The Impact of Race, Ethnicity, and Sex on Fairness in Artificial Intelligence for Glaucoma Prediction Models.

Objective: Despite advances in artificial intelligence (AI) in glaucoma prediction, most works lack multicenter focus and do not consider fairness concerning sex, race, or ethnicity. This study aims to examine the impact of these sensitive attributes on developing fair AI models that predict glaucoma progression to necessitating incisional glaucoma surgery. Design: Database study. Participants: Thirty-nine thousand ninety patients with glaucoma, as identified by International Classification of Disease codes from 7 academic eye centers participating in the Sight OUtcomes Research Collaborative. Methods: We developed XGBoost models using 3 approaches: (1) excluding sensitive attributes as input features, (2) including them explicitly as input features, and (3) training separate models for each group. Model input features included demographic details, diagnosis codes, medications, and clinical information (intraocular pressure, visual acuity, etc.), from electronic health records. The models were trained on patients from 5 sites (N = 27 999) and evaluated on a held-out internal test set (N = 3499) and 2 external test sets consisting of N = 1550 and N = 2542 patients. Main Outcomes and Measures: Area under the receiver operating characteristic curve (AUROC) and equalized odds on the test set and external sites. Results: Six thousand six hundred eighty-two (17.1%) of 39 090 patients underwent glaucoma surgery with a mean age of 70.1 (standard deviation 14.6) years, 54.5% female, 62.3% White, 22.1% Black, and 4.7% Latinx/Hispanic. We found that not including the sensitive attributes led to better classification performance (AUROC: 0.77-0.82) but worsened fairness when evaluated on the internal test set. However, on external test sites, the opposite was true: including sensitive attributes resulted in better classification performance (AUROC: external #1 - [0.73-0.81], external #2 - [0.67-0.70]), but varying degrees of fairness for sex and race as measured by equalized odds. Conclusions: Artificial intelligence models predicting whether patients with glaucoma progress to surgery demonstrated bias with respect to sex, race, and ethnicity. The effect of sensitive attribute inclusion and exclusion on fairness and performance varied based on internal versus external test sets. Prior to deployment, AI models should be evaluated for fairness on the target population. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Dynamic evaluation of China's atmospheric environmental pressure from 2008 to 2017: Trends and drivers.

Evaluating the pressure of atmospheric pollutant emissions on the atmospheric environment is crucial for effective pollution control and emission reduction policies. This study introduces a novel Atmospheric Environmental Pressure Index (AEPI) and employs a dynamic comprehensive method to evaluate China's Atmospheric Environmental Pressure (AEP) across 31 provinces from 2008 to 2017. The drivers of AEP were analyzed using a spatial panel data model, uncovering the integral role of pollution reduction policies, particularly the Air Pollution Prevention and Control Action Plan, which led to a 25% reduction in AEP during its enforcement. Our findings reveal significant spatial disparities in AEP, with higher levels in the Beijing-Tianjin-Hebei and Yangtze River Delta regions. The regression analysis identifies economic development, industrial structure, energy efficiency, environmental regulations, and urbanization as key influencing factors, though their impacts vary across different regions, suggesting the need for region-specific pollution control policies. Furthermore, the shift in the AEP gravity center from 2008 to 2017 indicated a southeastward movement, suggesting the necessity to focus air pollution control efforts on the southeast provinces. In conclusion, the AEPI developed in this study enables comparative analysis of AEP across different regions and facilitates the monitoring of long-term trends, which is valuable in guiding regional air pollution control in China.

Associations Among Circle-Based Kidney Allocation, Center Waiting Time, and Likelihood of Deceased-Donor Kidney Transplantation.

RATIONALE & OBJECTIVE: The kidney allocation system (KAS250), using circle-based distribution, attempts to address geographic disparities through broader sharing of deceased-donor kidney allografts. This study sought to evaluate the association between KAS250 and likelihood of deceased-donor kidney transplantation (DDKT) among waitlisted candidates, and whether the policy has differentially affected centers with shorter vs. longer waiting time. STUDY DESIGN: Retrospective cohort study. SETTING: & Participants: 160,941 candidates waitlisted at 176 transplant centers between 3/2017-3/2024. EXPOSURE: KAS250 allocation policy. OUTCOME: Rate of DDKT. ANALYTICAL APPROACH: Multivariable Cox regression, modeling KAS250 as a time-dependent variable. RESULTS: KAS250 was not independently associated with likelihood of DDKT overall (HR=1.01 vs. pre-KAS250, 95% C.I. 0.97-1.04). KAS250's association with likelihood of DDKT varied across centers from HR=0.18 (DDKT less likely after KAS250) to HR=17.12 (DDKT more likely) and varied even among neighboring centers. KAS250 was associated with decreased DDKT at 25.6% and increased DDKT at 18.2% of centers. Centers with previously long median waiting times (57+ months) experienced increased likelihood of DDKT after KAS250 (HR=1.20, 95% C.I. 1.15-1.26), whereas centers with previously short median waiting times (6-24mo.; HR=0.88, 0.84-0.92) experienced decreased likelihood of DDKT. LIMITATIONS: Retrospective study of allocation policy changes, confounded by multiple changes over the study timeframe. CONCLUSION: Association between KAS250 and DDKT varied across centers. For one-in-four centers, DDKT was less likely after KAS250 relative to pre-KAS250 trends. Candidates at centers with previously long waiting times experienced increased likelihood of DDKT after KAS250. Thus, broader distribution of kidneys may be associated with improved equity in access to DDKT, but additional strategies may be needed to minimize disparities between centers.

A Tool to Help Nurses Provide Health Education on Adverse Pregnancy Outcomes and Cardiovascular Health.

Adverse pregnancy outcomes are associated with poor short- and long-term cardiovascular health. However, patients and their health care providers may not have knowledge of this risk or of the healthful practices that can reduce this risk. Childbirth care can be a pivotal time in the patient-clinician relationship to build awareness and spur prevention planning. As part of the American Heart Association-supported program entitled Providing an Optimized and Empowered Pregnancy for You (P3OPPY), our team collaborated with a community advisory board to create a teaching handout about adverse pregnancy outcomes for incorporation into hospital-based postpartum care. This handout can be used by pregnancy and maternity care providers, including postpartum nurses, to provide health education on how adverse pregnancy outcomes can influence risk for future cardiovascular disease and what can be done for prevention.

Patterns and trends in melanoma mortality in Spain (1999-2022).

AIM: To examine melanoma mortality trends in Spanish Autonomous Communities from 1999 to 2022, focusing on gender and age differences. METHODS: Data from the National Statistics Institute were used to calculate age-standardized mortality rates (ASMRs). Joinpoint regression identified trend changes. RESULTS: Melanoma mortality varied significantly by region, gender, and age. Eastern Spain had higher male mortality, while western regions had lower rates. Asturias had higher female mortality, with lower rates in Andalusia, Extremadura, and Castilla-La Mancha. Men generally exhibited higher ASMRs than women, with variations across regions. While ASMRs remained stable in most areas, Madrid experienced a notable decline (AAPC: - 1.3%). A national trend reversal occurred in 2014 (AAPC: - 1.3%). For individuals aged 45-74 years, Catalonia saw a significant decrease (AAPC: - 1.1%, p < 0.05), whereas Andalusia experienced an increase (APC: 2.1% since 2007). Nationally, ASMRs for this age group declined (AAPC: - 0.7%). Among those aged 75 years and over, ASMRs varied considerably, with increases observed in Andalusia and Aragon. Nationally, male ASMRs rose (AAPC: 1.6% per year), while female rates were stable. Regional disparities were evident, with higher female mortality in the Balearic Islands and fluctuating rates in the Community of Madrid (an increase followed by a decrease after 2015). The gender gap in mortality varied across regions, with some areas showing a narrowing gap and others widening disparities. CONCLUSION: Continuous monitoring of melanoma mortality, especially among men and older adults, is crucial. Public health efforts should address regional disparities, improve early detection, and enhance treatment access to optimize outcomes nationwide.

Racial Biases Associated With Pulse Oximetry: Longitudinal Social Network Analysis of Social Media Advocacy Impact.

BACKGROUND: Pulse oximetry is a noninvasive method widely used in critical care and various clinical settings to monitor blood oxygen saturation. During the COVID-19 pandemic, its application for at-home oxygen saturation monitoring became prevalent. Further investigations found that pulse oximetry devices show decreased accuracy when used on individuals with darker skin tones. This study aimed to investigate the influence of X (previously known as Twitter) on the dissemination of information and the extent to which it raised health care sector awareness regarding racial disparities in pulse oximetry. OBJECTIVE: This study aimed to explore the impact of social media, specifically X, on increasing awareness of racial disparities in the accuracy of pulse oximetry and to map this analysis against the evolution of published literature on this topic. METHODS: We used social network analysis drawing upon Network Overview Discovery and Exploration for Excel Pro (NodeXL Pro; Social Media Research Foundation) to examine the impact of X conversations concerning pulse oximetry devices. Searches were conducted using the Twitter Academic Track application programming interface (as it was known then). These searches were performed each year (January to December) from 2012 to 2022 to cover 11 years with up to 52,052 users, generating 188,051 posts. We identified the nature of influencers in this field and monitored the temporal dissemination of information about social events and regulatory changes. Furthermore, our social media analysis was mapped against the evolution of published literature on this topic, which we located using PubMed. RESULTS: Conversations on X increased health care awareness of racial bias in pulse oximetry. They also facilitated the rapid dissemination of information, attaining a substantial audience within a compressed time frame, which may have impacted regulatory action announced concerning the investigation of racial biases in pulse oximetry. This increased awareness led to a surge in scientific research on the subject, highlighting a growing recognition of the necessity to understand and address these disparities in medical technology and its usage. CONCLUSIONS: Social media platforms such as X enabled researchers, health experts, patients, and the public to rapidly share information, increasing awareness of potential racial bias. These platforms also helped connect individuals interested in these topics and facilitated discussions that spurred further research. Our research provides a basis for understanding the role of X and other social media platforms in spreading health-related information about potential biases in medical devices such as pulse oximeters.

Implementing the Early Start Denver Model in Senegal: Outcomes and Insights from a Low-Resource Context.

BACKGROUND: Autism Spectrum Disorders (ASD) are characterized by significant challenges in social interaction and communication, accompanied by repetitive behaviors. Effective early interventions, such as the Early Start Denver Model (ESDM) are crucial but primarily studied in well-resourced Western countries. This study explores the adaptation and effectiveness of ESDM in Senegal, a low-resource setting, to adress gaps in autism care and intervention accessibility in Africa. SUBJECTS AND METHODS: An observational study was conducted at Diamniadio Children's Hospital, Dakar, Senegal, from January 2019 to July 2021, focusing on children under 10 years suspected of having ASD. Diagnostic assessments were performed using the DSM-5 criteria with tools like the Autism Diagnostic Interview-Revised (ADI-R) and Autism Diagnostic Observation Schedule, Second Edition (ADOS-2). Interventions based on ESDM were adapted to local resources and involved regular family and patient engagement. RESULTS: Of the 114 children referred for ASD suspicion, 80 were diagnosed with ASD. Post-diagnosis, 30 children received follow-up care at the day hospital, and another 30 were managed via outpatient care. 20 children did not receive any follow-up care at Diamniadio Children's Hospital. Significant socio-economic disparities were noted, influencing access to and engagement with intervention programs. No significant differences were found in clinical characteristics between groups, but socio-economic factors significantly affected intervention access. CONCLUSION: The adapted ESDM interventions show promise for implementation in resource-limited settings like Senegal, although challenges related to socio-economic disparities and service accessibility persist. Future research should focus on the integration of ASD services into broader health policies to enhance efficacy and accessibility.

Racial and ethnic disparities in treatment refusal for head and neck cutaneous malignancies.

Racial and ethnic minorities with skin cancer experience disproportionately worse prognoses and adverse outcomes compared to non-Hispanic, White patients. We analyzed patients diagnosed with any cutaneous malignancies of the head and neck between 2010 to 2021 using the data from the National Cancer Database to quantify disparities. The primary outcome variable was treatment refusal, and secondary variables included days from diagnosis to treatment, tumor depth, and mortality. Among the 151,733 patients analyzed, most were non-Hispanic White (99%) and male (71%). Black patients had the greatest odds of treatment refusal (4.166, 95% CI: 2.054-8.452, p < 0.001) across all cutaneous malignancies of the head and neck. Black and Hispanic patients also had increased times from diagnosis to treatment (p < 0.001). Black patients had higher odds of 90-day mortality compared to non-Hispanic White patients (p < 0.001). This coincided with greater tumor depth in Black and Hispanic patients compared to that of non-Hispanic White patients (p < 0.001). Black patients were more likely to refuse treatment for head and neck cutaneous malignancies. Moreover, Black and Hispanic patients experienced more treatment delays. These findings may relate to the increased 90-day mortality among Black patients and increased tumor depth in Black and Hispanic patients. Further investigation into the quality of life and functional impairment is warranted alongside interventions to reduce these disparities.

Gender and Racial Demographic Trends in the US Laryngology Workforce (1993-2022).

OBJECTIVES: To analyze demographic trends in laryngology fellowship training in the United States from 1993 to 2022, comparing periods before and after formalization of the fellowship within the National Resident Matching Program (NRMP) in 2012. METHODS: A national database of fellowship-trained laryngologists (FTLs) and non-fellowship-trained laryngologists (nFTLs) practicing primarily laryngology was created by methodically compiling laryngologists via Internet search, with corroboration by regional laryngologists and vetting by senior laryngologists on this manuscript. Demographic variables included residency and/or fellowship graduation year, gender, race and ethnicity inferred through individuals' photos and surnames. NRMP match data from 2012 to 2022 were obtained from the American Laryngological Association. RESULTS: An average of 21 programs offered 23 positions in the NRMP match, with 14 programs (66.4%) filling 16 positions (68.8%) from 2012 to 2022. The 10-year FTL growth rate decreased from 25.4% (1993-2002) to 10.5% and 6.6% in subsequent periods. In May 2023, there were 349 active laryngologists, including 303 FTLs, in the United States. A total of 189 (62.4%) FTLs were men, 114 (37.6%) were women; 201 (66.2%) were White, 102 (33.8%) were non-White. Between the pre-NRMP and post-NRMP periods, the percentage of male FTLs decreased from 71.5% to 55.5%, female FTLs increased from 28.5% to 44.5%, and White FTLs decreased from 69.2% to 64.2%. Chi-squared analysis yielded a statistically significant association between gender and training period for FTLs (p = 0.004), but no statistically significant difference between race and training period. CONCLUSIONS: The post-NRMP period saw an expansion of laryngology fellowships and workforce diversification, reflecting trends observed in otolaryngology and medicine overall. LEVEL OF EVIDENCE: NA Laryngoscope, 2024.

Economic evaluations of interventions addressing inequalities in cancer care: A systematic review.

OBJECTIVE: Although substantial evidence exists on the costs and benefits of cancer care and screening programs for the general population, economic evidence of interventions addressing inequalities is less well known. This systematic review summarised economic evaluations of interventions addressing inequalities in cancer screening and care to inform decision-makers on the value for money of such interventions. METHODS: Embase, Medline, Cochrane Library, EconLit and Scopus databases were searched for studies published from database inception to 27th October 2023. Studies were eligible for inclusion if they were economic evaluations of interventions to improve or address inequalities in cancer care among disadvantaged population groups. Study characteristics and cost-effectiveness results (USD 2023) were summarised. Study quality was assessed by two authors using the Drummond Checklist. RESULTS: The searches yielded 2,937 records, with 30 meeting the eligibility criteria for data extraction. In most (n=27, 90%) of the studies, interventions were considered cost-effective in addressing inequalities in cancer care and screening among disadvantaged populations. Sixty per cent of the studies were rated as high quality, 33.3% as good, and 6.7% as fair quality. CONCLUSION: This systematic review identified cost-effective strategies addressing inequalities in cancer screening and care that have the potential to be replicated in other locations. The interventions were mainly focused on screening programs, and few addressed equity gaps around risk reduction and diagnostic and treatment outcomes. This underscores the need for targeted approaches to address inequalities in under-researched priority population groups along the cancer care continuum.

Health Disparities Across the Spectrum of Amputation Care: A Review of Literature.

Limb loss is a common and disabling experience for patients, frequently caused by critical limb ischemia or deterioration of chronic wounds. Disparities in outcomes for prevention of amputation, level of amputation, and postamputation outcomes have been described. Understanding the nature of these disparities and the populations most affected can help clinicians and policymakers target interventions and programs. This article reviews existing literature regarding disparities in amputation care, including prevention methods, surgical outcomes, and postamputation outcomes. The authors identified several potential racial, socioeconomic, and gender disparities, particularly affecting Black, Native American, and Latino/a/x patients, female gender, and those in rural settings.

Sex-Based Survival Outcomes in Cardiogenic Shock.

BACKGROUND: Sex-based disparities have been demonstrated in care delivery for females with cardiogenic shock (CS), including lower use of coronary angiography (CAG), percutaneous intervention (PCI) and mechanical circulatory support (MCS). We evaluated whether sex-based disparities exist and are associated with worse CS outcomes in females. METHODS: We studied a retrospective cohort of 1498 consecutive, unique adult cardiovascular intensive care unit (CICU) admissions with CS from 2007-2018. RESULTS: Compared to males, females (n = 566, 37.1%) were older (71.7 vs 67.8 years; P < 0.001) but had similar burdens of medical comorbidities. Acute myocardial infarction (AMI) was present in 54.1% of females and 59.1% of males (P = 0.06). There were no sex-based differences in the use of CAG and PCI, but females received temporary MCS less commonly. Specifically, females with non-AMI CS received MCS devices less commonly (17.6% vs 24.4%; P = 0.04). There was no difference in in-hospital or 1-year mortality rates between the sexes. Compared to males, females who received PCI had lower risks of 1-year mortality (unadjusted HR 0.72; P = 0.03), whereas females who received CAG without PCI had higher risks of 1-year mortality (unadjusted HR 1.41; P = 0.02). CONCLUSIONS: No sex-based disparities in mortality due to CS were demonstrated in this large, diverse cohort of patients with CICU admissions. Females who underwent PCI demonstrated lower risks of 1-year mortality, whereas females who underwent CAG without PCI demonstrated higher risks of 1-year mortality compared to males. This may reflect underuse of PCI as a mortality-reducing therapy in females.

Discrimination and sleep disturbance among older Black Americans: A longitudinal analysis of the Health and Retirement Study.

OBJECTIVES: Black and older adults have higher risk for sleep problems than their White and younger counterparts. Yet, our understanding of the determinants of sleep problems specifically among older Black adults is severely limited. The aim of this study was to determine whether everyday and major discrimination are longitudinally associated with sleep disturbance in a nationally representative sample of older Black adults. METHODS: Non-Latinx Black respondents aged 51+ were selected from waves 8 (2006) through 15 (2020) of the Health and Retirement Study (baseline N = 1397). Sleep disturbance was measured with the 4-item Jenkins Sleep Questionnaire. The 6-item Everyday Discrimination Scale was used to measure everyday discrimination, and the Major Experiences of Discrimination Scale was used to measure major discrimination. Analyses controlled for sociodemographics, health behaviors, and health conditions. Lagged mixed-effects linear regression models were performed to test the longitudinal associations between baseline discrimination and sleep disturbance over 12years. RESULTS: Higher baseline everyday discrimination was longitudinally associated with more severe sleep disturbance. Compared to respondents who reported no major discrimination at baseline, those who reported two or more major discrimination experiences had more severe sleep disturbance over time. CONCLUSIONS: This study provides critical information on the possible longitudinal drivers of sleep disparities at the population level. This information has implications for better understanding the mechanisms of health disparities and for attaining health equity.

Machine learning applications in studying mental health among immigrants and racial and ethnic minorities: an exploratory scoping review.

BACKGROUND: The use of machine learning (ML) in mental health (MH) research is increasing, especially as new, more complex data types become available to analyze. By examining the published literature, this review aims to explore the current applications of ML in MH research, with a particular focus on its use in studying diverse and vulnerable populations, including immigrants, refugees, migrants, and racial and ethnic minorities. METHODS: From October 2022 to March 2024, Google Scholar, EMBASE, and PubMed were queried. ML-related, MH-related, and population-of-focus search terms were strung together with Boolean operators. Backward reference searching was also conducted. Included peer-reviewed studies reported using a method or application of ML in an MH context and focused on the populations of interest. We did not have date cutoffs. Publications were excluded if they were narrative or did not exclusively focus on a minority population from the respective country. Data including study context, the focus of mental healthcare, sample, data type, type of ML algorithm used, and algorithm performance were extracted from each. RESULTS: Ultimately, 13 peer-reviewed publications were included. All the articles were published within the last 6 years, and over half of them studied populations within the US. Most reviewed studies used supervised learning to explain or predict MH outcomes. Some publications used up to 16 models to determine the best predictive power. Almost half of the included publications did not discuss their cross-validation method. CONCLUSIONS: The included studies provide proof-of-concept for the potential use of ML algorithms to address MH concerns in these special populations, few as they may be. Our review finds that the clinical application of these models for classifying and predicting MH disorders is still under development.

Disparities in infectious disease-related health care utilization between Medicaid-enrolled American Indians and non-Hispanic Whites-Lessons from the first 16 months of coronavirus disease 2019 and a decade of flu seasons.

OBJECTIVE: To understand why American Indian and Alaskan Native (AIAN) populations have had exceptionally high COVID-19 mortality, we compare patterns of healthcare utilization and outcomes for two serious infectious respiratory diseases-Influenza-like-illness (ILI) and coronavirus disease 2019 (COVID-19)-between American Indian and Alaskan Native (AIAN) populations (as identified in Medicaid data) and non-Hispanic Whites over the 2009-2021 period. STUDY SETTING AND DESIGN: We select all people under the age of 65 years identified as non-Hispanic White or AIAN in the New York State Medicaid claims data between 2009 and 2021. We analyze data across 10 ILI cohorts (between September 2009 and August 2020) and 4 COVID-19 cohorts (March-June 2020, July-September 2020, October-December 2020, and January-June 2021). We examine mortality and utilization rates using logistic regressions, adjusting for demographic characteristics, prior chronic conditions, and geographic location (including residence near a reservation). We stratify the analysis by rural vs. nonrural counties. DATA SOURCES AND ANALYTIC SAMPLE: We use the New York State Medicaid claims data for the analysis. PRINCIPAL FINDINGS: We find that even among Medicaid beneficiaries, who are similar in socioeconomic status and identical in health insurance coverage, AIAN populations have much lower rates of use of outpatient services and much higher rates of acute (inpatient and emergency room) service utilization for both ILI and COVID-19 than non-Hispanic Whites. Prior to COVID-19, demographic and health status-adjusted all-cause mortality rates, including from ILI, were lower among American Indians than among non-Hispanic Whites on New York State Medicaid, but this pattern reversed during the COVID-19 pandemic. Both findings are driven by nonrural counties. We did not observe significant differences in all-cause mortality and acute service utilization comparing AIAN to non-Hispanic Whites in rural areas. CONCLUSION: The utilization and mortality disparities we identify within the Medicaid population highlight the need to move beyond insurance in addressing poor health outcomes in the American Indian population.

Prevalence and trends of autism spectrum disorder and other developmental disabilities among children and adolescents in the United States from 2019 to 2021.

Background: The National Health Interview Survey (NHIS) is a comprehensive health survey conducted by the National Center for Health Statistics (NCHS) in the U.S., providing valuable insights into the health status of the population. This study focuses on the NHIS child survey between 2019 and 2021, exploring developmental disabilities in U.S. children, including autism spectrum disorder (ASD), attention deficit/hyperactivity disorder or attention-deficit disorder (ADHD/ADD), intellectual disability (ID), other developmental delay (other DD), and learning disability (LD). Objective: Leveraging NHIS data, our primary objective is to investigate the latest trends and disparities in the prevalence of developmental disabilities among various racial-ethnic groups. Methods: Employing a repeated cross-sectional design, we analyzed NHIS data from 2019 to 2021, focusing on children aged 3-17. The survey employed a meticulous stratified multi-stage sampling design. We utilized SAS version 9.4 for data analysis, calculating race-ethnicity-specific prevalence rates and employing weighted linear regression and the Rao-Scott chi-square test for trend analysis. Results: Among 19,490 children, prevalence rates varied: ASD (3.11%), ADHD/ADD (9.50%), ID (1.85%), other DD (5.66%), and LD (7.49%). Non-Hispanic black children exhibited higher rates of ID and LD, while non-Hispanic white children had the highest ADHD/ADD prevalence. Disparities persisted across sociodemographic subgroups, with variations in prevalence rates. Conclusion: Our study reveals an increase in ASD prevalence and persistent disparities among racial-ethnic groups. Non-Hispanic black children face elevated risks of ID and LD, while non-Hispanic white children exhibit higher rates of ADHD/ADD.

Adaptation of a Tailored Lung Cancer Screening Decision Aid for People With HIV.

BACKGROUND: People with HIV are both at elevated risk of lung cancer and at high risk of multimorbidity, which makes shared decision-making (SDM) for lung cancer screening (LCS) in people with HIV complex. Currently no known tools have been adapted for SDM in people with HIV. RESEARCH QUESTION: Can an SDM decision aid be adapted to include HIV-specific measures with input from both people with HIV and their providers? STUDY DESIGN AND METHODS: This study used qualitative methods including focus groups of people with HIV and interviews with HIV care providers to adapt and iterate an SDM tool for people with HIV. Eligible participants were those with HIV enrolled in an HIV primary care clinic who met age and smoking eligibility criteria for LCS and HIV care providers at the clinic. Both the focus groups and interviews included semistructured discussions of SDM and decision aid elements for people with HIV. We used a framework-guided thematic analysis, mapping themes onto the Health Equity Implementation framework. RESULTS: Forty-three people with HIV participated in eight focus groups; 10 providers were interviewed. Key themes from patients included broad interest in adapting LCS SDM specifically for people with HIV, a preference for clear LCS recommendations, and the need for positive framing emphasizing survival. Providers were enthusiastic about personalized LCS risk assessments and point-of-care tools. Both patients and providers gave mixed views on the usefulness of HIV-specific risk measures in patient-facing tools. Themes were used to adapt a personalized and flexible SDM tool for LCS in people with HIV. INTERPRETATION: People with HIV and providers were enthusiastic about specific tools for SDM that are personalized and tailored for people with HIV, that make recommendations, and that inform LCS decision-making. Divergent views on presenting patient-facing quantitative risk assessments suggests that these elements could be optional but available for review. This tool may have usefulness in complex decision-making for LCS in this population and currently is being evaluated in a pilot prospective trial.

Health disparities and climate change in the Marshall Islands.

The small island nations, territories, and states dotting the Pacific are among the most disproportionately affected populations worldwide in the face of climate change. Sea level rise coupled with increased tropical storms contribute to seawater incursion, flooding, personal injury, trauma, and death. They face an existential threat due to the consequences of global warming, specifically ice melt resulting in sea level rise, repercussions for which they are not historically culpable. Along with these environmental threats, Pacific Island communities are further burdened with high rates of adverse health conditions such as diabetes and obesity yet have limited healthcare resources due to minimal economic development. The Republic of the Marshall Islands (RMI) has one of the highest amputation rates worldwide due to advanced diabetes from lifestyle factors, limited healthcare infrastructure, financial disparities, and a culturally based hesitancy to seek medical attention, all of which lead to an increased incidence of diabetic complications. Challenges posed by non-communicable chronic diseases include diabetes and infectious diseases like tuberculosis, hepatitis, malaria, and Zika. Just as crucial to the narrative of the Marshallese people is a fundamental indigenous knowledge of their surroundings and an inseparable relationship to the environment, aquatic animals, and communities around them, denoting a holistic living system. Though the outlook is precarious, solutions centering on lifestyle interventions that are informed by Indigenous cultural strengths can provide a responsive framework and a ray of hope, offering potential solutions to these two. This short perspective highlights the RMI as a case study of the challenges the Pacific Island nations bear, from a legacy of annexation to the modern threat of climate change, compounded by health disparities.