middle, and lower terciles of ADI consisted of 410, 767, and 518 patients, respectively. The most deprived tercile had greater emergency department visitation and office visitation within 90 days of surgery relative to the least and intermediate deprived terciles. Higher levels of social deprivation were independent risk factors for increased emergency department (ED) visitation and follow-up visitation. There was no difference in 90-day readmission rates or telephone calls made between the least, intermediate, and most deprived patients.

CONCLUSIONS

Patients with higher levels of deprivation demonstrated greater postoperative hospital utilization. We hope to use these results to identify risk factors for increased hospital use, guide clinical decision making, increase transparency, and manage patient outcomes following rotator cuff repair surgery.

Racial and Ethnic Disparities in Predictive Accuracy of Machine Learning Algorithms Developed Using a National Database for 30-Day Complications Following Total Joint Arthroplasty

BACKGROUND

While predictive capabilities of machine learning (ML) algorithms for hip and knee total joint arthroplasty (TJA) have been demonstrated in previous studies, their performance in racial and ethnic minority patients has not been investigated. This study aimed to assess the performance of ML algorithms in predicting 30-days complications following TJA in racial and ethnic minority patients.

METHODS

A total of 267,194 patients undergoing primary TJA between 2013 and 2020 were identified from a national outcomes database. The patient cohort was stratified according to race, with further substratification into Hispanic or non-Hispanic ethnicity. There were two ML algorithms, histogram-based gradient boosting (HGB), and random forest (RF), that were modeled to predict 30-days complications following primary TJA in the overall population. They were subsequently assessed in each racial and ethnic subcohort using discrimination, calibration, accuracy, and potential clinical usefulness.

RESULTS

Both models achieved excellent (Area under the curve (AUC) > 0.8) discrimination (AUCHGB = AUCRF = 0.86), calibration, and accuracy (HGB: slope = 1.00, intercept = -0.03, Brier score = 0.12; RF: slope = 0.97, intercept = 0.02, Brier score = 0.12) in the non-Hispanic White population (N = 224,073). Discrimination decreased in the White Hispanic (N = 10,429; AUC = 0.75 to 0.76), Black (N = 25,116; AUC = 0.77), Black Hispanic (N = 240; AUC = 0.78), Asian non-Hispanic (N = 4,809; AUC = 0.78 to 0.79), and overall (N = 267,194; AUC = 0.75 to 0.76) cohorts, but remained well-calibrated. We noted the poorest model discrimination (N = 1,870; AUC = 0.67 to 0.68) and calibration in the American-Indian cohort.

CONCLUSIONS

The ML algorithms demonstrate an inferior predictive ability for 30-days complications following primary TJA in racial and ethnic minorities when trained on existing healthcare big data. This may be attributed to the disproportionate underrepresentation of minority groups within these databases, as demonstrated by the smaller sample sizes available to train the ML models. The ML models developed using smaller datasets (e.g., in racial and ethnic minorities) may not be as accurate as larger datasets, highlighting the need for equity-conscious model development.

LEVEL OF EVIDENCE

III; retrospective cohort study.

Randomized controlled trials in the shoulder arthroplasty literature rarely include key demographic and socioeconomic patient data

BACKGROUND

It is well known that socioeconomic and demographic variables can greatly affect health outcomes. Previous studies across medical and surgical subspecialties have demonstrated that these variables are frequently under-reported in randomized controlled trials (RCTs). No such study currently exists that examines rates of reporting of sociodemographic variables in shoulder arthroplasty RCTs. This study aims to present these rates and explore the impact of failing to report socioeconomic variables in shoulder arthroplasty RCTs.

METHODS

The PubMed database was queried for the term shoulder arthroplasty. Sixty-five RCTs from the past 10 years were identified for inclusion from 5 high-impact orthopedic surgery journals. Each RCT was analyzed for patient age and sex or gender as well as the following sociodemographic variables: race, ethnicity, insurance status, income, work status, and education. It was also noted whether each of the above variable was mentioned in the results section of the article. Data were presented in a descriptive fashion as well as analyzed using χ2 and Fisher exact tests where appropriate.

RESULTS

From 2014 to 2023, the 65 shoulder arthroplasty RCTs published reported age in 40 of 65 (61.5%) in their results sections and 61 of 65 (93.8%) in any section. Sex or gender was reported in 27 of 65 (41.5%) in their results sections and 61 of 65 (93.8%) in any section. No articles included any sociodemographic variables in the results section. Reporting rates for sociodemographic variables in any section were as follows: race, 6 of 65 (9.2%); ethnicity, 5 of 65 (7.7%); work status, 4 of 65 (6.2%); and insurance status, 1 of 65 (1.5%). No studies included income or education of the enrolled patients. There was no difference in reporting sociodemographic variables by journal (P = .45) or by year of publication (P = .57). However, no study prior to 2020 included any sociodemographic variable (0 of 27, 0%), whereas from 2020 onward 6 studies included at least 1 (6 of 38, 15.8%). Sociodemographic variables were reported significantly less frequently than age and sex or gender (P = .001).

DISCUSSION

Our study found sociodemographic variables are rarely reported in shoulder arthroplasty RCTs, whereas age and sex or gender are reported with great frequency. In order to understand the results of shoulder arthroplasty RCTs, apply their findings to the care of our patients, and address health disparities, we must ensure these studies include patient sociodemographic data.

Evaluating the fairness and accuracy of machine learning-based predictions of clinical outcomes after anatomic and reverse total shoulder arthroplasty

BACKGROUND

Machine learning (ML)-based clinical decision support tools (CDSTs) make personalized predictions for different treatments; by comparing predictions of multiple treatments, these tools can be used to optimize decision making for a particular patient. However, CDST prediction accuracy varies for different patients and also for different treatment options. If these differences are sufficiently large and consistent for a particular subcohort of patients, then that bias may result in those patients not receiving a particular treatment. Such level of bias would deem the CDST "unfair." The purpose of this study is to evaluate the "fairness" of ML CDST-based clinical outcomes predictions after anatomic (aTSA) and reverse total shoulder arthroplasty (rTSA) for patients of different demographic attributes.

METHODS

Clinical data from 8280 shoulder arthroplasty patients with 19,249 postoperative visits was used to evaluate the prediction fairness and accuracy associated with the following patient demographic attributes: ethnicity, sex, and age at the time of surgery. Performance of clinical outcome and range of motion regression predictions were quantified by the mean absolute error (MAE) and performance of minimal clinically important difference (MCID) and substantial clinical benefit classification predictions were quantified by accuracy, sensitivity, and the F1 score. Fairness of classification predictions leveraged the "four-fifths" legal guideline from the US Equal Employment Opportunity Commission and fairness of regression predictions leveraged established MCID thresholds associated with each outcome measure.

RESULTS

For both aTSA and rTSA clinical outcome predictions, only minor differences in MAE were observed between patients of different ethnicity, sex, and age. Evaluation of prediction fairness demonstrated that 0 of 486 MCID (0%) and only 3 of 486 substantial clinical benefit (0.6%) classification predictions were outside the 20% fairness boundary and only 14 of 972 (1.4%) regression predictions were outside of the MCID fairness boundary. Hispanic and Black patients were more likely to have ML predictions out of fairness tolerance for aTSA and rTSA. Additionally, patients <60 years old were more likely to have ML predictions out of fairness tolerance for rTSA. No disparate predictions were identified for sex and no disparate regression predictions were observed for forward elevation, internal rotation score, American Shoulder and Elbow Surgeons Standardized Shoulder Assessment Form score, or global shoulder function.

CONCLUSION

The ML algorithms analyzed in this study accurately predict clinical outcomes after aTSA and rTSA for patients of different ethnicity, sex, and age, where only 1.4% of regression predictions and only 0.3% of classification predictions were out of fairness tolerance using the proposed fairness evaluation method and acceptance criteria. Future work is required to externally validate these ML algorithms to ensure they are equally accurate for all legally protected patient groups.

Operative management of rotator cuff tears: identifying disparities in access on a national level

BACKGROUND

The purpose of this study was to identify nationwide disparities in the rates of operative management of rotator cuff tears based on race, ethnicity, insurance type, and socioeconomic status.

METHODS

Patients diagnosed with a full or partial rotator cuff tear from 2006 to 2014 were identified in the Healthcare Cost and Utilization Project's National Inpatient Sample database using International Classification of Diseases, Ninth Revision diagnosis codes. Bivariate analysis using chi-square tests and adjusted, multivariable logistic regression models were used to evaluate differences in the rates of operative vs. nonoperative management for rotator cuff tears.

RESULTS

This study included 46,167 patients. When compared with white patients, adjusted analysis showed that minority race and ethnicity were associated with lower rates of operative management for Black (adjusted odds ratio [AOR]: 0.31, 95% confidence interval [CI]: 0.29-0.33; P < .001), Hispanic (AOR: 0.49, 95% CI: 0.45-0.52; P < .001), Asian or Pacific Islander (AOR: 0.72, 95% CI: 0.61-0.84; P < .001), and Native American patients (AOR: 0.65, 95% CI: 0.50-0.86; P = .002). In comparison to privately insured patients, our analysis also found that self-payers (AOR: 0.08, 95% CI: 0.07-0.10; P < .001), Medicare beneficiaries (AOR: 0.76, 95% CI: 0.72-0.81; P < .001), and Medicaid beneficiaries (AOR: 0.33, 95% CI: 0.30-0.36; P < .001) had lower odds of receiving surgical intervention. Additionally, relative to those in the bottom income quartile, patients in all other quartiles experienced nominally higher rates of operative repair; these differences were statistically significant for the second quartile (AOR: 1.09, 95% CI: 1.03-1.16; P = .004).

CONCLUSION

There are significant nationwide disparities in the likelihood of receiving operative management for rotator cuff tear patients of differing race/ethnicity, payer status, and socioeconomic status. Further investigation is needed to fully understand and address causes of these discrepancies to optimize care pathways.

Social determinants of health and race are independent predictors of reduced rotator cuff surgery rates in the Medicare population

BACKGROUND

Racial disparities have been shown to influence rates of surgery for patients with rotator cuff disease. Some individuals have attributed adverse social determinants of health (SDOHs) as potential confounders of this relationship between race and surgery rate. However, there is a paucity of literature observing whether adverse SDOHs and race independently influence rotator cuff surgery rates. Therefore, the purpose of this study was to determine whether adverse SDOHs and race are independent predictors of rotator cuff surgery rates for Medicare beneficiaries.

METHODS

A retrospective analysis was conducting using the Medicare Standard Analytic Files (SAF) data set of the PearlDiver database, observing 211,340 patients with rotator cuff pathology. Univariate and multivariable regression analyses were performed to observe whether race and adverse SDOHs were independent variables associated with rotator cuff surgery rates. To determine whether adverse SDOHs significantly influenced racial disparities, stratified analyses of patients with ≥1 adverse SDOH and those without adverse SDOHs were conducted to compare the odds ratios (ORs) and 95% confidence intervals (CIs) of racial disparities.

RESULTS

Among patients with rotator cuff disease, 21,679 (10.26%) were of nonwhite race and 21,835 (10.33%) had ≥1 adverse SDOH. The variables of nonwhite race (OR, 0.622; 95% CI, 0.599-0.668; P < .001) and having ≥1 adverse SDOH (OR, 0.715; 95% CI, 0.501-0.814; P < .001) were independent predictors of not undergoing surgery. On stratified analysis, there was no significant difference in racial disparities in patients with ≥1 adverse SDOH (OR, 0.620; 95% CI, 0.440-0.875) and those without adverse SDOHs (0.635; 95% CI, 0.601-0.671) based on overlapping 95% CIs.

DISCUSSION

This study demonstrated that among Medicare beneficiaries, adverse SDOHs and race are independent predictors of lower rotator cuff surgery rates, emphasizing the need to address disparities based on race alone.

Hospital characteristics and perioperative complications of Hispanic patients following reverse shoulder arthroplasty-a large database study

BACKGROUND

Hispanic patients are the youngest and fastest-growing ethnic group in the USA. Many of these patients are increasingly met with orthopedic issues, often electing to undergo corrective procedures such as reverse shoulder arthroplasty (RSA). This patient population has unique medical needs and has been reported to have higher incidences of perioperative complications following major procedures. Unfortunately, there is a lack of information on the hospitalization data and perioperative complications in Hispanic patients following procedures such as RSA. This project aimed to query the Nationwide Inpatient Sample (NIS) database to assess patient hospitalization information, demographics, and the prevalence of perioperative complications among Hispanic patients who received RSA.

METHODS

Information from 2016-2019 was queried from the NIS database. Demographic information, incidences of perioperative complications, length of stay, and costs of care among Hispanic patients undergoing RSA were compared to non-Hispanic patients undergoing RSA. A subsequent propensity matching was conducted to consider preoperative comorbidities.

RESULTS

The query of NIS identified 59,916 patients who underwent RSA. Of this sample, 2,656 patients (4.4%) were identified to be Hispanic, while the remaining 57,260 patients (95.6%) were found to belong to other races (control). After propensity matching, Hispanic patients had a significantly longer LOS (median = 1.4 days) than the patients in the control group (median = 1.0, P < 0.001). The Hispanic patients (89,168.5 USD) had a significantly higher cost of care than those in the control group (67,396.1 USD, P < 0.001). In looking at postoperative complications, Hispanic patients had increased incidences of acute renal failure (Hispanics: 3.1%, control group: 1.1%, P = 0.03) and blood loss anemia (Hispanics: 12.7%, control group: 10.9%, P = 0.03).

CONCLUSIONS

Hispanic patients had significantly longer lengths of stay, higher costs of care, and higher rates of perioperative complications compared to the control group. For patients who are Hispanic and undergoing RSA, this information will aid doctors in making comprehensive decisions regarding patient care and resource allocation.

Disparities in postoperative total shoulder arthroplasty outcomes between Black and White patients

Background

Despite the rise in surgical volume for total shoulder arthroplasty (TSA) procedures, racial disparities exist in outcomes between White and Black populations. The purpose of this study was to compare 30-day postoperative complication rates between Black and White patients following TSA.

Methods

The American College of Surgeons National Surgical Quality Improvement Program (NSQIP) database was queried for all patients who underwent TSA between 2015 and 2019. Patient demographics and comorbidities were compared between cohorts using bivariate analysis. Multivariate logistic regression, adjusted for all significantly associated patient demographics and comorbidities, was used to identify associations between Black or African American race and postoperative complications.

Results

A total of 19,733 patients were included in the analysis, 18,669 (94.6%) patients in the White cohort and 1064 (5.4%) patients in the Black or African American cohort. Demographics and comorbidities that were significantly associated with Black or African American race were age 40-64 years (P < .001), body mass index ≥40 (P < .001), female gender (P < .001), American Society of Anesthesiologists classification ≥3 (P < .001), smoking status (P < .001), non-insulin and insulin dependent diabetes mellitus (P < .001), hypertension requiring medication (P < .001), disseminated cancer (P = .040), and operative duration ≥129 minutes (P = .002). Multivariate logistic regression identified Black or African American race to be independently associated with higher rates of readmission (odds ratio: 1.42, 95% confidence interval: 1.05-1.94; P = .025).

Conclusion

Black or African American race was independently associated with higher rates of 30-day readmission following TSA.

Influence of Race on Utilization and Outcomes in Shoulder Arthroplasty: A Systematic Review

BACKGROUND

Studies have shown that utilization and outcomes after shoulder arthroplasty vary by sociodemographic factors, highlighting disparities in care. This systematic review synthesized all available literature regarding the relationship between utilization and outcomes of shoulder arthroplasty and race/ethnicity.

METHODS

Studies were identified using PubMed, MEDLINE (through Ovid), and CINAHL databases. All English language studies of Level I through IV evidence that specifically evaluated utilization and/or outcomes of hemiarthroplasty, total shoulder arthroplasty, or reverse shoulder arthroplasty by race and/or ethnicity were included. Outcomes of interest included rates of utilization, readmission, reoperation, revision, and complications.

RESULTS

Twenty-eight studies met inclusion criteria. Since the 1990s, Black and Hispanic patients have demonstrated a lower utilization rate of shoulder arthroplasty compared with White patients. Although utilization has increased among all racial groups throughout the present decade, the rate of increase is greater for White patients. These differences persist in both low-volume and high-volume centers and are independent of insurance status. Compared with White patients, Black patients have a longer postoperative length of stay after shoulder arthroplasty, worse preoperative and postoperative range of motion, a higher likelihood of 90-day emergency department visits, and a higher rate of postoperative complications including venous thromboembolism, pulmonary embolism, myocardial infarction, acute renal failure, and sepsis. Patient-reported outcomes, including the American Shoulder and Elbow Surgeon's score, did not differ between Black and White patients. Hispanics had a significantly lower revision risk compared with White patients. One-year mortality did not differ significantly between Asians, Black patients, White patients, and Hispanics.

CONCLUSION

Shoulder arthroplasty utilization and outcomes vary by race and ethnicity. These differences may be partly due to patient factors such as cultural beliefs, preoperative pathology, and access to care, as well as provider factors such as cultural competence and knowledge of health care disparities.

LEVEL OF EVIDENCE

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

Wide Geographic Variation in Resource Utilization after Shoulder Arthroplasty

Background

There is growing interest in optimizing cost and resource utilization after shoulder arthroplasty, but little data to guide improvement efforts.

Objective

The purpose of this study was to evaluate geographic variation in length of stay and home discharge disposition after shoulder arthroplasty across the United States.

Methods

The Centers for Medicare and Medicaid Services database was used to identify Medicare discharges following shoulder arthroplasties performed from April 2019 through March 2020. National, regional (Northeast, Midwest, South, West), and state-level variation in length of stay and home discharge disposition rates were examined. The degree of variation was assessed using the coefficient of variation, with a value greater than 0.15 being considered as "substantial" variation. Geographic maps were created for visual representation of the data.

Results

There was substantial state-level variation in home discharge disposition rates (64% in Connecticut to 96% in West Virginia) and length of stay (1.01 days in Delaware to 1.86 days in Kansas). There was wide regional variation in length of stay (1.35 days in the West to 1.50 days in the Northeast) and home discharge disposition rates (73% in the Northeast to 85% in the West).

Conclusions

There is wide variation in resource utilization after shoulder arthroplasty across the United States. Certain patterns emerge from our data; for instance, the Northeast has the longest hospital stays with the lowest home discharge rates. This study provides important information for the implementation of targeted strategies to effectively reduce geographic variation in healthcare resource utilization.

A Novel Comorbidity Risk Score for Predicting Post-Operative 30-day Complications in Total Shoulder Arthroplasty & Elucidation of Potential Racial Disparities

Background

Efficient and effective preoperative identification of those patients with elevated risk may allow for more cost-effective interventions, accurate bundled payment adjustments, and overall improved patient care. Few comorbidity indices have provided clinical utility and adequate discriminative ability in the setting of complications after shoulder arthroplasty (SA).

Methods

The American College of Surgeons National Surgical Quality Improvement Program database was queried for anatomic and/or reverse SA procedures between 2010 and 2019. A subset of comorbidities were utilized including end-stage renal disease, history of hypertension, chronic obstructive pulmonary disease, functional status, history of bleeding disorder, and disseminated cancer.

Results

A total of 25,927 patients with an average age of 69.2 (standard deviation ±9.5) years were included in the study. Patients with a comorbidity risk score (CRS) at or above 2 were indicated to have at least a 29.6% 30-day postoperative complication rate after undergoing total shoulder arthroplasty, significantly higher than the described average of approximately 15%. The area under receiver operator curve for the novel CRS scoring system was 0.595, indicating fair discriminative ability to predict 30-day postoperative complications after SA. This illustrates a discriminative ability similar to that of the American Society of Anesthesiologists classification (0.584, confidence interval [CI] 0.578-0.589), modified Charlson Comorbidity Index (0.567, CI 0.561-0.573), and modified Frailty Index (0.534, CI 0.529-0.539), each of which are common comorbidity indices used for the National Surgical Quality Improvement Program database. The average CRS for the population was 0.8537 (CI 0.8011-0.8150; P < .05) while that for the Black demographic was 1.08 (CI 1.03-1.13; P < .001). Our results suggest that if the disparity in CRS among races was corrected, the average complication rate would be decreased by 2.0%.

Discussion and Conclusion

A higher CRS score resulted in higher rates of 30-day postoperative complications following SA. Black patients had a higher average CRS than all other races illustrating a racial disparity in comorbidity risk. Although the average complication rate of each race would still be unequal, this could mitigate some of the racial disparities observed and decrease the overall 30-day complication rate in SA. With the rise of bundled payments further increasing the need to preoperatively identify patients at high risk for costly complications, the CRS is based on easily identified, relevant comorbidities that may be an advantageous tool to identify patients at increased risk of complications following SA.

Clinical Fate of Glenohumeral Osteoarthritis Following Intraarticular Corticosteroid Injection: An Analysis in 311 Shoulders

Background

Intraarticular corticosteroid injection is commonly used conservative treatment for glenohumeral osteoarthritis (OA). The purpose of this study was to investigate the clinical fate of symptomatic glenohumeral OA following intraarticular corticosteroid injection and to identify factors associated with undergoing shoulder arthroplasty.

Methods

Glenohumeral OA patients who had undergone at least one glenohumeral corticosteroid injection from 2012 to 2017 were identified. Data for demographics, comorbidities, number of injections, severity of radiographic arthritis, and subsequent treatment were collected up to February 2020. Data were analyzed to compare between patients who had eventually undergone shoulder arthroplasty and those who had not.

Results

A total of 311 shoulders (275 patients) were followed up for 3 to 8 years after the index injection. The mean age of patients was 64.7 years. There were 148 females, and 116 shoulders (37.3%) eventually underwent arthroplasty, 68 (21.9%) further injections only, 104 (33.4%) no further treatment, 14 (4.5%) a non-arthroplasty surgical procedure, and 9 (2.9%) were lost to follow up. Severity of radiographic arthritic changes, female sex, younger age, and nonsmoking status were found to be significantly associated with undergoing arthroplasty (p < 0.001, p = 0.014, p = 0.003, and p = 0.043, respectively).

Conclusion

Approximately one third of glenohumeral OA patients who had received an intraarticular corticosteroid injection eventually elected to undergo shoulder arthroplasty within 3 to 8 years of the injection. High-grade arthritic changes in radiographs, female gender, and younger age were found to be independent factors associated with undergoing arthroplasty. This information may be useful in counseling patients about their future clinical course.

Level of Evidence: Level III Retrospective comparative study

Racial and Gender Shoulder Arthroplasty Utilization Disparities of High- and Low-Volume Centers in New York State

Introduction

The literature has consistently demonstrated utilization disparities in joint replacement procedures, though no studies have evaluated disparities in total shoulder arthroplasty with regard to operative volume.

Methods

We queried the New York (NY) Statewide Planning and Research Cooperative System (SPARCS) database for 32 410 total shoulder arthroplasties performed between 2009 and 2017. Patients were identified using Clinical Classifications Software code 154 for Non-Hip/Knee Arthroplasty and All Patient Refined-Diagnosis Related Group code 322 for Shoulder. Racial groups included Hispanic, non-Hispanic white, non-Hispanic black, and Other. High-volume centers were facilities that performed 2 standard deviations above the mean annual procedures. Utilization rates were calculated by dividing total shoulder arthroplasties per group by the 2010 NY Census population of that group. The Fisher exact test was used to determine significance.

Results

Total shoulder arthroplasty utilization increased from 43/100 000 to 73/100 000, two-thirds of which was driven by an increase in white resident utilization. More White residents per 100 000 underwent shoulder arthroplasty than Black, Hispanic, and Other residents per 100 000 residents of their respective race. White residents were 90% more likely than Hispanic residents to undergo total shoulder arthroplasty at high-volume centers (P = .04). There were no differences in utilization rate regarding operative volume comparing Black or Other residents to White residents. More females underwent total shoulder arthroplasty than males, though there was no difference in utilization rate regarding operative volume.

Conclusion

Though total shoulder arthroplasty utilization nearly doubled, disparities persisted across gender and minority groups particularly in Hispanic utilization as White residents were 90% more likely than Hispanic residents to undergo shoulder arthroplasty at high-volume centers.