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.

Health Disparities in Dementia.

PURPOSE OF REVIEW: Causes of health disparities in Alzheimer disease and related dementias (ADRD) in the United States are multifactorial. This article contextualizes health disparities as they relate to the neurodegenerative processes of ADRD. RECENT FINDINGS: Older adults' life expectancy has increased such that a 65-year-old is expected to live 19 or more years and an 85-year-old can expect to live, on average, 6 to 7 years longer. Individuals of certain ethnoracial groups (Black, Hispanic/Latino, American Indian/Alaska Native, and Native Hawaiian/Pacific Islander) may be at a higher risk of incident ADRD compared to non-Hispanic/Latino White people. These differences in a higher risk of ADRD across ethnoracial groups persist despite no statistically significant differences in the rate of cognitive decline over time. The intersectionality of social determinants of health, experiences with discrimination and oppression, and access to care are related to the issue of justice and the risk for and expression of ADRD. The theoretical frameworks of various health disparities provide organized approaches to tracking the progression of health disparities for diverse patients. SUMMARY: ADRD health disparities are complex. Neurologists and their care teams must consider the main reasons for clinical ADRD evaluations of members of ethnoracial groups and the factors that may impact patient adherence and compliance with diagnostic and management recommendations.

Feasibility of a virtual Facebook community platform for engagement on health research.

INTRODUCTION: Community engagement is important for advancing Clinical and Translational Science (CTS), but face-to-face engagement has limited reach and scale. We examined the feasibility of a novel virtual Facebook community platform for public engagement on health research statewide in Minnesota. METHODS: The Facebook platform, MN Research Link, was evaluated from June 19, 2019 to June 30, 2020. Facebook advertisements and boosts were used to recruit followers. Content, based on prior formative work, included health research information and interactive postings (e.g., live interviews with researchers). Standard metrics obtained from Facebook analytics included participation (followers), content reach (views), and engagement (likes, shares, comments, clicks). RESULTS: During the 12-month period, we acquired 1406 followers (31% rural residents), with a retention of followers of 99.7%. Mean number of views per month was 9379.83 (Mdn = 2791, range 724-41,510). Engagement metrics indicated a mean of 535.2 likes, shares, comments, and/or clicks per month (Mdn = 296.5, range 55-1535). The page continued to acquire new followers, but a slight decrease in engagement was observed in the final months after state COVID-19 mitigation strategies were implemented. CONCLUSION: As the complexity of CTS continues to grow, along with social distancing measures resulting from the COVID-19 pandemic, the availability of virtual digital platforms to reach and engage community stakeholders in conversations about health and research has increasing importance. Preliminary findings from this program evaluation indicate that a Facebook community platform is feasible to engage Minnesota residents in conversations around health and research topics. Future work will evaluate its potential for reach, scale, and sustainability.

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 limited review into how to make the most of SBDH information from EHRs using AI approaches.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, natural language processing (NLP) approaches for extracting SBDH from clinical notes, and predictive models using SBDH for health outcomes.Discussion. The associations between SBDH and health outcomes are complicated and diverse; several pathways may be involved. Using 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 diseases, 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, ultimately promoting health and health equity.

Public feedback on a proposed statewide virtual translational research community.

INTRODUCTION: Researchers have explored using the internet and social media to recruit participants to specific research projects. Less systematic work has been done to inform the engagement of large populations in virtual communities to advance clinical and translational science. We report on our first step to use social media to engage Minnesota residents by studying the willingness of participants to engage in a virtual (Facebook) community about the concepts of health and health-related research. METHODS: Data were collected at the 2018 Minnesota State Fair using a cross-sectional, 46-item survey with assessment including sociodemographics and willingness to engage in a Facebook group for health-related research. Quantitative analysis included univariate, bivariate, and multivariate analyses. Content analysis was used to generate themes from open-ended survey responses. RESULTS: Five hundred people completed the survey; after data cleaning, 418 participant responses informed this report. A majority were younger than age 50 (73%), female (66%), and married/partnered (54%). Overall, 46% of participants agreed/strongly agreed they are willing to join the Facebook group. Multivariate logistic regression identified social media use over the past 6 months as the sole variable independently associated with willingness to join the Facebook group (once a day vs. never or rarely OR = 1.82 (0.86, 3.88), several hours a day vs. never or rarely OR = 2.17 (1.17, 4.02, overall p-value 0.048). CONCLUSION: Facebook holds potential for reaching a broader community, democratizing access to and engagement with clinical and translational research. Social media infrastructure and content could be disseminated to other institutions with Clinical and Translational Science Awards.