BACKGROUND: Recent research highlighting a shortage of pediatric subspecialists in the United States has shown wide variations in the distance from children to the nearest subspecialists but has not accounted for subspecialty outreach clinics, in which specialists may improve access in rural areas by periodically staffing clinics there. This study aimed to determine the impact of pediatric subspecialty outreach clinics on the driving times to the nearest pediatric subspecialists for children in Maine.
METHODS: This cross-sectional study utilized administrative data on the schedule and location of pediatric subspecialty clinics in Maine in 2022 to estimate the driving time from each ZIP-code tabulation area to the nearest subspecialist, with and without the inclusion of outreach clinics. Using 2020 census data, we calculated the median and interquartile ranges of driving times for the state\'s overall child population, as well as for children living in urban and rural areas.
RESULTS: Of 207,409 individuals under 20 years old in Maine, 68% were located closer to an outreach location than to a clinical hub. Across the seven subspecialties offering outreach clinics, outreach clinics decreased median driving times to the nearest pediatric subspecialist by 5 to 26 minutes among all children, and by 16 to 46 minutes among rural children.
CONCLUSIONS: Pediatric subspecialty outreach clinics can substantially reduce the driving time to the nearest pediatric subspecialist , especially for children living in rural areas. The use of outreach clinics should be accounted for in research describing the geographic access or barriers to care. Expanding the number of outreach clinics should be considered by policymakers hoping to improve access.

UNASSIGNED: The purpose of the study was to investigate the relationship between community-level variables and emergency department (ED) visit rates before and during COVID-19. The focus was on opioid-related ED visits. Despite large declines in overall ED visits during COVID-19, opioid-related visits increased. While visits for avoidable conditions decreased, the opposite was true for opioid-related visits.
UNASSIGNED: We combined data from Florida EDs with community-level variables from the 2020 American Community Survey. The outcome measures of the study were quarterly ZIP code tabulation-area-level ED visit rates for opioid-related ED visits as well as visit rates for all other causes. Associations with opioid-related visit rates were estimated before and during COVID-19.
UNASSIGNED: The associations between community-level variables and opioid-related visit rates did not match those found when analyzing overall ED visit rates. The increase in opioid-related visits during COVID-19 was not unique to or more prevalent in areas with a larger percentage of racial/ethnic minority populations. However, socioeconomic status was important, as areas with higher unemployment, lower income, lower home ownership, and higher uninsured had higher overall ED visit rates and opioid visit rates during the pandemic. In addition, the negative association with income increased during the pandemic.
UNASSIGNED: These results suggest socioeconomic status should be the focus of prevention and treatment efforts to reduce opioid-related visits in future pandemics. Healthcare organizations can use these results to target their prevention and treatment efforts during future pandemics.

UNASSIGNED: Transthyretin amyloid cardiomyopathy (ATTR-CM) is associated with significant mortality. The Val122Ile variant, highly prevalent in Black patients, portends poorer survival compared with other ATTR-CM subtypes. Although Val122Ile is biologically more aggressive, the contribution of race and socioeconomic status (SES) to disease outcomes in patients with ATTR-CM is undefined.
UNASSIGNED: The aim of this study was to evaluate the impact of race and SES on clinical outcomes in patients with ATTR-CM.
UNASSIGNED: Patients with ATTR-CM who received care at Johns Hopkins Hospital between 2006 and 2022 were included. SES was assessed using area deprivation index (ADI). Associations of race and ADI with heart failure (HF) hospitalization and/or death were measured using multivariable logistic or Cox proportional hazards models.
UNASSIGNED: Of 282 patients, 225 (80%) were men, and 129 (46%) were Black. Black vs White patients disproportionately constituted the highest ADI (most deprived) category (66% vs 28%; P = 0.004), and Black patients were more likely to have HF hospitalization or death over 5 years compared with White patients (log-rank P < 0.001). Among those with ADI >25, Black patients had a significantly greater hazard of HF hospitalization or death compared with White patients, independent of disease stage at diagnosis (HR: 2.77; 95% CI: 1.45-5.32; P = 0.002).
UNASSIGNED: Black patients with low SES may be at greater risk for underdiagnosis and adverse outcomes compared with White patients. Ongoing efforts are needed to improve outcomes in this subset of patients with ATTR-CM.

UNASSIGNED: HPV is responsible for most cervical, oropharyngeal, anal, vaginal, and vulvar cancers. The HPV vaccine has decreased cervical cancer incidence, but only 49% of Texas adolescents have initiated the vaccine. Texas shows great variation in HPV vaccination rates. We used geospatial analysis to identify areas with high and low vaccination rates and explored differences in neighborhood characteristics.
UNASSIGNED: Using Anselin\'s Local Moran\'s I statistic, we conducted an ecological analysis of hot and cold spots of adolescent HPV vaccination coverage in Texas from 2017 to 2021. Next, we utilized a Mann-Whitney U test to compare neighborhood characteristics of vaccination coverage in hot spots versus cold spots, leveraging data from the Child Opportunity Index (COI) and American Community Survey.
UNASSIGNED: In Texas, there are 64 persistent vaccination coverage hotspots and 55 persistent vaccination coverage cold spots. The persistent vaccination coverage hot spots are characterized by ZIP codes with lower COI scores, higher percentages of Hispanic residents, higher poverty rates, and smaller populations per square mile compared to vaccine coverage cold spots. We found a more pronounced spatial clustering pattern for male adolescent vaccine coverage than we did for female adolescent vaccine coverage.
UNASSIGNED: In Texas, HPV vaccination coverage rates differ depending on the community\'s income level, with lower-income areas achieving higher success rates. Notably, there are also gender-based discrepancies in vaccination coverage rates, particularly among male adolescents. This knowledge can aid advocates in customizing their outreach initiatives to address these disparities.

UNASSIGNED: To identify the impact of race, ethnicity, and socioeconomic status (SES) on the rate of tympanostomy tube placement.
UNASSIGNED: Retrospective medical review and population-level analyses.
UNASSIGNED: Tertiary referral center.
UNASSIGNED: Demographic and population-level characteristics (age, gender, race, insurance status, and ZIP code) compared to the regional, health system, and otolaryngology clinic demographics.
UNASSIGNED: Among 38,461 children diagnosed with otitis media (OM) 61.4% were white, 27.4% were black, 32.7% had private insurance, and 18.2% were Hispanic. Among patients seen in the pediatric ear, nose, and throat (ENT) clinics, 70.0% were white, 20.0% were black, 46.6% had private insurance, and 14.9% were Hispanic. Further disparity was noted among those receiving tympanostomy tubes: 75.6% white, 15.6% black, 61.9% private insurance, and 11.7% Hispanic. Higher rates of tube placement were noted for those of white race [odds ratio, OR: 1.96, (95% confidence interval, CI: 1.85-2.04), <.001] and non-Hispanic ethnicity [OR: 1.67, (95% CI: 1.56-1.75), <.001]. Geographically, rates of tube placement were significantly lower in areas with higher deprivation indices, areas with lower proportions of white residents, and areas with the lowest median incomes. These markers correlate strongly with black race and Hispanic ethnicity. Lower rates of tube placement were also seen in majority white locales with higher deprivation indices and lower median incomes.
UNASSIGNED: Rates of access to pediatric ENT clinics, and of tube placement, are significantly lower for those of Hispanic ethnicity and black race than for non-Hispanic white children. Higher rates of tube placement were noted among white children and those with private insurance. Lower rates of tube placement were seen in areas of lower SES regardless of racial demographics.

Digital health disparities continue to affect marginalized populations, especially older adults, individuals with low-income, and racial/ethnic minorities, intensifying the challenges these populations face in accessing healthcare. Bridging this digital divide is essential, as digital access and literacy are social determinants of health that can impact digital health use and access to care. This article discusses the potential of leveraging community Wi-Fi and spaces to improve digital access and digital health use, as well as the challenges and opportunities associated with this strategy. The existing limited evidence has shown the possibility of using community Wi-Fi and spaces, such as public libraries, to facilitate telehealth services. However, privacy and security issues from using public Wi-Fi and spaces remain a concern for librarians and healthcare professionals. To advance digital equity, efforts from multilevel stakeholders to improve users\' digital access and literacy and offer tailored technology support in the community are required. Ultimately, leveraging community Wi-Fi and spaces offers a promising avenue to expand digital health accessibility and use, highlighting the critical role of collaborative efforts in overcoming digital health disparities.

BACKGROUND: Emerging artificial intelligence (AI) applications have the potential to improve health, but they may also perpetuate or exacerbate inequities.
OBJECTIVE: This review aims to provide a comprehensive overview of the health equity issues related to the use of AI applications and identify strategies proposed to address them.
METHODS: We searched PubMed, Web of Science, the IEEE (Institute of Electrical and Electronics Engineers) Xplore Digital Library, ProQuest U.S. Newsstream, Academic Search Complete, the Food and Drug Administration (FDA) website, and ClinicalTrials.gov to identify academic and gray literature related to AI and health equity that were published between 2014 and 2021 and additional literature related to AI and health equity during the COVID-19 pandemic from 2020 and 2021. Literature was eligible for inclusion in our review if it identified at least one equity issue and a corresponding strategy to address it. To organize and synthesize equity issues, we adopted a 4-step AI application framework: Background Context, Data Characteristics, Model Design, and Deployment. We then created a many-to-many mapping of the links between issues and strategies.
RESULTS: In 660 documents, we identified 18 equity issues and 15 strategies to address them. Equity issues related to Data Characteristics and Model Design were the most common. The most common strategies recommended to improve equity were improving the quantity and quality of data, evaluating the disparities introduced by an application, increasing model reporting and transparency, involving the broader community in AI application development, and improving governance.
CONCLUSIONS: Stakeholders should review our many-to-many mapping of equity issues and strategies when planning, developing, and implementing AI applications in health care so that they can make appropriate plans to ensure equity for populations affected by their products. AI application developers should consider adopting equity-focused checklists, and regulators such as the FDA should consider requiring them. Given that our review was limited to documents published online, developers may have unpublished knowledge of additional issues and strategies that we were unable to identify.

UNASSIGNED: Our previous analysis showed how in-hospital mortality of intubated patients with COVID-19 in Greece is adversely affected by patient load and regional disparities.
UNASSIGNED: We aimed to update this analysis to include the large Delta and Omicron waves that affected Greece during 2021-2022, while also considering the effect of vaccination on in-hospital mortality.
UNASSIGNED: Anonymized surveillance data were analyzed from all patients with COVID-19 in Greece intubated between September 1, 2020, and April 4, 2022, and followed up until May 17, 2022. Time-split Poisson regression was used to estimate the hazard of dying as a function of fixed and time-varying covariates: the daily total count of intubated patients with COVID-19 in Greece, age, sex, COVID-19 vaccination status, region of the hospital (Attica, Thessaloniki, or rest of Greece), being in an intensive care unit, and an indicator for the period from September 1, 2021.
UNASSIGNED: A total of 14,011 intubated patients with COVID-19 were analyzed, of whom 10,466 (74.7%) died. Mortality was significantly higher with a load of 400-499 intubated patients, with an adjusted hazard ratio (HR) of 1.22 (95% CI 1.09-1.38), rising progressively up to 1.48 (95% CI 1.31-1.69) for a load of ≥800 patients. Hospitalization away from the Attica region was also independently associated with increased mortality (Thessaloniki: HR 1.22, 95% CI 1.13-1.32; rest of Greece: HR 1.64, 95% CI 1.54-1.75), as was hospitalization after September 1, 2021 (HR 1.21, 95% CI 1.09-1.36). COVID-19 vaccination did not affect the mortality of these already severely ill patients, the majority of whom (11,944/14,011, 85.2%) were unvaccinated.
UNASSIGNED: Our results confirm that in-hospital mortality of severely ill patients with COVID-19 is adversely affected by high patient load and regional disparities, and point to a further significant deterioration after September 1, 2021, especially away from Attica and Thessaloniki. This highlights the need for urgent strengthening of health care services in Greece, ensuring equitable and high-quality care for all.

OBJECTIVE: The COVID-19 pandemic abruptly interrupted breast cancer screening, an essential preventive service in primary care. We aimed to evaluate the pandemic\'s impact on overall and follow-up breast cancer screening using real-world health records data.
METHODS: We retrospectively analyzed a cohort of women eligible for breast cancer screening through the study period from January 1, 2017 to February 28, 2022 using TriNetX Research Network data. We examined the temporal trend of monthly screening volume throughout the study period and compared the rate of adherence to follow-up screening within 24 months after the previous screening when the follow-up screening was due in the pre-COVID period vs the COVID period. To account for multiple screenings in the longitudinal data, we applied a logistic regression model using generalized estimating equations with adjustment for individual-level covariates.
RESULTS: Among 1,186,669 screening-eligible women, the monthly screening volume temporarily decreased by 80.6% from February to April 2020 and then rebounded to close to pre-COVID levels by June 2020. Yet, the follow-up screening rate decreased from 78.9% (95% CI, 78.8%-79.0%) in the pre-COVID period to 77.7% (95% CI, 77.6%-77.8%) in the COVID period. Multivariate regression analysis also showed a lower adherence to follow-up screening during the COVID period (odds ratio = 0.86; 0.86-0.87) and a greater pandemic impact among women aged 65 years and older and women of non-Hispanic \"other\" race (Asian, American Indian or Alaska Native, and Native Hawaiian or Other Pacific Islander).
CONCLUSIONS: The COVID-19 pandemic had a transient negative effect on breast cancer screening overall and a prolonged negative effect on follow-up screening. It also exacerbated gaps in adherence to follow-up screening, especially among certain vulnerable groups, requiring innovative strategies to address potential health disparities in primary care.

UNASSIGNED: Individuals from minoritized racial and ethnic backgrounds experience pernicious and pervasive health disparities that have emerged, in part, from clinician bias.
UNASSIGNED: We used a natural language processing approach to examine whether linguistic markers in electronic health record (EHR) notes differ based on the race and ethnicity of the patient. To validate this methodological approach, we also assessed the extent to which clinicians perceive linguistic markers to be indicative of bias.
UNASSIGNED: In this cross-sectional study, we extracted EHR notes for patients who were aged 18 years or older; had more than 5 years of diabetes diagnosis codes; and received care between 2006 and 2014 from family physicians, general internists, or endocrinologists practicing in an urban, academic network of clinics. The race and ethnicity of patients were defined as White non-Hispanic, Black non-Hispanic, or Hispanic or Latino. We hypothesized that Sentiment Analysis and Social Cognition Engine (SEANCE) components (ie, negative adjectives, positive adjectives, joy words, fear and disgust words, politics words, respect words, trust verbs, and well-being words) and mean word count would be indicators of bias if racial differences emerged. We performed linear mixed effects analyses to examine the relationship between the outcomes of interest (the SEANCE components and word count) and patient race and ethnicity, controlling for patient age. To validate this approach, we asked clinicians to indicate the extent to which they thought variation in the use of SEANCE language domains for different racial and ethnic groups was reflective of bias in EHR notes.
UNASSIGNED: We examined EHR notes (n=12,905) of Black non-Hispanic, White non-Hispanic, and Hispanic or Latino patients (n=1562), who were seen by 281 physicians. A total of 27 clinicians participated in the validation study. In terms of bias, participants rated negative adjectives as 8.63 (SD 2.06), fear and disgust words as 8.11 (SD 2.15), and positive adjectives as 7.93 (SD 2.46) on a scale of 1 to 10, with 10 being extremely indicative of bias. Notes for Black non-Hispanic patients contained significantly more negative adjectives (coefficient 0.07, SE 0.02) and significantly more fear and disgust words (coefficient 0.007, SE 0.002) than those for White non-Hispanic patients. The notes for Hispanic or Latino patients included significantly fewer positive adjectives (coefficient -0.02, SE 0.007), trust verbs (coefficient -0.009, SE 0.004), and joy words (coefficient -0.03, SE 0.01) than those for White non-Hispanic patients.
UNASSIGNED: This approach may enable physicians and researchers to identify and mitigate bias in medical interactions, with the goal of reducing health disparities stemming from bias.