You say you want to be "diverse": What are the practical steps towards increasing diversity of spine surgeons?

This article explores the critical issue of underrepresentation in spine surgery, specifically addressing racial/ethnic diversity. The paper proposes actionable strategies to enhance diversity within spine surgery through early education and outreach, intentional mentorship and sponsorship, and addressing biases in recruitment and promotion processes. It emphasizes the importance of a supportive culture within spine surgery divisions and practices, advocating for a top-down approach to inclusivity, while underscoring the necessity of continuous evaluation and adaptation of diversity initiatives. By leveraging diverse perspectives, the field of spine surgery can better serve an increasingly heterogeneous population, ultimately improving patient care and healthcare outcomes.

Social Determinants of Health and Disparities in Spine Surgery: A Ten-Year Analysis of 8,565 Cases using Ensemble Machine Learning and Multilayer Perceptron.

BACKGROUND CONTEXT: The influence of SDOH on spine surgery is poorly understood. Historically, researchers commonly focused on the isolated influences of race, insurance status, or income on healthcare outcomes. However, analysis of SDOH is becoming increasingly more nuanced as viewing social factors in aggregate rather than individually may offer more precise estimates of the impact of SDOH on healthcare delivery. PURPOSE: The aim of this study was to evaluate the effects of patient social history on length of stay (LOS) and readmission within 90 days following spine surgery using ensemble machine learning and multilayer perceptron. STUDY DESIGN: Retrospective chart review PATIENT SAMPLE: 8,565 elective and emergency spine surgery cases performed from 2013-2023 using our institution's database of longitudinally collected electronic medical record information. OUTCOMES MEASURES: Patient LOS, discharge disposition, and rate of 90-day readmission. METHODS: Ensemble machine learning and multilayer perceptron were employed to predict LOS and readmission within 90 days following spine surgery. All other subsequent statistical analysis was performed using SPSS version 28. To further assess correlations among variables, Pearson's correlation tests and multivariate linear regression models were constructed. Independent sample t-tests, paired sample t-tests, one-way analysis of variance (ANOVA) with post-hoc Bonferroni and Tukey corrections, and Pearson's chi-squared test were applied where appropriate for analysis of continuous and categorical variables. RESULTS: Black patients demonstrated a greater LOS compared to white patients, but race and ethnicity were not significantly associated with 90-day readmission rates. Insured patients had a shorter LOS and lower readmission rates compared to non-insured patients, as did privately insured patients compared to publicly insured patients. Patients discharged home had lower LOS and lower readmission rates, compared to patients discharged to other facilities. Marriage decreased both LOS and readmission rates, underweight patients showcased increased LOS and readmission rates, and religion was shown to impact LOS and readmission rates. When utilizing patient social history, lab values, and medical history, machine learning determined the top 5 most-important variables for prediction of LOS -along with their respective feature importances-to be insurance status (0.166), religion (0.100), ICU status (0.093), antibiotic use (0.061), and case status: elective or urgent (0.055). The top 5 most-important variables for prediction of 90-day readmission-along with their respective feature importances-were insurance status (0.177), religion (0.123), discharge location (0.096), emergency case status (0.064), and history of diabetes (0.041). CONCLUSIONS: This study highlights that SDOH is influential in determining patient length of stay, discharge disposition, and likelihood of readmission following spine surgery. Machine learning was utilized to accurately predict LOS and 90-day readmission with patient medical history, lab values, and social history, as well as social history alone.

Artificial Intelligence Portrayals in Orthopaedic Surgery: An Analysis of Gender and Racial Diversity Using Text-to-Image Generators.

BACKGROUND: The increasing accessibility of artificial intelligence (AI) text-to-image generators offers a novel avenue for exploring societal perceptions. The present study assessed AI-generated images to examine the representation of gender and racial diversity among orthopaedic surgeons. METHODS: Five prominent text-to-image generators (DALL·E 2, Runway, Midjourney, ImagineAI, and JasperArt) were utilized to create images for the search queries "Orthopedic Surgeon," "Orthopedic Surgeon's Face," and "Portrait of an Orthopedic Surgeon." Each query produced 80 images, resulting in a total of 240 images per generator. Two independent reviewers categorized race, sex, and age in each image, with a third reviewer resolving discrepancies. Images with incomplete or multiple faces were excluded. The demographic proportions (sex, race, and age) of the AI-generated images were then compared with those of the 2018 American Academy of Orthopaedic Surgeons (AAOS) census. RESULTS: In our examination across all AI platforms, 82.8% of the images depicted surgeons as White, 12.3% as Asian, 4.1% as Black, and 0.75% as other; 94.5% of images were men; and a majority (64.4%) appeared ≥50 years old. DALL·E 2 exhibited significantly increased diversity in representation of both women and non-White surgeons compared with the AAOS census, whereas Midjourney, Runway, and ImagineAI exhibited significantly decreased representation. CONCLUSIONS: The present study highlighted distortions in AI portrayal of orthopaedic surgeon diversity, influencing public perceptions and potentially reinforcing disparities. DALL·E 2 and JasperArt show encouraging diversity, but limitations persist in other generators. Future research should explore strategies for improving AI to promote a more inclusive and accurate representation of the evolving demographics of orthopaedic surgery, mitigating biases related to race and gender. CLINICAL RELEVANCE: This study is clinically relevant as it investigates the accuracy of AI-generated images in depicting diversity among orthopaedic surgeons. The findings reveal significant discrepancies in representation by race and gender, which could impact societal perceptions and exacerbate existing disparities in health care.

Current Orthopaedic Residency Letters of Recommendation Are Not Biased by Gender of Applicant.

Letters of recommendation (LORs) are highly influential in the residency selection process. Differences in language and length of LORs by gender have been demonstrated for applicants applying to surgical residencies and fellowships. This had yet to be studied in orthopaedic surgery. Given the gender disparity in the field, we sought to investigate the impact of gender on orthopaedic residency applicant LORs. We hypothesized that differences in length and language would be present for women applicants as compared to men. METHODS: LORs for 2019 to 2020 applicants who applied to a single academic institution were selected for review. Female and male applicants were matched by medical school attended and United States Medical Licensing Examination Step 1 score. LORs were analyzed using both qualitative and quantitative analyses. Letters were evaluated for their word count, presence of language terms, and frequency of language terms. A similar subgroup language analysis was performed for standardized LORs (SLORs). RESULTS: Six hundred fifty-six applicants met the initial screening criteria-126 women and 530 men. After matching, 71 female applicants were paired with 111 male applicants. Word count was, on average, longer for female applicants. LORs for female applicants were more likely to contain language terms that characterized their ability, achievement, participation in athletics, awards received, fit, leadership, and personality traits. Of these terms, ability and participation in athletics were also found more frequently in LORs written for women. In addition, language characterizing technical skills was found more frequently in LORs of female applicants. Similar codes were found to be statistically significant in the SLOR subgroup analysis. CONCLUSION: This study highlights that current orthopaedic surgery residency LORs do not appear to be biased by applicant gender. LORs were longer for female applicants and described them more positively. Future female orthopaedic residency applicants should be assured that current female candidates are applying with at least similar if not greater subjective qualifications to their male counterparts based on the findings of this study.

Do Medicare Accountable Care Organizations Reduce Disparities After Spinal Fracture?

BACKGROUND: National changes in health care disparities within the setting of trauma care have not been examined within Accountable Care Organizations (ACOs) or non-ACOs. We sought to examine the impact of ACOs on post-treatment outcomes (in-hospital mortality, 90-day complications, and readmissions), as well as surgical intervention among whites and nonwhites treated for spinal fractures. MATERIALS AND METHODS: We identified all beneficiaries treated for spinal fractures between 2009 and 2014 using national Medicare fee for service claims data. Claims were used to identify sociodemographic and clinical criteria, receipt of surgery and in-hospital mortality, 90-day complications, and readmissions. Multivariable logistic regression analysis accounting for all confounders was used to determine the effect of race/ethnicity on outcomes. Nonwhites were compared with whites treated in non-ACOs between 2009 and 2011 as the referent. RESULTS: We identified 245,704 patients who were treated for spinal fractures. Two percent of the cohort received care in an ACO, whereas 7% were nonwhite. We found that disparities in the use of surgical fixation for spinal fractures were present in non-ACOs over the period 2009-2014 but did not exist in the context of care provided through ACOs (odds ratio [OR] 0.75; 95% confidence interval [CI] 0.44, 1.28). A disparity in the development of complications existed for nonwhites in non-ACOs (OR 1.09; 95% CI 1.01, 1.17) that was not encountered among nonwhites receiving care in ACOs (OR 1.32; 95% CI 0.90, 1.95). An existing disparity in readmission rates for nonwhites in ACOs over 2009-2011 (OR 1.34; 95% CI 1.01, 1.80) was eliminated in the period 2012-2014 (OR 0.85; 95% CI 0.65, 1.09). CONCLUSIONS: Our work reinforces the idea that ACOs could improve health care disparities among nonwhites. There is also the potential that as ACOs become more familiar with care integration and streamlined delivery of services, further improvements in disparities could be realized.

Changes in healthcare delivery following spinal fracture in Medicare Accountable Care Organizations.

BACKGROUND CONTEXT: Accountable Care Organizations (ACOs) were designed to reduce healthcare costs while simultaneously improving quality. Given that the success of ACOs is predicated on controlling costs, concerns have been expressed that patients could be adversely affected through restricted access to surgery, including in the context of spine fracture care. PURPOSE: Evaluate the impact of Medicare ACO formation on the utilization of surgery and outcomes following spinal fractures. STUDY DESIGN: Retrospective review of Medicare claims (2009-2014). PATIENT SAMPLE: Patients treated for spinal fractures in an ACO or non-ACO. OUTCOME MEASURES: The utilization of surgery as treatment for spinal fractures, in-hospital mortality, 90-day complications, or hospital readmission within 90-days injury. METHODS: We used a pre-post study design to compare outcomes for patients treated in ACOs versus non-ACOs. Receipt of surgery for treatment of a spinal fracture was the primary outcome, with mortality, complications and readmissions treated secondarily. We used multivariable logistic regression adjusting for confounders to determine the association between environment of care (ACO vs. non-ACO) and the outcomes of interest. In all testing, beneficiaries treated in non-ACOs during 2009 to 2011 were used as the referent. RESULTS: During 2009 to 2011, 9% (n=10,866) of patients treated in non-ACOs received surgery, whereas a similar percentage (9%; n=210) underwent surgery in ACOs. This figure decreased to 8% (n=9,857) for individuals treated in non-ACOs over 2012 to 2014, although the surgical rate remained unchanged for those receiving care in an ACO (9%; n=227). There was no difference in the use of surgery among patients treated in ACOs (OR 0.96; 95% CI 0.79, 1.18) over 2012 to 2014. Similar increases in the odds of mortality were observed for both ACOs and non-ACOs during this period. A marginal, yet significant increase in complications was observed among ACOs, although there was no change in the odds of readmission. CONCLUSIONS: Our study found that the formation of ACOs did not result in alterations in the use of surgery for spinal fractures or substantive changes in outcomes. As ACOs continue to evolve, more emphasis should be placed on the incorporation of measures directly related to surgical and trauma care in the determinants of risk-based reimbursements.