Postacute Care Readmission and Resource Utilization in Patients From Socioeconomically Distressed Communities After Total Joint Arthroplasty.

Racial and socioeconomic disparities have been associated with complications and poorer patient-reported outcomes after THA and TKA, but little is known regarding the variation of postacute care resource utilization based on socioeconomic difference in the communities in which patients reside. Hip and knee arthroplasty are among the most common elective orthopaedic procedures. Therefore, understanding social factors provides insight into patients at risk for readmission and the way in which these patients use other postoperative resources. This knowledge can help surgeons better understand which patients are at risk for complications or preventable readmissions and how to anticipate when additional surveillance or intervention might reduce this risk. (1) Do patients from communities with a higher distress level experience higher rates of readmission after THA and TKA? (2) Do patients from distressed communities have increased postoperative resource utilization? Demographics, ZIP code of residence, and Charlson comorbidity index (CCI) were recorded for each patient undergoing TKA or THA between 2016 and 2019 at two high-volume hospitals. Patients were classified according to the Distressed Communities Index (DCI) score of their ZIP code of residence. The DCI combines seven metrics of socioeconomic well-being (high school graduation, poverty rate, unemployment, housing vacancy, household income, change in employment, and change in establishment) to create a single score. ZIP codes are then classified by scores into five categories based on national quintiles (prosperous, comfortable, mid-tier, at-risk, and distressed). The DCI was chosen because it provides a single composite measure of multiple important socioeconomic factors. Multivariate analysis with logistic, negative binomial regression, or Poisson was used to investigate the association of DCI category with postoperative resource utilization while controlling forage, gender, BMI, and comorbidities. The primary outcome was 90-day readmissions. Secondary outcomes included postoperative medication prescriptions from the orthopaedic team, patient telephone calls to the surgeon's office, physical therapy sessions attended, follow-up office visits, and emergency department visits. A total of 5077 patients who underwent TKA (mean age 66 ± 9 years, 59% [2983 of 5077] are women, and 69% [3519 of 5077] are White), and 5299 who underwent THA (mean age 63 ± 11 years, 50% [2654 of 5299] are women, and 74% [3903 of 5299] are White) were included. When adjusting for age, gender, race and CCI, readmission risk was higher in distressed communities compared with prosperous communities for patients undergoing TKA (odds ratio 1.6 [95% confidence interval 1.1 to 2.3]; p = 0.02) but not for THA. For secondary outcomes after TKA, at-risk communities had more postoperative prescriptions compared with prosperous communities, but no other differences were found. After THA, no major differences were found in the likelihood to utilize postoperative resources based on DCI category. Race was not associated with readmissions or resource utilization. We found that socioeconomic distress was associated with readmission after TKA, but, after controlling for relevant confounding variables, race had no association. Patients from these communities do not demonstrate an increased or decreased use of other resources after post-TKA discharge. Increased awareness of these disparities may allow for closer monitoring and improved patient education and communication, with the goal of reducing the frequency of complications and preventable readmissions. Level III, therapeutic study.

Magnuson JA ，Griffin SA ，Venkat N ，Gold PA ，Courtney PM ，Krueger CA ... -  《-》

Racial Disparities in Outcomes After THA and TKA Are Substantially Mediated by Socioeconomic Disadvantage Both in Black and White Patients.

Demographic factors have been implicated in THA and TKA outcome disparities. Specifically, patients' racial backgrounds have been reported to influence outcomes after surgery, including length of stay, discharge disposition, and inpatient readmissions. However, in the United States, health-impacting socioeconomic disadvantage is sometimes associated with racial differences in ways that can result in important confounding, thereby raising the question of whether race-associated post-THA/TKA adverse outcomes are an independent function of race or a byproduct of confounding from socioeconomic deprivation, which is potentially addressable. To explore this, we used the Area Deprivation Index (ADI) as a proxy for socioeconomic disadvantage, since it is a socioeconomic parameter that estimates the likely deprivation associated with a patient's home address. The goal of this study was to investigate (1) whether race (in this study, Black versus White) was independently associated with adverse outcomes, including prolonged length of stay (LOS > 3 days), nonhome discharge, 90-day readmission, and emergency department (ED) visits while controlling for age, gender, BMI, smoking, Charlson comorbidity index (CCI), and insurance; and (2) whether socioeconomic disadvantage, measured by ADI, substantially mediated any association between race and any of the aforementioned measured outcomes. Between November 2018 and December 2019, 2638 underwent elective primary THA and 4915 patients underwent elective primary TKA for osteoarthritis at one of seven hospitals within a single academic center. Overall, 12% (742 of 5948) of patients were Black and 88% (5206 of 5948) were White. We included patients with complete demographic data, ADI data, and who were of Black or White race; with these criteria, 11% (293 of 2638) were excluded in the THA group, and 27% (1312 of 4915) of patients were excluded in the TKA group. In this retrospective, comparative study, patient follow-up was obtained using a longitudinally maintained database, leaving 89% (2345 of 2638) and 73% (3603 of 4915) for analysis in the THA and TKA groups, respectively. For both THA and TKA, Black patients had higher ADI scores, slightly higher BMIs, and were more likely to be current smokers at baseline. Furthermore, within the TKA cohort there was a higher proportion of Black women compared with White women. Multivariable regression analysis was utilized to assess associations between race and LOS of 3 or more days, nonhome discharge disposition, 90-day inpatient readmission, and 90-day ED admission, while adjusting for age, gender, BMI, smoking, CCI, and insurance. This was followed by a mediation analysis that explored whether the association between race (the independent variable) and measured outcomes (the dependent variables) could be partially or completely attributable to confounding from the ADI (the mediator, in this model). The mediation effect was measured as a percentage of the total effect of race on the outcomes of interest that was mediated by ADI. In the THA group, after adjusting for age, gender, BMI, smoking, CCI, and insurance, White patients had lower odds of experiencing an LOS of 3 days or more (OR 0.43 [95% confidence interval (CI) 0.31 to 0.59]; p < 0.001) and nonhome discharge (OR 0.39 [95% CI 0.27 to 0.56]; p < 0.001). In mediation analysis, ADI partially explained (or mediated) 37% of the association between race and LOS of 3 days or more (-0.043 [95% CI -0.063 to -0.026]; p < 0.001) and 40% of the association between race and nonhome discharge (0.041 [95% CI 0.024 to 0.059]; p < 0.001). However, a smaller direct association between race and both outcomes was observed (LOS 3 days or more: -0.075 [95% CI -0.13 to -0.024]; p = 0.004; nonhome discharge: 0.060 [95% CI 0.016 to 0.11]; p = 0.004). No association was observed between race and 90-day readmission or ED admission in the THA group. In the TKA group, after adjusting for age, gender, BMI, smoking, CCI, and insurance, White patients had lower odds of experiencing an LOS of 3 days or more (OR 0.41 [95% CI 0.32 to 0.54]; p < 0.001), nonhome discharge (OR 0.44 [95% CI 0.33 to 0.60]; p < 0.001), 90-day readmission (OR 0.54 [95% CI 0.39 to 0.77]; p < 0.001), and 90-day ED admission (OR 0.60 [95% CI 0.45 to 0.79]; p < 0.001). In mediation analysis, ADI mediated 19% of the association between race and LOS of 3 days or more (-0.021 [95% CI -0.035 to -0.007]; p = 0.004) and 38% of the association between race and nonhome discharge (0.029 [95% CI -0.016 to 0.040]; p < 0.001), but there was also a direct association between race and these outcomes (LOS 3 days or more: -0.088 [95% CI -0.13 to -0.049]; p < 0.001; nonhome discharge: 0.046 [95% CI 0.014 to 0.078]; p = 0.006). ADI did not mediate the associations observed between race and 90-day readmission and ED admission in the TKA group. Our findings suggest that socioeconomic disadvantage may be implicated in a substantial proportion of the previously assumed race-driven disparity in healthcare utilization parameters after primary total joint arthroplasty. Orthopaedic surgeons should attempt to identify potentially modifiable socioeconomic disadvantage indicators. This serves as a call to action for the orthopaedic community to consider specific interventions to support patients from vulnerable areas or whose incomes are lower, such as supporting applications for nonemergent medical transportation or referring patients to local care coordination agencies. Future studies should seek to identify which specific resources or approaches improve outcomes after TJA in patients with socioeconomic disadvantage. Level III, therapeutic study.

Hadad MJ ，Rullán-Oliver P ，Grits D ，Zhang C ，Emara AK ，Molloy RM ，Klika AK ，Piuzzi NS ... -  《-》

Distressed communities demonstrate increased readmission and health care utilization following shoulder arthroplasty.

Socioeconomic status (SES) has been shown to affect outcomes following total shoulder arthroplasty (TSA), but little is known regarding how SES and the communities in which patients reside can affect postoperative health care utilization. With the growing use of bundled payment models, understanding what factors put patients at risk for readmission and the ways in which patients utilize the health care system postoperatively is crucial for preventing excess costs for providers. This study helps surgeons predict which patients are high-risk and may require additional surveillance following shoulder arthroplasty. A retrospective review of 6170 patients undergoing primary shoulder arthroplasty (anatomic and reverse; Current Procedural Terminology code 23472) from 2014-2020 at a single academic institution was performed. Exclusion criteria included arthroplasty for fracture, active malignancy, and revision arthroplasty. Demographics, patient zip code, and Charlson Comorbidity Index were attained. Patients were classified according to the Distressed Communities Index (DCI) score of their zip code. The DCI combines several metrics of socioeconomic well-being to generate a single score. Zip codes are then classified by scores into 5 categories based on national quintiles. The primary outcome of interest was 90-day readmissions. Secondary outcomes included number of postoperative medication prescriptions, patient telephone calls to the office, and follow-up office visits. Among all patients undergoing total shoulder arthroplasty, individuals from distressed communities were more likely than their prosperous counterparts to experience an unplanned readmission (odds ratio = 1.77, P = .045). Patients from comfortable (relative risk [RR] = 1.12, P < .001), midtier (RR = 1.13, P < .001), at-risk (RR = 1.20, P < .001), and distressed (RR = 1.17, P < .001) communities were all more likely to use more medications compared to those from prosperous communities. Likewise, those from comfortable (RR = 0.92, P < .001), midtier (RR = 0.88, P < .001), at-risk (RR = 0.93, P = .008), and distressed (RR = 0.93, P = .033) communities, respectively, were at a lower risk of making calls compared to prosperous communities. Following primary total shoulder arthroplasty, patients who reside in distressed communities are at significantly increased risk of experiencing an unplanned readmission and increased health care utilization postoperatively. This study revealed that patient socioeconomic distress is more associated with readmission than race following TSA. Increased awareness and employing strategies to maintain and ultimately improve communication with patients offers a potential solution to reduce excessive health care utilization, benefiting both patients and providers alike.

Farronato DM ，Pezzulo JD ，Rondon AJ ，Sherman MB ，Davis DE ... -  《-》

Are Neighborhood Characteristics Associated With Outcomes After THA and TKA? Findings From a Large Healthcare System Database.

Non-White patients have higher rates of discharge to an extended care facility, hospital readmission, and emergency department use after primary THA and TKA. The reasons for this are unknown. Place of residence, which can vary by race, has been linked to poorer healthcare outcomes for people with many health conditions. However, the potential relationship between place of residence and disparities in these joint arthroplasty outcomes is unclear. (1) Are neighborhood-level characteristics, including racial composition, marital proportions, residential vacancy, educational attainment, employment proportions, overall deprivation, access to medical care, and rurality associated with an increased risk of discharge to a facility, readmission, and emergency department use after elective THA and TKA? (2) Are the associations between neighborhood-level characteristics and discharge to a facility, readmission, and emergency department use the same among White and Black patients undergoing elective THA and TKA? Between 2007 and 2018, 34,008 records of elective primary THA or TKA for osteoarthritis, rheumatoid arthritis, or avascular necrosis in a regional healthcare system were identified. After exclusions for unicompartmental arthroplasty, bilateral surgery, concomitant procedures, inability to geocode a residential address, duplicate records, and deaths, 21,689 patients remained. Ninety-seven percent of patients in this cohort self-identified as either White or Black, so the remaining 659 patients were excluded due to small sample size. This left 21,030 total patients for analysis. Discharge destination, readmissions within 90 days of surgery, and emergency department visits within 90 days were identified. Each patient's street address was linked to neighborhood characteristics from the American Community Survey and Area Deprivation Index. A multilevel, multivariable logistic regression analysis was used to model each outcome of interest, controlling for clinical and individual sociodemographic factors and allowing for clustering at the neighborhood level. The models were then duplicated with the addition of neighborhood characteristics to determine the association between neighborhood-level factors and each outcome. The linear predictors from each of these models were used to determine the predicted risk of each outcome, with and without neighborhood characteristics, and divided into tenths. The change in predicted risk tenths based on the model containing neighborhood characteristics was compared to that without neighborhood characteristics.The change in predicted risk tenth for each outcome was stratified by race. After controlling for age, sex, insurance type, surgery type, and comorbidities, we found that an increase of one SD of neighborhood unemployment (odds ratio 1.26 [95% confidence interval 1.17 to 1.36]; p < 0.001) was associated with an increased likelihood of discharge to a facility, whereas an increase of one SD in proportions of residents receiving public assistance (OR 0.92 [95% CI 0.86 to 0.98]; p = 0.008), living below the poverty level (OR 0.82 [95% CI 0.74 to 0.91]; p < 0.001), and being married (OR 0.80 [95% CI 0.71 to 0.89]; p < 0.001) was associated with a decreased likelihood of discharge to a facility. Residence in areas one SD above mean neighborhood unemployment (OR 1.12 [95% CI [1.04 to 1.21]; p = 0.002) was associated with increased rates of readmission. An increase of one SD in residents receiving food stamps (OR 0.83 [95% CI 0.75 to 093]; p = 0.001), being married (OR 0.89 [95% CI 0.80 to 0.99]; p = 0.03), and being older than 65 years (OR 0.93 [95% CI 0.88 to 0.98]; p = 0.01) was associated with a decreased likelihood of readmission. A one SD increase in the percentage of Black residents (OR 1.11 [95% CI 1.00 to 1.22]; p = 0.04) and unemployed residents (OR 1.15 [95% CI 1.05 to 1.26]; p = 0.003) was associated with a higher likelihood of emergency department use. Living in a medically underserved area (OR 0.82 [95% CI 0.68 to 0.97]; p = 0.02), a neighborhood one SD above the mean of individuals using food stamps (OR 0.81 [95% CI 0.70 to 0.93]; p = 0.004), and a neighborhood with an increasing percentage of individuals older than 65 years (OR 0.90 [95% CI 0.83 to 0.96]; p = 0.002) were associated with a lower likelihood of emergency department use. With the addition of neighborhood characteristics, the risk prediction tenths of the overall cohort remained the same in more than 50% of patients for all three outcomes of interest. When stratified by race, neighborhood characteristics increased the predicted risk for 55% of Black patients for readmission compared with 17% of White patients (p < 0.001). The predicted risk tenth increased for 60% of Black patients for emergency department use compared with 21% for White patients (p < 0.001). These results can be used to identify high-risk patients who might benefit from preemptive interventions to avoid these particular outcomes and to create more realistic, comprehensive risk adjustment models for value-based care programs. Additionally, this study demonstrates that neighborhood characteristics are associated with greater risk for these outcomes among Black patients compared with White patients. Further studies should consider that race/ethnicity and neighborhood characteristics may not function independently from each other. Understanding this link between race and place of residence is essential for future racial disparities research. Level III, therapeutic study.

Adelani MA ，Marx CM ，Humble S 《-》

Which Clinical and Patient Factors Influence the National Economic Burden of Hospital Readmissions After Total Joint Arthroplasty?

Kurtz SM ，Lau EC ，Ong KL ，Adler EM ，Kolisek FR ，Manley MT ... -  《-》