High prevalence of chronic viral hepatitis B and C in Minnesota Somalis contributes to rising hepatocellular carcinoma incidence

BACKGROUND: Chronic hepatitis B virus (HBV) and hepatitis C virus (HCV) infections are known risk factors for liver disease, cirrhosis and hepatocellular carcinoma (HCC). There is substantial global variation in HBV and HCV prevalence resulting in variations in cirrhosis and HCC. We previously reported high prevalence of HBV and HCV infections in Somali immigrants seen at an academic medical center in Minnesota. AIM: To determine the prevalence of chronic viral hepatitis in Somali immigrants in Minnesota through a community-based screening program. METHODS: We conducted a prospective community-based participatory research study in the Somali community in Minnesota in partnership with community advisory boards, community clinics and local mosques between November 2010 and December 2015 (data was analyzed in 2020). Serum was tested for hepatitis B surface antigen, hepatitis B core antibody, hepatitis B surface antibody and anti-HCV antibody. RESULTS: Of 779 participants, 15.4% tested positive for chronic HBV infection, 50.2% for prior exposure to HBV and 7.6% for chronic HCV infection. Calculated age-adjusted frequencies in males and females for chronic HBV were 12.5% and 11.6%; for prior exposure to HBV were 44.8% and 41.3%; and for chronic HCV were 6.7% and 5.7%, respectively. Seven participants developed incident HCC during follow up. CONCLUSION: Chronic HBV and HCV are major risk factors for liver disease and HCC among Somali immigrants, with prevalence of both infections substantially higher than in the general United States population. Community-based screening is essential for identifying and providing health education and linkage to care for diagnosed patients

Identifying contributors to disparities in patient access of online medical records: Examining the role of clinician encouragement

OBJECTIVE: The aim of this study was to understand the influence of clinician encouragement and sociodemographic factors on whether patients access online electronic medical records (EMR). MATERIALS AND METHODS: We analyzed 3279 responses from the Health Information National Trends Survey 5 cycle 4 survey, a cross-sectional, nationally representative survey administered by the National Cancer Institute. Frequencies and weighted proportions were calculated to compare clinical encouragement and access to their online EMR. Using multivariate logistic regression, we identified factors associated with online EMR use and clinician encouragement. RESULTS: In 2020, an estimated 42% of US adults accessed their online EMR and 51% were encouraged by clinicians to access their online EMR. In multivariate regression, respondents who accessed EMR were more likely to have received clinician encouragement (odds ratio [OR], 10.3; 95% confidence interval [CI], 7.7-14.0), college education or higher (OR, 1.9; 95% CI, 1.4-2.7), history of cancer (OR, 1.5; 95% CI, 1.0-2.3), and history of chronic disease (OR, 2.3; 95% CI, 1.7-3.2). Male and Hispanic respondents were less likely to have accessed EMR than female and non-Hispanic White respondents (OR, 0.6; 95% CI, 0.5-0.8, and OR, 0.5; 95% CI, 0.3-0.8, respectively). Respondents receiving encouragement from clinicians were more likely to be female (OR, 1.7; 95% CI, 1.3-2.3), have college education (OR, 1.5; 95% CI, 1.1-2.0), history of cancer (OR, 1.8; 95% CI, 1.3-2.5), and greater income levels (OR, 1.8-3.6). DISCUSSION: Clinician encouragement of patient EMR use is strongly associated with patients accessing EMR, and there are disparities in who receives clinician encouragement related to education, income, sex, and ethnicity. CONCLUSIONS: Clinicians have an important role to ensure that all patients benefit from online EMR use

Social and behavioral determinants of health in the era of artificial intelligence with electronic health records: A scoping review

Background: There is growing evidence that social and behavioral determinants of health (SBDH) play a substantial effect in a wide range of health outcomes. Electronic health records (EHRs) have been widely employed to conduct observational studies in the age of artificial intelligence (AI). However, there has been little research into how to make the most of SBDH information from EHRs. Methods: A systematic search was conducted in six databases to find relevant peer-reviewed publications that had recently been published. Relevance was determined by screening and evaluating the articles. Based on selected relevant studies, a methodological analysis of AI algorithms leveraging SBDH information in EHR data was provided. Results: Our synthesis was driven by an analysis of SBDH categories, the relationship between SBDH and healthcare-related statuses, and several NLP approaches for extracting SDOH from clinical literature. Discussion: The associations between SBDH and health outcomes are complicated and diverse; several pathways may be involved. Using Natural Language Processing (NLP) technology to support the extraction of SBDH and other clinical ideas simplifies the identification and extraction of essential concepts from clinical data, efficiently unlocks unstructured data, and aids in the resolution of unstructured data-related issues. Conclusion: Despite known associations between SBDH and disease, SBDH factors are rarely investigated as interventions to improve patient outcomes. Gaining knowledge about SBDH and how SBDH data can be collected from EHRs using NLP approaches and predictive models improves the chances of influencing health policy change for patient wellness, and ultimately promoting health and health equity. Keywords: Social and Behavioral Determinants of Health, Artificial Intelligence, Electronic Health Records, Natural Language Processing, Predictive ModelComment: 32 pages, 5 figure

Bridging the technological divide: Stigmas and challenges with technology in digital brain health studies of older adults

The COVID-19 pandemic has increased adoption of remote assessments in clinical research. However, longstanding stereotypes persist regarding older adults\u27 technology familiarity and their willingness to participate in technology-enabled remote studies. We examined the validity of these stereotypes using a novel technology familiarity assessment

Measuring quality and outcomes of research collaborations: An integrative review

Introduction: Although the science of team science is no longer a new field, the measurement of team science and its standardization remain in relatively early stages of development. To describe the current state of team science assessment, we conducted an integrative review of measures of research collaboration quality and outcomes. Methods: Collaboration measures were identified using both a literature review based on specific keywords and an environmental scan. Raters abstracted details about the measures using a standard tool. Measures related to collaborations with clinical care, education, and program delivery were excluded from this review. Results: We identified 44 measures of research collaboration quality, which included 35 measures with reliability and some form of statistical validity reported. Most scales focused on group dynamics. We identified 89 measures of research collaboration outcomes; 16 had reliability and 15 had a validity statistic. Outcome measures often only included simple counts of products; publications rarely defined how counts were delimited, obtained, or assessed for reliability. Most measures were tested in only one venue. Conclusions: Although models of collaboration have been developed, in general, strong, reliable, and valid measurements of such collaborations have not been conducted or accepted into practice. This limitation makes it difficult to compare the characteristics and impacts of research teams across studies or to identify the most important areas for intervention. To advance the science of team science, we provide recommendations regarding the development and psychometric testing of measures of collaboration quality and outcomes that can be replicated and broadly applied across studies

Association between socioeconomic factors, race, and use of a specialty memory clinic

BACKGROUND AND OBJECTIVES: The capacity of specialty memory clinics in the United States is very limited. If lower socioeconomic status or minoritized racial group is associated with reduced use of memory clinics, this could exacerbate health care disparities, especially if more effective treatments of Alzheimer disease become available. We aimed to understand how use of a memory clinic is associated with neighborhood-level measures of socioeconomic factors and the intersectionality of race. METHODS: We conducted an observational cross-sectional study using electronic health record data to compare the neighborhood advantage of patients seen at the Washington University Memory Diagnostic Center with the catchment area using a geographical information system. Furthermore, we compared the severity of dementia at the initial visit between patients who self-identified as Black or White. We used a multinomial logistic regression model to assess the Clinical Dementia Rating at the initial visit and RESULTS: A total of 4,824 patients seen at the memory clinic between 2008 and 2018 were included in this study (mean age 72.7 [SD 11.0] years, 2,712 [56%] female, 543 [11%] Black). Most of the memory clinic patients lived in more advantaged neighborhoods within the overall catchment area. The percentage of patients self-identifying as Black (11%) was lower than the average percentage of Black individuals by census tract in the catchment area (16%) ( DISCUSSION: This study demonstrates that patients living in less affluent neighborhoods were less likely to be seen in one large memory clinic. Black patients were under-represented in the clinic, and Black patients had more severe dementia at their initial visit. These findings suggest that patients with a lower socioeconomic status and who identify as Black are less likely to be seen in memory clinics, which are likely to be a major point of access for any new Alzheimer disease treatments that may become available

Racial disparities in bipolar disorder treatment and research: a call to action

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146344/1/bdi12638.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146344/2/bdi12638_am.pd

Challenging the 'New Professionalism': from managerialism to pedagogy?

In recent years there have been changes made to the conceptualisation of continuing professional development for teachers in both the Scottish and English systems of education. These changes have been instigated by successive UK governments (and more recently, by the Scottish Executive), together with the General teaching Council for Scotland (GTCS) and the General Teaching Council for England (GTCE). This paper argues that these changes have not provided a clear rationale for CPD, but instead have introduced tensions between the concept of teacher education and that of training. The need for a less confused understanding of CPD and its purposes is underlined, as is the need for school based approaches to continuing teacher education. Arguably, teacher education must move from technicist emphases to a model which integrates the social processes of change within society and schools with the individual development and empowerment of teachers

Effect of race on prediction of brain amyloidosis by plasma Aβ42/Aβ40, phosphorylated tau, and neurofilament light

BACKGROUND AND OBJECTIVES: To evaluate whether plasma biomarkers of amyloid (Aβ42/Aβ40), tau (p-tau181 and p-tau231), and neuroaxonal injury (neurofilament light chain [NfL]) detect brain amyloidosis consistently across racial groups. METHODS: Individuals enrolled in studies of memory and aging who self-identified as African American (AA) were matched 1:1 to self-identified non-Hispanic White (NHW) individuals by age, RESULTS: There were 76 matched pairs of AA and NHW participants (n = 152 total). For both AA and NHW groups, the median age was 68.4 years, 42% were DISCUSSION: Models predicting brain amyloidosis using a high-performance plasma Aβ42/Aβ40 assay may provide an accurate and consistent measure of brain amyloidosis across AA and NHW groups, but models based on plasma p-tau181, p-tau231, and NfL may perform inconsistently and could result in disproportionate misdiagnosis of AA individuals