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.

High Area Deprivation Index is Associated With Not Achieving the Patient-acceptable Symptom State After TKA.

BACKGROUND: The Area Deprivation Index (ADI) approximates a patient's relative socioeconomic deprivation. The ADI has been associated with increased healthcare use after TKA, but it is unknown whether there is an association with patient-reported outcome measures (PROMs). Given that a high proportion of patients are dissatisfied with their results after TKA, and the large number of these procedures performed, knowledge of factors associated with PROMs may indicate opportunities to provide support to patients who might benefit from it. QUESTIONS/PURPOSES: (1) Is the ADI associated with achieving the minimum clinically important difference (MCID) for the Knee Injury and Osteoarthritis Outcome Score (KOOS) for pain, Joint Replacement (JR), and Physical Function (PS) short forms after TKA? (2) Is the ADI associated with achieving the patient-acceptable symptom state (PASS) thresholds for the KOOS pain, JR, and PS short forms? METHODS: This was a retrospective study of data drawn from a longitudinally maintained database. Between January 2016 and July 2021, a total of 12,239 patients underwent unilateral TKA at a tertiary healthcare center. Of these, 92% (11,213) had available baseline PROM data and were potentially eligible. An additional 21% (2400) of patients were lost before the minimum study follow-up of 1 year or had incomplete data, leaving 79% (8813) for analysis here. The MCID is the smallest change in an outcome score that a patient is likely to perceive as a clinically important improvement, and the PASS refers to the threshold beyond which patients consider their symptoms acceptable and consistent with adequate functioning and well-being. MCIDs were calculated using a distribution-based method. Multivariable logistic regression models were created to investigate the association of ADI with 1-year PROMs while controlling for patient demographic variables. ADI was stratified into quintiles based on their distribution in our sample. Achievement of MCID and PASS thresholds was determined by the improvement between preoperative and 1-year PROMs. RESULTS: After controlling for patient demographic factors, ADI was not associated with an inability to achieve the MCID for the KOOS pain, KOOS PS, or KOOS JR. A higher ADI was independently associated with an increased risk of inability to achieve the PASS for KOOS pain (for example, the odds ratio of those in the ADI category of 83 to 100 compared with those in the 1 to 32 category was 1.34 [95% confidence interval 1.13 to 1.58]) and KOOS JR (for example, the OR of those in the ADI category of 83 to 100 compared with those in the 1 the 32 category was 1.29 [95% CI 1.10 to 1.53]), but not KOOS PS (for example, the OR of those in the ADI category of 83 to 100 compared with those in the 1 the 32 category was 1.09 [95% CI 0.92 to 1.29]). CONCLUSION: Our findings suggest that social and economic factors are associated with patients' perceptions of their overall pain and function after TKA, but such factors are not associated with patients' perceptions of their improvement in symptoms. Patients from areas with higher deprivation may be an at-risk population and could benefit from targeted interventions to improve their perception of their healthcare experience, such as through referrals to nonemergent medical transportation and supporting applications to local care coordination services before proceeding with TKA. Future research should investigate the mechanisms underlying why socioeconomic disadvantage is associated with inability to achieve the PASS, but not the MCID, after TKA. LEVEL OF EVIDENCE: Level III, therapeutic study.

Intraincisional Pin Placement is Safe for Robotic-Assisted Total Knee Arthroplasty.

BACKGROUND: While robotic-arm assisted total knee arthroplasty (RA-TKA) has seen a major increase in its utilization, it requires bone array pins to be fixed into the femur and tibia, which intrinsically carries a risk. As it is currently off-label with some robotic platforms to place pins intraincisional, we aimed to evaluate the safety of intraincisional pin placement during RA-TKAs. METHODS: A prospective cohort of 2,343 patients who underwent RA-TKA at a North American Healthcare System between January 2018 and March 2022 was included. Primary outcomes included periprosthetic fracture or infection (eg, superficial or deep). Secondary outcomes included 1-year reoperation rate due to any cause. Cases were retrospectively reviewed to determine whether complications could be attributed to metaphyseal intraincisional pin placement (4.0 mm pins; two tibial and two femoral). The 90-day follow-up was 100% and the 1-year follow-up rate was 70.6% (n = 1,655). RESULTS: The pin-site related periprosthetic fracture incidence at 90 days was 0.09% (2 out of 2,343). The 90-day infection incidence was 1.4% (superficial: 22; deep: 13). The 1-year reoperation rate was 1.8% (29 out of 1,655). The most common causes of reoperation at 1-year were deep infection (n = 14; 0.83%), superficial infection (n = 3; 0.18%), periprosthetic fracture, mechanical symptoms, instability, and hematoma (n = 2; 0.12% for each). CONCLUSIONS: One in 1,172 patients may experience a pin-related periprosthetic fracture after RA-TKA with intraincisional bone array pin placement. There was a low 90-day infection incidence and reoperations within 1-year after RA-TKA were rare.

What Are the Diagnosis-Specific Thresholds of Minimal Clinically Important Difference and Patient Acceptable Symptom State in Hip Disability and Osteoarthritis Outcome Score After Primary Total Hip Arthroplasty?

BACKGROUND: This study aimed to determine the minimal clinically important difference (MCID) and Patient Acceptable Symptom State (PASS) thresholds for Hip Disability and Osteoarthritis Outcome Score (HOOS) pain, physical short form (PS), and joint replacement (JR) 1 year after primary total hip arthroplasty stratified by preoperative diagnosis of osteoarthritis (OA) versus non-OA. METHODS: A prospective institutional cohort of 5,887 patients who underwent primary total hip arthroplasty (January 2016 to December 2018) was included. There were 4,184 patients (77.0%) who completed a one-year follow-up. Demographics, comorbidities, and baseline and one-year HOOS pain, PS, and JR scores were recorded. Patients were stratified by preoperative diagnosis: OA or non-OA. Minimal detectable change (MDC) and MCIDs were estimated using a distribution-based approach. The PASS values were estimated using an anchor-based approach, which corresponded to a response to a satisfaction question at one year post surgery. RESULTS: The MCID thresholds were slightly higher in the non-OA cohort versus OA patients. (HOOS-Pain: OA: 8.35 versus non-OA: 8.85 points; HOOS-PS: OA: 9.47 versus non-OA: 9.90 points; and HOOS-JR: OA: 7.76 versus non-OA: 8.46 points). Similarly, all MDC thresholds were consistently higher in the non-OA cohort compared to OA patients. The OA cohort exhibited similar or higher PASS thresholds compared to the non-OA cohort for HOOS-Pain (OA: ≥80.6 versus non-OA: ≥77.5 points), HOOS-PS (OA: ≥83.6 versus non-OA: ≥83.6 points), and HOOS-JR (OA: ≥76.8 versus non-OA: ≥73.5 points). A similar percentage of patients achieved MCID and PASS thresholds regardless of preoperative diagnosis. CONCLUSIONS: While MCID and MDC thresholds for all HOOS subdomains were slightly higher among non-OA than OA patients, PASS thresholds for HOOS pain and JR were slightly higher in the OA group. The absolute magnitude of the difference in these thresholds may not be sufficient to cause major clinical differences. However, these subtle differences may have a significant impact when used as indicators of operative success in a population setting.

Predictive Modeling of Medical- and Orthopaedic-Related 90-Day Readmissions Following Primary Total Hip Arthroplasty.

BACKGROUND: The rate of unplanned hospital readmissions following total hip arthroplasty (THA) varies from 3 to 10%, representing a major economic burden. However, it is unknown if specific factors are associated with different types of complications (ie, medical or orthopaedic-related) that lead to readmissions. Therefore, this study aimed to: (1) determine the overall, medical-related, and orthopaedic-related 90-day readmission rate; and (2) develop a predictive model for risk factors affecting overall, medical-related, and orthopaedic-related 90-day readmissions following THA. METHODS: A prospective cohort of primary unilateral THAs performed at a large tertiary academic center in the United States from 2016 to 2020 was included (n = 8,893 patients) using a validated institutional data collection system. Orthopaedic-related readmissions were specific complications affecting the prosthesis, joint, and surgical wound. Medical readmissions were due to any other cause requiring medical management. Multivariable logistic regression models were used to investigate associations between prespecified risk factors and 90-day readmissions, as well as medical and orthopaedic-related readmissions independently. RESULTS: Overall, the rate of 90-day readmissions was 5.6%. Medical readmissions (4.2%) were found to be more prevalent than orthopaedic-related readmissions (1.4%). The area under the curve for the 90-day readmission model was 0.71 (95% confidence interval: 0.69 to 0.74). Factors significantly associated with medical-related readmissions were advanced age, Black race, education, Charlson Comorbidity Index, surgical approach, opioid overdose risk score, and nonhome discharge. In contrast, risk factors linked to orthopaedic-related readmissions encompassed body mass index, patient-reported outcome measure phenotype, nonosteoarthritis indication, opioid overdose risk, and nonhome discharge. CONCLUSIONS: Of the overall 90-day readmissions following primary THA, 75% were due to medical-related complications. Our successful predictive model for complication-specific 90-day readmissions highlights how different risk factors may disproportionately influence medical versus orthopaedic-related readmissions, suggesting that patient-specific, tailored preventive measures could reduce postoperative readmissions in the current value-based health care setting.

Does Your Patient Need to Lose Weight? Weight Change Before and After Total Hip Arthroplasty Does Not Affect Health Care Utilization and Achievement of the Minimal Clinically Important Difference.

BACKGROUND: Despite the potential negative impact of preoperative obesity on total hip arthroplasty (THA) outcomes, the association between preoperative and postoperative weight change and outcomes is much less understood. Therefore, this study aimed to determine the impact of preoperative and postoperative weight change and preoperative body mass index (BMI) on health care utilization, satisfaction, and achievement of minimal clinically important difference (MCID) for Hip Disability and Osteoarthritis Outcome Score Physical Function Short-Form (HOOS PS) and HOOS Pain. METHODS: Patients who underwent primary elective unilateral THA between January 2016 and December 2019 were included (N = 2,868). Multivariable logistic regression assessed the association between BMI and preoperative and postoperative weight change on outcomes while controlling for demographic characteristics. RESULTS: There was no association between preoperative weight change and prolonged length of stay (> 3 days), 90-day readmission, nonhome discharge, patient dissatisfaction at 1 year, or achievement of HOOS Pain or HOOS PS MCID. Postoperative weight loss was an independent risk factor for patient dissatisfaction at 1 year but was not associated with achievement of either HOOS Pain or HOOS PS MCID at 1-year postoperative. Preoperative obesity classes I to III were independent risk factors for nonhome discharge. Nevertheless, preoperative obesity class I and class II were associated with an increased probability of reaching HOOS Pain MCID. Preoperative BMI was not associated with an increased risk of patient dissatisfaction. CONCLUSIONS: Preoperative weight change does not appear to influence health care utilization, satisfaction, or achievement of MCID in pain and function following THA. Postoperative weight loss may play a role as a risk factor for dissatisfaction following THA. Additionally, patients who had a higher baseline BMI may be more likely to see improvement in pain following THA. Therefore, when counseling obese patients for THA, surgeons must balance the risk of perioperative complications with the expectation of greater improvements in pain.

Recognizing the Sex Disparity in Surgeons Performing Total Knee Arthroplasty.

BACKGROUND: There is an unambiguous sex disparity in the field of orthopaedic surgery, with women making up only 7.4% of practicing orthopaedic surgeons in 2022. This study seeks to evaluate the sex distribution among orthopaedic surgeons engaged in primary total knee arthroplasty (TKA) between 2013 and 2020, as well as the procedural volume attributed to each provider. METHODS: We retrospectively queried the Medicare dataset to quantify all physicians reporting orthopaedic surgery as their specialty and performing primary TKA from 2013 to 2020. Healthcare Common Procedure Coding System codes for primary TKA procedures were used to extract associated utilization and billing provider information. Trend analyses were performed with 2-sided correlated Mann-Kendall tests to evaluate trends in the number of surgeons by sex and the women-to-men surgeon ratio. RESULTS: During the study period, 6,198 to 7,189 surgeons billed for primary TKA. Of this number, an average of 2% were women. The mean number of procedures billed for by men was 39.02/y (standard deviation: 34.54), and by women was 28.76/y (standard deviation: 20.62) (P < .001). There was no significant trend in the number of men or women surgeons who billed for primary TKA during the study period. Trend analysis of the women-to-men ratio demonstrated an increasing trend of statistical significance (P = .0187). CONCLUSIONS: There was a significant upward trend in the women-to-men ratio of surgeons who billed for primary TKA. However, there remains a colossal gender gap, as women only made up 2.4% of surgeons who billed for the procedure. The current study raises awareness of the notable discrepancy in the average number of TKAs performed by women as compared to men. The orthopaedic community should aim to determine ways to increase the number of women arthroplasty surgeons along with the opportunities that women have to perform TKAs.

The Mark Coventry Award: PhotothermAA Gel Combined With Debridement, Antibiotics, and Implant Retention Significantly Decreases Implant Biofilm Burden and Soft-Tissue Infection in a Rabbit Model of Knee Periprosthetic Joint Infection.

BACKGROUND: Chronic periprosthetic joint infection (PJI) is a major complication of total joint arthroplasty. The underlying pathogenesis often involves the formation of bacterial biofilm that protects the pathogen from both host immune responses and antibiotics. The gold standard treatment requires implant removal, a procedure that carries associated morbidity and mortality risks. Strategies to preserve the implant while treating PJI are desperately needed. Our group has developed an anti-biofilm treatment, PhotothermAA gel, which has shown complete eradication of 2-week-old mature biofilm in vitro. In this study, we tested the anti-biofilm efficacy and safety of PhotothermAA in vivo when combined with debridement, antibiotics and implant retention (DAIR) in a rabbit model of knee PJI. METHODS: New Zealand white rabbits (n = 21) underwent knee joint arthrotomy, titanium tibial implant insertion, and inoculation with Xen36 (bioluminescent Staphylococcus aureus) after capsule closure. At 2 weeks, rabbits underwent sham surgery (n = 6), DAIR (n = 6), or PhotothermAA with DAIR (n = 9) and were sacrificed 2 weeks later to measure implant biofilm burden, soft-tissue infection, and tissue necrosis. RESULTS: The combination of anti-biofilm PhotothermAA with DAIR significantly decreased implant biofilm coverage via scanning electron microscopy compared to DAIR alone (1.8 versus 81.0%; P < .0001). Periprosthetic soft-tissue cultures were significantly decreased in the PhotothermAA with DAIR treatment group (log reduction: Sham 1.6, DAIR 2.0, combination 5.6; P < .0001). Treatment-associated necrosis was absent via gross histology of tissue adjacent to the treatment area (P = .715). CONCLUSIONS: The addition of an anti-biofilm solution like PhotothermAA as a supplement to current treatments that allow implant retention may prove useful in PJI treatment.

Patient satisfaction and patient-reported outcomes do not vary by BMI class in total hip arthroplasty.

PURPOSE: Obesity has been identified as a risk factor for postoperative complications in patients undergoing total hip arthroplasty (THA). This study aimed to investigate patient-reported outcomes, pain, and satisfaction as a function of body mass index (BMI) class in patients undergoing THA. METHODS: 1736 patients within a prospective observational study were categorized into BMI classes. Pre- and postoperative Hip disability and Osteoarthritis Outcome Score for Joint Replacement (HOOS JR), satisfaction, and pain scores were compared by BMI class using one-way ANOVA. RESULTS: Healthy weight patients reported the highest preoperative HOOS JR (56.66 ± 13.35) compared to 45.51 ± 14.45 in Class III subjects. Healthy weight and Class III patients reported the lowest (5.65 ± 2.01) and highest (7.06 ± 1.98, p < 0.0001) preoperative pain, respectively. Changes in HOOS JR scores from baseline suggest larger improvements with increasing BMI class, where Class III patients reported an increase of 33.7 ± 15.6 points at 90 days compared to 26.1 ± 17.1 in healthy weight individuals (p = 0.002). Fewer healthy weight patients achieved the minimal clinically important difference (87.4%) for HOOS JR compared to Class II (96.5%) and III (94.7%) obesity groups at 90 days postoperatively. Changes in satisfaction and pain scores were largest in the Class III patients. Overall, no functional outcomes varied by BMI class postoperatively. CONCLUSION: Patients of higher BMI class reported greater improvements following THA. While risk/benefit shared decision-making remains a personalized requirement of THA, this study highlights that utilization of BMI cutoff may not be warranted based on pain and functional improvement.

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

BACKGROUND: 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. QUESTIONS/PURPOSES: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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 OF EVIDENCE: Level III, therapeutic study.

Challenging the Status Quo: Debunking the Necessity of 5-Year to 10-Year Patient-Reported Outcome Measures in Total Hip and Knee Arthroplasties.

BACKGROUND: In the current shift toward value-based healthcare, patient-reported outcome measures (PROMs) have become essential to assess the effectiveness of medical interventions. However, elucidation of the optimal timeframe for PROMs evaluation remains crucial. This study aimed to (1) determine the proportion of patients who experienced clinically meaningful improvements in PROMs scores at each follow-up visit after total hip arthroplasty (THA) and total knee arthroplasty (TKA) and (2) calculate and apply the clinical relevance ratio (CRR) for these long-term PROM collections postoperatively. METHODS: A total of 12 independent studies reporting THA (n = 8 studies) and TKA (n = 4 studies) postoperative PROM data with up to 10 years of follow-up in Europe or the United States were aggregated. A distribution-based minimal clinically important difference threshold and CRR were used to determine which patients had clinically meaningful improvements in PROMs at 1, 5, and 10 years. RESULTS: The proportion of patients who had clinically meaningful improvements in PROM scores stabilized after 1 year following both THA and TKA. Overall, the CRR decreased over time for all PROMs, with the CRR beginning to decrease at 1-year follow-up, bringing into question the robustness and clinical relevance of long-term PROMs data. CONCLUSIONS: The present study challenges the utility of requiring PROMs with a minimum follow-up of 2 years for THA and TKA. Research efforts should be focused on registries evaluating implant survivorship at longer-term follow-up, while PROMs should be better assessed up to 1-year follow-up. Reconsidering the long-term PROMs assessment would lead to more efficient and cost-effective research in orthopedic outcomes, without compromising data quality.

What Drives the Material Costs of Total Knee Arthroplasty in the Operating Room?

INTRODUCTION: Approximately one-third of US healthcare spending is related to surgical care. Optimizing operating room (OR) spending is crucial, specifically for high-volume procedures like total knee arthroplasty (TKA). Therefore, the primary objective was to identify leading material drivers of cost for TKA procedures within the OR. MATERIALS AND METHODS: Patients who underwent a primary, elective TKA from 2018 to 2019 were included (n=8,672). Intraoperative cost details for each TKA patient were captured from the Vizient Clinical Database Resource Manager (CDB/RM) data. Each cost type was categorized into (1) implant, (2) disposables, (3) wound care, and (4) miscellaneous. RESULTS: 7,124 patients undergoing primary TKA were included. Implant-related costs accounted for 87.3% of cost, disposable materials covered 10.7%, and wound care products took 2%. The leading subcategories of implant costs were primary prosthetics (85.1%), revision prosthetics (9.9%), cement (2.8%), and implant instruments (1.7%). Within disposables, surgical products accounted for 81.3% of the cost, patient care products for 8.9%, medical apparel for 7.9%, and electrolytes for 1.8%. For an average individual TKA procedure, 86.4% (±4.4) of total cost went towards the implant, 10.7% (±3.4) towards disposable materials, and 1.6% (±1.4) to wound care products. Within the implant category, 92.5% (± 12.8) of costs were associated with primary implants, 13.3% (± 6.9) with instruments, and 2.5% (± 2.8) with cement. CONCLUSIONS: The primary operative material expense category was costs associated with the TKA prosthesis and its fixation followed by disposable materials. A large amount of variation exists in the percent of the total cost for a given TKA procedure that can be attributed to each category.

Can extant comorbidity indices identify patients who experience poor outcomes following total joint arthroplasty?

INTRODUCTION: It is uncertain if generic comorbidity indices commonly used in orthopedics accurately predict outcomes after total hip (THA) or knee arthroplasty (TKA). The purpose of this study was to determine the predictive ability of such comorbidity indices for: (1) 30-day mortality; (2) 30-day rate of major and minor complications; (3) discharge disposition; and (4) extended length of stay (LOS). METHODS: The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database was retrospectively reviewed for all patients who underwent elective THA (n = 202,488) or TKA (n = 230,823) from 2011 to 2019. The American Society of Anesthesiologists (ASA) physical status classification system score, modified Charlson Comorbidity Index (mCCI), Elixhauser Comorbidity Measure (ECM), and 5-Factor Modified Frailty Index (mFI-5) were calculated for each patient. Logistic regression models predicting 30-day mortality, discharge disposition, LOS greater than 1 day, and 30-day major and minor complications were fit for each index. RESULTS: The ASA classification (C-statistic = 0.773 for THA and TKA) and mCCI (THA: c-statistic = 0.781; TKA: C-statistic = 0.771) were good models for predicting 30-day mortality. However, ASA and mCCI were not predictive of major and minor complications, discharge disposition, or LOS. The ECM and mFI-5 did not reliably predict any outcomes of interest. CONCLUSION: ASA and mCCI are good models for predicting 30-day mortality after THA and TKA. However, similar to ECM and mFI-5, these generic comorbidity risk-assessment tools do not adequately predict 30-day postoperative outcomes or in-hospital metrics. This highlights the need for an updated, data-driven approach for standardized comorbidity reporting and risk assessment in arthroplasty.

Simultaneous bilateral total knee arthroplasty has higher in-hospital complications than both staged surgeries: a nationwide propensity score matched analysis of 38,764 cases.

PURPOSE: To investigate (1) healthcare utilization, (2) in-hospital metrics and (3) total in-hospital costs associated with simultaneous versus staged BTKA while evaluating staged BTKA as a single process consisting of two combined episodes. METHODS: The national readmissions database was reviewed for simultaneous and staged (two primary unilateral TKAs12 months apart) BTKA patients (2016-2017). A total of 19,382 simultaneous BTKAs were identified, and propensity score matched (1:1) to staged BTKA patients (19,382 patients; 38,764 surgeries) based on demographics, comorbidities, and socioeconomic determinants. Outcomes included healthcare utilization [length of stay (LOS) and discharge disposition], in-hospital periprosthetic fractures, non-mechanical complications, and costs. Staged BTKA was evaluated as one process consisting of two episodes. For each staged patient, continuous outcomes were evaluated via the sum of both episodes. Categorical outcomes were added, and percents were expressed relative to total number of surgeries (n = 38,764). RESULTS: Simultaneous BTKA had longer LOS (5.0 days ± 4.7 vs. 4.5 days ± 3.5; p < 0.001), higher non-home discharge [36.9% (n = 7150/19,382) vs. 13.6% (n = 5451/38,764)], in-hospital periprosthetic fractures [0.13% (26/19,382) vs. 0.08% (31/38,764); p = 0.049], any non-mechanical complication [33.76% (6543/19,382) vs.15.93% (6177/38,764); p < 0.0001], hematoma/seroma formation [0.11% (22/19,382) vs. 0.05% (20/38,764); p = 0.0088], wound disruption [0.08% (16/19,382) vs. 0.04% (16/38,764); p = 0.0454], and any infection [1.13% (219/19,382) vs. 0.50% (194/38,764); p < 0.0001]. Average in-hospital costs for the two staged BTKA episodes combined were $5006 higher than those of simultaneous BTKA ($28,196 ± $18,488 vs. $33,202 ± $15,240; p < 0.001). CONCLUSION: Simultaneous BTKA had higher healthcare utilization and in-hospital complications than both episodes of staged BTKA combined, with a minimal in-hospital cost savings. Future studies are warranted to further explore patient selection who would benefit from BTKA.

Preoperative Colonization With Staphylococcus Aureus in THA Is Associated With Increased Length of Stay.

BACKGROUND: Staphylococcus aureus is a common organism implicated in prosthetic joint infection after THA and TKA, prompting preoperative culturing and decolonization to reduce infection rates. It is unknown whether colonization is associated with other noninfectious outcomes of THA or TKA. QUESTIONS/PURPOSES: (1) What is the association between preoperative S. aureus colonization (methicillin-sensitive S. aureus [MSSA] and methicillin-resistant S. aureus [MRSA]) and the noninfectious outcomes (discharge destination, length of stay, Hip/Knee Disability and Osteoarthritis Outcome Score [HOOS/KOOS] pain score, HOOS/KOOS physical function score, 90-day readmission, and 1-year reoperation) of THA and TKA? (2) What factors are associated with colonization with S. aureus ? METHODS: Between July 2015 and March 2019, 8078 patients underwent primary THA in a single healthcare system, and 17% (1382) were excluded because they were not tested preoperatively for S. aureus nasal colonization, leaving 6696 patients in the THA cohort. Between June 2015 and March 2019, 9434 patients underwent primary TKA, and 12% (1123) were excluded because they were not tested for S. aureus colonization preoperatively, leaving 8311 patients in the TKA cohort. The goal of the institution's standardized care pathways is to test all THA and TKA patients preoperatively for S. aureus nasal colonization; the reason the excluded patients were not tested could not be determined. Per institutional protocols, all patients were given chlorhexidine gluconate skin wipes to use on the day before and the day of surgery, and patients with positive S. aureus cultures were instructed to use mupirocin nasal ointment twice daily for 3 to 5 days preoperatively. Adherence to these interventions was not tracked, and patients were not rescreened to test for S. aureus control. The minimum follow-up time for each outcome and the percentage of the cohort lost for each was: for discharge destination, until discharge (0 patients lost); for length of stay, until discharge (0.06% [4 of 6696] lost in the THA group and 0.01% [1 of 8311] lost in the TKA group); for HOOS/KOOS pain score, 1 year (26% [1734 of 6696] lost in the THA group and 24% [2000 of 8311] lost in the TKA group); for HOOS/KOOS physical function, 1 year (33% [2193 of 6696] lost in the THA group and 28% [2334 of 8311] lost in the TKA group); for 90-day readmission, 90 days (0.06% [4 of 6696] lost in the THA group and 0.01% [1 of 8311] lost in the TKA group); and for 1-year reoperation, 1 year (30% [1984 of 6696] lost in the THA group and 30% [2475 of 8311] lost in the TKA group). Logistic regression models were constructed to test for associations between MSSA or MRSA and nonhome discharge, length of stay greater than 1 day, improvement in the HOOS/KOOS pain subscale (≥ the minimum clinically important difference), HOOS/KOOS physical function short form (≥ minimum clinically important difference), 90-day readmission, and 1-year reoperation. We adjusted for patient-related and hospital-related factors, such as patient age and hospital site. Variable significance was assessed using the likelihood ratio test with a significance level of p < 0.05. To assess factors associated with S. aureus colonization, we constructed a logistic regression model with the same risk factors. RESULTS: Among the THA cohort, after controlling for potentially confounding variables such as patient age, smoking status, and BMI, S. aureus colonization was associated with length of stay greater than 1 day (MSSA: odds ratio 1.32 [95% CI 1.08 to 1.60]; MRSA: OR 1.88 [95% CI 1.24 to 2.85]; variable p < 0.001 by likelihood ratio test) but not the other outcomes of THA. Male sex (OR 1.26 [95% CI 1.09 to 1.45]; p = 0.001) and BMI (OR 1.02 for a one-unit increase over median BMI [95% CI 1.01 to 1.03]; p = 0.003) were patient-related factors associated with S. aureus colonization, whereas factors associated with a lower odds were older age (OR 0.99 [95% CI 0.98 to 0.99]; p < 0.001) and Black race compared with White race (OR 0.64 [95% CI 0.50 to 0.82]; p < 0.001). Among the TKA cohort, S. aureus colonization was associated with 90-day readmission (MSSA: OR 1.00 [95% CI 0.99 to 1.01]; MRSA: OR 1.01 [95% CI 1.00 to 1.01]; variable p = 0.007 by likelihood ratio test). Male sex (OR 1.19 [95% CI 1.05 to 1.34]; p = 0.006) was associated with S. aureus colonization, whereas factors associated with a lower odds of colonization were older age (OR 0.99 [95% CI 0.98 to 0.99]; p < 0.001), Veterans RAND-12 mental component score (OR 0.99 [95% CI 0.99 to 1.00]; p = 0.027), Black race compared with White race (OR 0.70 [95% CI 0.57 to 0.85]; p < 0.001), and being a former smoker (OR 0.86 [95% CI 0.75 to 0.97]; p = 0.016) or current smoker (OR 0.70 [95% CI 0.55 to 0.90]; p = 0.005) compared with those who never smoked. CONCLUSION: After controlling for the variables we explored, S. aureus colonization was associated with increased length of stay after THA and 90-day readmission after TKA, despite preoperative decolonization. Given that there is little causal biological link between colonization and these outcomes, the association is likely confounded but may be a proxy for undetermined social or biological factors, which may alert the surgeon to pay increased attention to outcomes in patients who test positive. Further study of the association of S. aureus colonization and increased length of stay after THA and readmission after TKA may be warranted to determine what the confounding variables are, which may be best accomplished using large cohorts or registry data. LEVEL OF EVIDENCE: Level III, therapeutic study.

Combinations of Preoperative Patient-Reported Outcome Measure Phenotype (Pain, Function, and Mental Health) Predict Outcome After Total Knee Arthroplasty.

BACKGROUND: Value-driven healthcare models prioritize patient-perceived benefits to quantify the quality of care through patient-reported outcome measures (PROMs). The Patient Acceptable Symptom State (PASS) is the highest level of symptom beyond which a patient considers his/her condition satisfactory. We identified preoperative phenotypes of PROMs associated with not achieving PASS at 1 year following total knee arthroplasty (TKA) and explored the relationships between such phenotypes with hospital utilization parameters. METHODS: A prospective institutional cohort of 5,274 primary TKAs for osteoarthritis from 2016 to 2019 with 1-year follow-up were included. Preoperative scores on Knee Disability and Osteoarthritis Outcome Score (KOOS) Pain, KOOS-Physical function Short form (PS), and Veterans RAND 12-Item Health Survey (VR-12) Mental Component Summary (MCS) were used to develop patient phenotypes. Associations between preoperative "phenotype" and 1-year PASS, discharge disposition, length of stay, 90-day readmission, and 1-year reoperation were evaluated using multivariate regression. RESULTS: In total, 16.3% (n = 862) of patients reported their state as "not acceptable" at 1 year. A combination of low scores in each of the presently examined PROMs was associated with the highest odds of 1-year dissatisfaction (odds ratio 2.18, 95% confidence interval 1.74-2.74). The PROM phenotypes were the greatest drivers compared to sociodemographic variables in predicting satisfaction. Combinations of low scores in VR-12 MCS and KOOS-PS were significantly associated with both non-home discharge status and prolonged length of stay. CONCLUSION: Patients with combined lower preoperative scores across multiple PROMs (KOOS-Pain <41.7, KOOS-PS <51.5, and VR-12 MCS <52.8) have increased odds of dissatisfaction after TKA. Measuring pain, function, and mental health concurrently as phenotypes may help identify TKA patients at risk for not achieving a satisfactory outcome at 1 year.

Dissatisfaction After Total Hip Arthroplasty Associated With Preoperative Patient-Reported Outcome Phenotypes.

BACKGROUND: Patient satisfaction is indicative of the quality of care in the value-driven healthcare model. The Patient Acceptable Symptom State (PASS) is a dichotomous outcome tool measuring the highest level of symptom beyond which a patient considers him/herself well. The purpose of the present study was to identify combined preoperative phenotypes of PROMs associated with not achieving PASS at 1 year following total hip arthroplasty (THA) and to associate such phenotypes with hospital utilization parameters. METHODS: A prospective institutional cohort of 4,034 patients who underwent primary THA for osteoarthritis (OA) with 1-year follow-up was included. Preoperative scores on Hip Disability and Osteoarthritis Outcome Score (HOOS)-pain, HOOS physical short form-(PS), and Veteran's Rand-12 (VR-12) mental component summary-(MCS) were used to develop phenotypes. Associations between preoperative 'phenotype' and 1-year PASS, discharge disposition, prolonged length of stay, 90-day readmission, and 1-year reoperation were evaluated using multivariate regression. RESULTS: 10.6% (427/4,043) reported their state as 'not satisfactory' at 1 year. The phenotypes were the only preoperative factors to demonstrate the increased likelihood of 1-year dissatisfaction. Only phenotypes with lower than average preoperative MCS demonstrated this association. Low scores in all presently measured PROMs (Pain-PS-MCS-) was associated with double the odds of 1-year dissatisfaction (P < .001), 2.43 times the odds of nonhome discharge and 2.2 times the odds of prolonged LOS. CONCLUSIONS: Patients with lower preoperative scores across multiple PROMs have increased odds of dissatisfaction after THA; and assessing pain, function, and MCS concomitantly (as phenotypes) may support identifying patients at risk for not achieving a satisfactory outcome.

The Impact of Surgeon Variability on Patient-Reported Outcomes in Total Hip Arthroplasty.

BACKGROUND: Patient-related and surgery-related factors have been shown to be drivers of outcomes after total hip arthroplasty (THA); however, the impact of intersurgeon variability is poorly understood. The purpose of this study is to assess the following: (1) overall effect of surgeon on 1-year patient-reported outcome measures (PROMs), length of stay (LOS), discharge disposition, and 90-day readmission following THA; and (2) variability in 1-year PROMs among surgeons. METHODS: A prospective cohort of 3,695 patients who underwent THA between 2016 and 2018 was included. Seventy-eight percent of patients completed 1-year follow-up. Thirty-one surgeons from a large healthcare system were included. Likelihood ratio tests analyzed the relationship among surgeon and 1-year Hip Disability and Osteoarthritis Outcome Score (HOOS)-Pain, HOOS-Physical Function Short-Form, HOOS-Joint Replacement, University of California, Los Angeles activity score, Patient Acceptable Symptom State, LOS, discharge disposition, and 90-day readmission. Mixed-effect proportional odds and logistic regression models were used to determine variable importance for each outcome. RESULTS: In total, 90.5% of patients responded positively to 1-year Patient Acceptable Symptom State. There was a significant association among surgeon and 1-year PROMs, LOS, discharge disposition (P < .001), and readmission (P = .002). For HOOS-Pain, Physical Function Short-Form, and Joint Replacement, surgeon (Akaike information criterion increase: 34.6, 18.7, 17.1, respectively) was a greater contributor to outcome than patient-level factors, including age, gender, and comorbidity. Differences in the highest and lowest median probability of achieving any given score on 1-year PROMs ranged from 11% to 18.5%. Variability was not explained by approach (P = .431) or case volume (correlation coefficient, ρ = 0.19). CONCLUSION: Surgeon-level variability appears to be a greater driver of 1-year PROMs than some patient-level characteristics. Incorporating surgeon as a variable is beneficial for model-fitting and important for increasing value in THA.

Staged Versus Simultaneous Bilateral Knee Arthroplasty: Does Minimal Cost Difference Justify Risks?

BACKGROUND: Simultaneous bilateral total knee arthroplasty (BTKA) is associated with a higher risk but can be perceived to afford faster improvement and mitigated costs versus staged BTKA. We aimed to explore (1) health care utilization, (2) surgical supply costs of simultaneous BTKA; and (3) 1-year improvement in patient-reported pain, function, and quality of life (QOL) versus staged BTKA. METHODS: A prospective cohort of 198 simultaneous and 625 staged BTKAs was obtained (2016-2020). Simultaneous BTKA cohort was propensity score-matched (1:2) to a similar group of staged patients (simultaneous = 198 versus staged = 396). Outcomes included length of stay, discharge disposition, 90-day readmission, 1-year reoperation, surgical episode supply cost, Knee Injury and Osteoarthritis Outcome Score (KOOS)-pain, KOOS-Physical Function Short Form, and KOOS-QOL. Rates of attaining minimal clinically important difference and Patient Acceptable Symptomatic State were calculated. RESULTS: Compared to both staged BTKA surgeries combined, simultaneous BTKA demonstrated shorter median net length of stay (2.00 [2.00, 3.00] days versus 2.00 [2.00, 4.00] days; P < .001) but higher rates of nonhome discharge (n = 56 [28.3%] versus n = 32 [4.04%]; P < .001), 90-day readmission (n = 20 [10.1%] versus n = 48 [6.06%]; P = .047) and similar reoperation rates (P = .44). Simultaneous BTKA afforded slight reduction in net surgical cost compared to that of both staged BTKAs combined ($643; P = .028). There was no significant difference in 1-year improvement and minimal clinically important difference attainment rates with simultaneous versus staged BTKA for KOOS-pain (P = .137 and P = .99), KOOS-QOL (P = .095 and P = .81), or KOOS-Physical Function Short Form (P = .75 and P = .49, respectively) or Patient Acceptable Symptomatic State (P = .12). CONCLUSION: Staged BTKA is associated with similar 1-year pain, function, and QOL at a better safety profile and minimal surgical supply cost increase compared to simultaneous BTKA.

Neighborhood Socioeconomic Disadvantage Associated With Increased Healthcare Utilization After Total Hip Arthroplasty.

BACKGROUND: The multifaceted effects of socioeconomic status on healthcare outcomes can be difficult to quantify. The Area Deprivation Index (ADI) quantifies a socioeconomic disadvantage with higher scores indicating more disadvantaged groups. The present study aimed to describe the ADI distribution for primary total hip arthroplasty (THA) patients stratified by patient demographics and to characterize the association of ADI with healthcare utilization (discharge disposition and length of stay [LOS]), 90-day emergency department (ED) visits, and 90-day all cause readmissions. METHODS: Two thousand three hundred and ninety one patients who underwent primary elective THA over a 13-month period were included. A multivariable binary logistic regression analysis with outcomes of nonhome discharge, prolonged LOS (>3 days), 90-day ED visits, and 90-day readmission were performed using predictors of ADI, gender, race, smoking status, body mass index, insurance status, and Charlson comorbidity index. Plots of restricted cubic splines were used to graph associations between ADI as a continuous variable and the outcomes of interest using odds ratios. RESULTS: In the multivariable regression model, there were statistically significant higher odds of nonhome discharge (OR, 1.82; 95% CI, 1.19-2.77, P = .005) for individuals in the 61-80 ADI quintile as compared to the reference group of 21-40. Individuals in the highest ADI quintile, 81-100, had the greatest odds of nonhome discharge (OR, 2.20; 95% CI, 1.39-3.49, P < .001) and prolonged LOS (OR, 1.91, 95% CI, 1.28-2.84, P = .001). CONCLUSIONS: Higher ADI is associated with an increased healthcare utilization within 90 days of THA.