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Background: Despite the growing increase in the utilization of hospice in the U.S, disparities exist in the utilization of hospice. Accumulating evidence has shown that neighborhood characteristics have an impact on availability of hospice agencies., Objective: To assess the association between neighborhood social vulnerability and hospice agency availability., Methods: Using the Medicare Post-Acute Care and Hospice Provider Utilization and Payment Public Use Files (PAC PUF) for 2019. Hospice agency addresses were geocoded to the census tract level. Multivariable Poisson regression models were used to assess the association between socioeconomic status SVI theme and hospice agency availability adjusting for number of home health agencies, primary care health profession shortage, per cent Black, and Percent Hispanic at the census tract level and rurality., Results: The socioeconomic status SVI subtheme was associated with decreased likelihood of hospice agency availability (adjusted IRR (aIRR), .56; 95% CI, .50- .63; P < .001). Predominantly Black, and predominantly Hispanic neighborhoods had lower rates of hospice agency availability (aIRR, .48; 95% CI, .39-.59; P < .001 and aIRR, .29; 95% CI, .24-.36; P < .001), respectively., Conclusion: Neighborhood socioeconomic disadvantage was associated with lower availability of hospice agencies. Policies aimed at increasing access to hospice should be cognizant of neighborhood socioeconomic disadvantage., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Artificial intelligence (AI) and machine learning are central components of today's medical environment. The fairness of AI, i.e. the ability of AI to be free from bias, has repeatedly come into question. This study investigates the diversity of members of academia whose scholarship poses questions about the fairness of AI. The articles that combine the topics of fairness, artificial intelligence, and medicine were selected from Pubmed, Google Scholar, and Embase using keywords. Eligibility and data extraction from the articles were done manually and cross-checked by another author for accuracy. Articles were selected for further analysis, cleaned, and organized in Microsoft Excel; spatial diagrams were generated using Public Tableau. Additional graphs were generated using Matplotlib and Seaborn. Linear and logistic regressions were conducted using Python to measure the relationship between funding status, number of citations, and the gender demographics of the authorship team. We identified 375 eligible publications, including research and review articles concerning AI and fairness in healthcare. Analysis of the bibliographic data revealed that there is an overrepresentation of authors that are white, male, and are from high-income countries, especially in the roles of first and last author. Additionally, analysis showed that papers whose authors are based in higher-income countries were more likely to be cited more often and published in higher impact journals. These findings highlight the lack of diversity among the authors in the AI fairness community whose work gains the largest readership, potentially compromising the very impartiality that the AI fairness community is working towards., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Alberto et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Racial inequity persists for chronic disease outcomes amid the proliferation of health information technology (HIT) designed to support patients in following recommended chronic disease self-management behaviors (ie, medication behavior, physical activity, and dietary behavior and attending follow-up appointments). Numerous interventions that use consumer-oriented HIT to support self-management have been evaluated, and some of the related literature has focused on racial minorities who experience disparate chronic disease outcomes. However, little is known about the efficacy of these interventions., Objective: This study aims to conduct a systematic review of the literature that describes the efficacy of consumer-oriented HIT interventions designed to support self-management involving African American and Hispanic patients with chronic diseases., Methods: We followed an a priori protocol using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses)-Equity 2012 Extension guidelines for systematic reviews that focus on health equity. Themes of interest included the inclusion and exclusion criteria. We identified 7 electronic databases, created search strings, and conducted the searches. We initially screened results based on titles and abstracts and then performed full-text screening. We then resolved conflicts and extracted relevant data from the included articles., Results: In total, there were 27 included articles. The mean sample size was 640 (SD 209.5), and 52% (14/27) of the articles focused on African American participants, 15% (4/27) of the articles focused on Hispanic participants, and 33% (9/27) included both. Most articles addressed 3 of the 4 self-management behaviors: medication (17/27, 63%), physical activity (17/27, 63%), and diet (16/27, 59%). Only 15% (4/27) of the studies focused on follow-up appointment attendance. All the articles investigated HIT for use at home, whereas 7% (2/27) included use in the hospital., Conclusions: This study addresses a key gap in research that has not sufficiently examined what technology designs and capabilities may be effective for underserved populations in promoting health behavior in concordance with recommendations., (©Charles Senteio, Paul Joseph Murdock. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 04.04.2022.)

Objective: The study objective was to examine predictors of sleep disturbance and strain among caregivers of persons living with dementia (PLWD)., Methods: This cross-sectional study utilized a sample of community-dwelling older adults and their family caregivers drawn from the 2017 National Health and Aging Trends Study and National Study of Caregiving. Multivariable logistic regression was used to assess the association between caregiver and PLWD characteristics and a composite measure of caregiving strain. High caregiving strain was defined as a total score of ≥ 5 on the 6 caregiving strain items (e.g., emotional difficulty, no time for self). We used multivariable proportional odds models to examine predictors of caregiver sleep-related outcomes (trouble falling back to sleep and interrupted sleep), after adjusting for other caregiver and PLWD factors., Results: Of the 1,142 family caregivers, 65.2% were female, 15% were Black, and 14% were Hispanic. Average age was 60 years old. Female caregivers were more likely to report high level of strain compared to male caregivers (OR: 2.61, 95% CI = 1.56, 4.39). Compared to non-Hispanic Whites, non-Hispanic Black and Hispanic caregivers had reduced odds of reporting greater trouble falling back asleep [OR = 0.55, CI (0.36, 0.82) and OR = 0.56, CI (0.34, 0.91), respectively]. The odds of reporting greater trouble falling back asleep was significantly greater among caregivers with high blood pressure vs. caregivers without high blood pressure [OR = 1.62, CI (1.12, 2.33)]., Conclusion: In this cross-sectional study, caregivers with greater sleep difficulty (trouble falling back asleep) were more likely to report having high blood pressure. We found no racial/ethnic differences in interrupted sleep among caregivers to PLWD. These results suggest that interventions to improve sleep among caregivers to PLWD may decrease poor cardiovascular outcomes in this group., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Osakwe, Senteio, Bubu, Obioha, Turner, Thawani, Saint Fleur-Calixte and Jean-Louis.)

Competing Interests: The authors have no declarations to make.

Objective: There are increasing efforts to capture psychosocial information in outpatient care in order to enhance health equity. To advance clinical decision support systems (CDSS), this study investigated which psychosocial information clinicians value, who values it, and when and how clinicians use this information for clinical decision-making in outpatient type 2 diabetes care., Materials and Methods: This mixed methods study involved physician interviews (n = 17) and a survey of physicians, nurse practitioners (NPs), and diabetes educators (n = 198). We used the grounded theory approach to analyze interview data and descriptive statistics and tests of difference by clinician type for survey data., Results: Participants viewed financial strain, mental health status, and life stressors as most important. NPs and diabetes educators perceived psychosocial information to be more important, and used it significantly more often for 1 decision, than did physicians. While some clinicians always used psychosocial information, others did so when patients were not doing well. Physicians used psychosocial information to judge patient capabilities, understanding, and needs; this informed assessment of the risks and the feasibility of options and patient needs. These assessments influenced 4 key clinical decisions., Discussion: Triggers for psychosocially informed CDSS should include psychosocial screening results, new or newly diagnosed patients, and changes in patient status. CDSS should support cost-sensitive medication prescribing, and psychosocially based assessment of hypoglycemia risk. Electronic health records should capture rationales for care that do not conform to guidelines for panel management. NPs and diabetes educators are key stakeholders in psychosocially informed CDSS., Conclusion: Findings highlight opportunities for psychosocially informed CDSS-a vital next step for improving health equity., (© The Author(s) 2019. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Psychosocial information informs clinical decisions by providing crucial context for patients' barriers to recommended self-care; this is especially important in outpatient diabetes care because outcomes are largely dependent upon self-care behavior. Little is known about provider perceptions of use of psychosocial information. Further, while EHRs have dramatically changed how providers interact with patient health information, the EHRs' role in collection and retrieval of psychosocial information is not understood., Methods: We designed a qualitative study. We used semi-structured interviews to investigate physicians' (N = 17) perspectives on the impact of EHR for psychosocial information use for outpatient Type II diabetes care decisions. We selected the constant comparative method to analyze the data., Findings: Psychosocial information is perceived as dissimilar from other clinical information such as HbA1c and prescribed medications. Its narrative form conveys the patient's story, which elucidates barriers to following self-care recommendations. The narrative is abstract, and requires interpretation of patterns. Psychosocial information is also circumstantial; hence, the patients' context determines influence on self-care. Furthermore, EHRs can impair the collection of psychosocial information because the designs of EHR tools make it difficult to document, search for, and retrieve it. Templates do not enable users from collecting the patient's 'story', and using free text fields is time consuming. Providers therefore had low use of, and confidence in, the accuracy of psychosocial information in the EHR., Principal Conclusions: Workflows and EHR tools should be re-designed to better support psychosocial information collection and retrieval. Tools should enable recording and summarization of the patient's story, and the rationale for treatment decisions., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Objective: We compare 5 health informatics research projects that applied community-based participatory research (CBPR) approaches with the goal of extending existing CBPR principles to address issues specific to health informatics research., Materials and Methods: We conducted a cross-case analysis of 5 diverse case studies with 1 common element: integration of CBPR approaches into health informatics research. After reviewing publications and other case-related materials, all coauthors engaged in collaborative discussions focused on CBPR. Researchers mapped each case to an existing CBPR framework, examined each case individually for success factors and barriers, and identified common patterns across cases., Results: Benefits of applying CBPR approaches to health informatics research across the cases included the following: developing more relevant research with wider impact, greater engagement with diverse populations, improved internal validity, more rapid translation of research into action, and the development of people. Challenges of applying CBPR to health informatics research included requirements to develop strong, sustainable academic-community partnerships and mismatches related to cultural and temporal factors. Several technology-related challenges, including needs to define ownership of technology outputs and to build technical capacity with community partners, also emerged from our analysis. Finally, we created several principles that extended an existing CBPR framework to specifically address health informatics research requirements., Conclusions: Our cross-case analysis yielded valuable insights regarding CBPR implementation in health informatics research and identified valuable lessons useful for future CBPR-based research. The benefits of applying CBPR approaches can be significant, particularly in engaging populations that are typically underserved by health care and in designing patient-facing technology., (© The Authors 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Adherence to treatment recommendations for chronic diseases is notoriously low across all patient populations. But African American patients, who are more likely to live in low-income neighborhoods and to have multiple chronic conditions, are even less likely to follow medical recommendations. Yet we know little about their contextually embedded, adherence-related experiences. We interviewed individuals (n = 37) with at least two of the following conditions: hypertension, diabetes, and chronic kidney disease. Using an "invisible work" theoretical framework, we outline the adherence work that arose in patients' common life circumstances. We found five types: constantly searching for better care, stretching medications, eating what I know, keeping myself alive, and trying to make it right. Adherence work was effortful, challenging, and addressed external contingencies present in high-poverty African American neighborhoods. This work was invisible within the health care system because participants lacked ongoing, trusting relationships with providers and rarely discussed challenges with them., (© The Author(s) 2014.)

Objectives: We examined racial/ethnic differences in prenatal antiretroviral (ARV) treatment among 3259 HIV-infected pregnant Medicaid enrollees., Methods: We analyzed 2005-2007 Medicaid claims data from 14 southern states, comparing rates of not receiving ARVs and suboptimal versus optimal ARV therapy., Results: More than one third (37.3%) had zero claims for ARV drugs. Three quarters (73.4%) of 346 Hispanic women received no prenatal ARVs. After we adjusted for covariates, Hispanic women had 3.89 (95% confidence interval = 2.58, 5.87) times the risk of not receiving ARVs compared with Whites. Hispanic women often had only 1 or 2 months of Medicaid eligibility, perhaps associated with barriers for immigrants. Less than 3 months of eligibility was strongly associated with nontreatment (adjusted odds ratio = 29.0; 95% confidence interval = 13.4, 62.7)., Conclusions: Optimal HIV treatment rates in pregnancy are a public health priority, especially for preventing transmission to infants. Medicaid has the surveillance and drug coverage to ensure that all HIV-infected pregnant women are offered treatment. States that offer emergency Medicaid coverage for only delivery services to pregnant immigrants are missing an opportunity to screen, diagnose, and treat pregnant women with HIV, and to prevent HIV in children.

Background: South Dallas experiences significant disparities in breast cancer mortality, with a high proportion of stage III and IV diagnoses. To address these rates, the Dallas Cancer Disparities Community Research Coalition created an educational intervention to promote breast health and early detection efforts., Objectives: The goals of the intervention were to increase (a) knowledge regarding the chief contributing factors for breast cancer, (b) awareness of the importance of screening for early detection, and (c) the proportion of women who have engaged in appropriate breast cancer screening practices., Methods: Eligibility criteria for this nonrandomized, controlled trial included women age 40 and older, English-speaking, and having no personal history of cancer. Control participants received written breast health educational materials. Intervention participants attended 8 weekly sessions that included interactive educational materials, cooking demonstrations, and discussions emphasizing primary and secondary breast cancer prevention. All study participants completed a 1-hour survey at baseline and 4 months later., Results: There were 59 women were enrolled in the intervention and 60 in the control group. At follow-up, after controlling for baseline mammography status, women in the intervention group were 10.4 times more likely (95% confidence interval [CI], 2.9-36.4) to have received a screening mammogram in the last year compared with the control group. Intervention participants demonstrated statistically significantly higher rates of breast self-examination (odds ratio [OR], 3.0; 95% CI, 1.0-8.6) and breast cancer knowledge (p=.003)., Conclusion: Lessons learned from this community-based participatory research (CBPR) study can be used to create sustainable cancer disparity reduction models that can be replicated in similar communities.

Each year in the United States, as adolescents age out or are emancipated from the foster care system, they are at risk of experiencing homelessness. It is essential that services and programs focus on encouraging and supporting youth in transition from foster care to a life of independence, and The Transition Resource Action Center (TRAC) strives to provide these services. The researchers sought to determine if TRAC's residential program provides their clients with a chance of a stable life (e.g., housing, employment, health care). Findings suggest that fewer clients of TRAC became homeless and more acquired transitional or temporary housing from screening 1 to screening 2, demonstrating promise that these services have fostered change in the lives of their clients.