No Differences Between White and Non-White Patients in Terms of Care Quality Metrics, Complications, and Death After Hip Fracture Surgery When Standardized Care Pathways Are Used.

Many initiatives by medical and public health communities at the national, state, and institutional level have been centered around understanding and analyzing critical determinants of population health with the goal of equitable and nondisparate care. In orthopaedic traumatology, several studies have demonstrated that race and socioeconomic status are associated with differences in care delivery and outcomes of patients with hip fractures. However, studies assessing the effectiveness of methods to address disparities in care delivery, quality metrics, and complications after hip fracture surgery are lacking. (1) Are hospital quality measures (such as delay to surgery, major inpatient complications, intensive care unit admission, and discharge disposition) and outcomes (such as mortality during inpatient stay, within 30 days or within 1 year) similar between White and non-White patients at a single institution in the setting of a standardized hip fracture pathway? (2) What factors correlate with aforementioned hospital quality measures and outcomes under the standardized care pathway? In this retrospective, comparative study, we evaluated the records of 1824 patients 55 years of age or older with hip fractures from a low-energy mechanism who were treated at one of four hospitals in our urban academic healthcare system, which includes an orthopaedic tertiary care hospital, from the initiation of a standardized care pathway in October 2014 to March 2020. The standardized 4-day hip fracture pathway is comprised of medicine comanagement of all patients and delineated tasks for doctors, nursing, social work, care managers, and physical and occupational therapy from admission to expected discharge on postoperative day 4. Of the 1824 patients, 98% (1787 of 1824) of patients who had their race recorded in the electronic medical record chart (either by communicating it to a medical provider or by selecting their race from options including White, Black, Hispanic, and Asian in a patient portal of the electronic medical record) were potentially eligible. A total of 14% (249 of 1787) of patients were excluded because they did not have an in-state address. Of the included patients, 5% (70 of 1538) were lost to follow-up at 30 days and 22% (336 of 1538) were lost to follow-up at 1 year. Two groups were established by including all patients selecting White as primary race into the White cohort and all other patients in the non-White cohort. There were 1111 White patients who were 72% (801) female with mean age 82 ± 10 years and 427 non-White patients who were 64% (271) female with mean age 80 ± 11 years. Univariate chi-square and Mann-Whitney U tests of demographics were used to compare White and non-White patients and find factors to control for potentially relevant confounding variables. Multivariable regression analyses were used to control for important baseline between-group differences to (1) determine the correlation of White and non-White race on mortality, inpatient complications, intensive care unit (ICU) admissions, and discharge disposition and (2) assess the correlation of gender, socioeconomic status, insurance payor, and the Score for Trauma Triage in the Geriatric and Middle Aged (STTGMA) trauma risk score with these quality measures and outcomes. After controlling for gender, insurer, socioeconomic status and STTGMA trauma risk score, we found that non-White patients had similar or improved care in terms of mortality and rates of delayed surgery, ICU admission, major complications, and discharge location in the setting of the standardized care pathway. Non-White race was not associated with inpatient (odds ratio 1.1 [95% CI 0.40 to 2.73]; p > 0.99), 30-day (OR 1.0 [95% CI 0.48 to 1.83]; p > 0.99) or 1-year mortality (OR 0.9 [95% CI 0.57 to 1.33]; p > 0.99). Non-White race was not associated with delay to surgery beyond 2 days (OR = 1.1 [95% CI 0.79 to 1.38]; p > 0.99). Non-White race was associated with less frequent ICU admissions (OR 0.6 [95% CI 0.42 to 0.85]; p = 0.03) and fewer major complications (OR 0.5 [95% CI 0.35 to 0.83]; p = 0.047). Non-White race was not associated with discharge to skilled nursing facility (OR 1.0 [95% CI 0.78 to 1.30]; p > 0.99), acute rehabilitation facility (OR 1.0 [95% CI 0.66 to 1.41]; p > 0.99), or home (OR 0.9 [95% CI 0.68 to 1.29]; p > 0.99). Controlled factors other than White versus non-White race were associated with mortality, discharge location, ICU admission, and major complication rate. Notably, the STTGMA trauma risk score was correlated with all endpoints. In the context of a hip fracture care pathway that reduces variability from time of presentation through discharge, no differences in mortality, time to surgery, complications, and discharge disposition rates were observed beween White and non-White patients after controlling for baseline differences including trauma risk score. The pathway detailed in this study is one iteration that the authors encourage surgeons to customize and trial at their institutions, with the goal of providing equitable care to patients with hip fractures and reducing healthcare disparities. Future investigations should aim to elucidate the impact of standardized trauma care pathways through the use of the STTGMA trauma risk score as a controlled confounder or randomized trials in comparing standardized to individualized, surgeon-specific care. Level III, therapeutic study.

Parola R ，Neal WH ，Konda SR ，Ganta A ，Egol KA ... -  《-》

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 ... -  《-》

Patients From Distressed Communities Who Undergo Surgery for Hip Fragility Fractures Are Less Likely to Have Advanced Care Planning Documents in Their Electronic Medical Record.

Advanced care planning documents provide a patient's healthcare team and loved ones with guidance on patients' treatment preferences when they are unable to advocate for themselves. A substantial proportion of patients will die within a few months of experiencing a hip fracture, but despite the importance of such documents, patients undergoing surgery for hip fracture seldom have discussions documented in the medical records regarding end-of-life care during their surgical admission. To the best of our knowledge, the proportion of patients older than 65 years treated with surgery for hip fractures who have advanced care planning documents in their electronic medical record (EMR) has not been explored, neither has the association between socioeconomic status and the presence of those documents in the EMR. Determining this information can help to identify opportunities to promote advanced care planning. (1) What percentage of patients older than 65 years who undergo hip fracture surgery have completed advanced care planning documents uploaded in the EMR before or during their surgical hospitalization, or at any timepoint (before admission, during admission, and after admission)? (2) Are patients from distressed communities less likely to have advanced care planning documents in the EMR than patients from wealthier communities, after controlling for economic well-being as measured by the Distressed Communities Index? (3) What percentage of patients older than 65 years with hip fractures who died during their hospitalization for hip fracture surgery had advanced care planning documents uploaded in the EMR? This was a retrospective, comparative study conducted at two geographically distinct hospitals: one urban Level I trauma center and one suburban Level II trauma center. Between 2017 and 2021, these two centers treated 850 patients for hip fractures. Among those patients, we included patients older than 65 years who were treated with open reduction and internal fixation, intramedullary nailing, hemiarthroplasty, or THA for a fragility fracture of the proximal femur. Based on that, 83% (709 of 850) of patients were eligible; a further 6% (52 of 850) were excluded because they had codes other than ICD-9 820 or ICD-10 S72.0, and another 2% (17 of 850) had incomplete datasets, leaving 75% (640 of 850) for analysis here. Most patients with incomplete datasets were in the prosperous Distressed Communities Index category. Among patients included in this study, the average age was 82 years, 70% (448 of 640) were women, and regarding the Distressed Communities Index, 32% (203 of 640) were in the prosperous category, 25% (159 of 640) were in the comfortable category, 15% (99 of 640) were in the mid-tier category, 5% (31 of 640) were in the at-risk category, and 23% (145 of 640) were in the distressed category. The primary outcome included the presence of advanced care planning documents (advanced directives, healthcare power of attorney, or physician orders for life-sustaining treatment) in the EMR before surgery, during the surgical admission, or at any time. The Distressed Communities Index was used to indicate economic well-being, and patients were identified as being in one of five Distressed Communities Index categories (prosperous, comfortable, mid-tier, at-risk, and distressed) based on ZIP Code. An exploratory analysis was conducted to determine variables associated with the presence of advanced care planning documents in the EMR. A multivariate regression was then performed for patients who did or did not have advanced care planning documents in their medical record at any time. The results are presented as ORs with the associated 95% confidence interval (CI). Nine percent (55 of 640) of patients had advanced care planning documents in the EMR preoperatively or during their surgical admission, and 22% (142 of 640) of patients had them in the EMR at any time. After controlling for potential confounding variables such as age, laterality (left or right hip), hospital type, and American Society of Anesthesiologists (ASA) classification, we found that patients in Distressed Communities Index categories other than prosperous had ORs lower than 0.7, with patients in the distressed category (OR 0.4 [95% CI 0.2 to 0.7]; p < 0.01) and comfortable category (OR 0.5 [95% CI 0.3 to 0.9]; p = 0.01) having a substantially lower odds of having advanced care planning documents in their EMR. Patients aged 86 to 95 years (OR 1.9 [95% CI 1.1 to 3.4]), those 96 years and older (OR 4.0 [95% CI 1.7 to 9.5]), and those with a higher ASA classification (OR 1.6 [95% CI 1.1 to 2.3]) had a higher odds of having advanced care planning documents in the EMR at any time. Among 14 patients who experienced in-hospital mortality, two had advanced care planning documents uploaded into their EMR, whereas 12 of 14 who died in the hospital did not have advanced care planning documents uploaded into their EMR. Orthopaedic surgeons should counsel patients regarding the risk for postoperative complications after fragility hip fracture surgery and engage in shared decision-making regarding advanced care planning documents with patients or, if the patients are unable, with their families. Additionally, implementing virtual education about advanced care planning documents and using easy-to-read forms may facilitate the completion of advanced care planning documents by patients older than 65 years, especially patients with low economic well-being. Limitations of this study include having a restricted number of patients in the at-risk and mid-tier Distressed Communities Index categories and a restricted number of patients identifying as non-White races/ethnicities. Future research should evaluate the effect of advanced care document presence in the EMR on end-of-life care intensity in patients treated for fragility hip fractures. Level III, therapeutic study.

Khan IA ，Magnuson JA ，Ciesielka KA ，Levicoff EA ，Cohen-Rosenblum A ，Krueger CA ，Fillingham YA ... -  《-》

Do Disparities in Wait Times to Operative Fixation for Pathologic Fractures of the Long Bones and 30-day Complications Exist Between Black and White Patients? A Study Using the NSQIP Database.

Racial disparities in outcomes after orthopaedic surgery have been well-documented in the fields of arthroplasty, trauma, and spine surgery; however, little research has assessed differences in outcomes after surgery for oncologic musculoskeletal disease. If racial disparities exist in the treatment of patients with pathologic long bone fractures, then they should be identified and addressed to promote equity in patient care. (1) How do wait times between hospital admission and operative fixation for pathologic fractures of long bones differ between Black and non-Hispanic white patients, after controlling for confounding variables using propensity score matching? (2) How does the proportion of patients with 30-day postoperative complication differ between these groups after controlling for confounding variables using propensity score matching? Using the National Surgical Quality Improvement Program database, we analyzed 828 patients who underwent fixation for pathologic fractures from 2012 to 2018. This database not only provides a large enough sample of pathologic long bone fracture patients to conduct the present study, but also it contains variables such as time from hospitalization to surgery that other national databases do not. After excluding patients with incomplete data (4% of the initial cohort), 775 patients were grouped by self-reported race as Black (12% [94]) or white (88% [681]). Propensity score matching using a 1:1 nearest-neighbor match was then used to match 94 Black patients with 94 white patients according to age, gender, BMI, American Society of Anesthesiologists physical status classification, anemia, endstage renal disease, independence in performing activities of daily living, congestive heart failure, and pulmonary disease. The primary outcome of interest was the number of days between hospital admission and operative fixation, which we assessed using a Poisson regression and report as an incidence risk ratio. The secondary outcomes were the occurrences of major 30-day postoperative adverse events (failure to wean off mechanical ventilation, cerebrovascular events, renal failure, cardiovascular events, reoperation, death), minor 30-day adverse events (reintubation, wound complications, pneumonia, and thromboembolic events), and any 30-day adverse events (defined as the pooling of all adverse events, including readmissions). These outcomes were analyzed using a bivariate analysis and logistic regression with robust estimates of variance and are reported as odds ratios. Because any results on disparities rely on rigorous control of other baseline demographics, we performed this multivariable approach to ensure we were controlling for confounding variables as much as possible. After controlling for potentially confounding variables such as age and gender, we found that Black patients had a longer mean wait time (incidence risk ratio 1.5 [95% CI 1.1 to 2.1]; p = 0.01) than white patients. After controlling for confounding variables, Black patients also had greater odds of having any postoperative adverse event (OR 2.1 [95% CI 1.1 to 3.8]; p = 0.02), including readmission (OR 3.3 [95% CI 1.5 to 7.6]; p = 0.004). The racial disparities in pathologic long bone fracture care found in our study may be attributed to fundamental racial biases, as well as systemic socioeconomic disparities in the US healthcare system. Identifying and eliminating the racial, socioeconomic, and sociocultural biases that drive these disparities would improve care for patients with orthopaedic oncologic conditions. One possible way to reduce these disparities would be to implement standardized surgical care pathways for pathological long bone fractures across different institutions to minimize variation in important aspects of care, such as time to surgical fixation. Further insight is needed on the types of standardized care pathways and the implementation mechanisms that are most effective. Level III, therapeutic study.

Raad M ，Puvanesarajah V ，Wang KY ，McDaniel CM ，Srikumaran U ，Levin AS ，Morris CD ... -  《-》

Is Delayed Time to Surgery Associated with Increased Short-term Complications in Patients with Pathologic Hip Fractures?

Varady NH ，Ameen BT ，Chen AF 《-》