Mining the health disparities and minority health bibliome: A computational scoping review and gap analysis of 200,000+ articles.

Without comprehensive examination of available literature on health disparities and minority health (HDMH), the field is left vulnerable to disproportionately focus on specific populations or conditions, curtailing our ability to fully advance health equity. Using scalable open-source methods, we conducted a computational scoping review of more than 200,000 articles to investigate major populations, conditions, and themes as well as notable gaps. We also compared trends in studied conditions to their relative prevalence using insurance claims (42 million Americans). HDMH publications represent 1% of articles in Medical Literature Analysis and Retrieval System Online (MEDLINE). Most studies are observational in nature, although randomized trial reporting has increased fivefold in the past 20 years. Half of HDMH articles concentrate on only three disease groups (cancer, mental health, and endocrine/metabolic disorders), while hearing, vision, and skin-related conditions are among the least well represented despite substantial prevalence. To support further investigation, we present HDMH Monitor, an interactive dashboard and repository generated from the HDMH bibliome.

Mining the Health Disparities and Minority Health Bibliome: A Computational Scoping Review and Gap Analysis of 200,000+ Articles.

Without comprehensive examination of available literature on health disparities and minority health (HDMH), the field is left vulnerable to disproportionately focus on specific populations or conditions, curtailing our ability to fully advance health equity. Using scalable open-source methods, we conducted a computational scoping review of more than 200,000 articles to investigate major populations, conditions, and themes in the literature as well as notable gaps. We also compared trends in studied conditions to their relative prevalence in the general population using insurance claims (42MM Americans). HDMH publications represent 1% of articles in MEDLINE. Most studies are observational in nature, though randomized trial reporting has increased five-fold in the last twenty years. Half of all HDMH articles concentrate on only three disease groups (cancer, mental health, endocrine/metabolic disorders), while hearing, vision, and skin-related conditions are among the least well represented despite substantial prevalence. To support further investigation, we also present HDMH Monitor, an interactive dashboard and repository generated from the HDMH bibliome.

Evaluating and refining a pain quality information visualization tool with patients and interpreters to facilitate pain assessment in primary care settings.

Information visualization (InfoViz) tools offer a potential solution to pain communication challenges. Incongruencies in communication styles between patients with limited English proficiency (LEP), interpreters, and providers contribute to significant disparities in pain care and outcomes. This study's purpose is to evaluate and refine a culturally appropriate InfoViz pain quality assessment tool for LEP Hmong patients. We conducted a three-part iterative user-centered study with LEP Hmong, bilingual Hmong, and Hmong interpreters with (1) participatory design sessions to evaluate and refine pain infographics for inclusion on the tool, (2) card-sorting to organize the infographics to match the mental models of LEP patients, and (3) a tool assessment to identify which tool accurately represented LEP patients' mental models and was preferred in clinical settings. Fifty-five participants provided three common themes for pain infographics refinement: culturally-relevant colors, infographics resembling human anatomy, and action-specific squiggle lines. The card-sorting sessions revealed three organizational themes: sensation (n = 15; 71.4%), localization (n = 6; 28.6%), and severity of pain quality (n = 5; 24.3%). Most participants selected the localization as the most accurate tool and preferred it in clinical settings. Using a multi-step, user-centered approach resulted in a culturally appropriate pain InfoViz tool for LEP Hmong patients.

Informatics and data science perspective on Future of Nursing 2020-2030: Charting a pathway to health equity.

The Future of Nursing 2020 to 2030 report explicitly addresses the need for integration of nursing expertise in designing, generating, analyzing, and applying data to support initiatives focused on social determinants of health (SDOH) and health equity. The metrics necessary to enable and evaluate progress on all recommendations require harnessing existing data sources and developing new ones, as well as transforming and integrating data into information systems to facilitate communication, information sharing, and decision making among the key stakeholders. We examine the recommendations of the 2021 report through an interdisciplinary lens that integrates nursing, biomedical informatics, and data science by addressing three critical questions: (a) what data are needed?, (b) what infrastructure and processes are needed to transform data into information?, and (c) what information systems are needed to "level up" nurse-led interventions from the micro-level to the meso- and macro-levels to address social determinants of health and advance health equity?

Phenotypes of engagement with mobile health technology for heart rhythm monitoring.

OBJECTIVES: Guided by the concept of digital phenotypes, the objective of this study was to identify engagement phenotypes among individuals with atrial fibrillation (AF) using mobile health (mHealth) technology for 6 months. MATERIALS AND METHODS: We conducted a secondary analysis of mHealth data, surveys, and clinical records collected by participants using mHealth in a clinical trial. Patterns of participants' weekly use over 6 months were analyzed to identify engagement phenotypes via latent growth mixture model (LGMM). Multinomial logistic regression models were fitted to compute the effects of predictors on LGMM classes. RESULTS: One hundred twenty-eight participants (mean age 61.9 years, 75.8% male) were included in the analysis. Application of LGMM identified 4 distinct engagement phenotypes: "High-High," "Moderate-Moderate," "High-Low," and "Moderate-Low." In multinomial models, older age, less frequent afternoon mHealth use, shorter intervals between mHealth use, more AF episodes measured directly with mHealth, and lower left ventricular ejection fraction were more strongly associated with the High-High phenotype compared to the Moderate-Low phenotype (reference). Older age, more palpitations, and a history of stroke or transient ischemic attack were more strongly associated with the Moderate-Moderate phenotype compared to the reference. DISCUSSION: Engagement phenotypes provide a nuanced characterization of how individuals engage with mHealth over time, and which individuals are more likely to be highly engaged users. CONCLUSION: This study demonstrates that engagement phenotypes are valuable in understanding and possibly intervening upon engagement within a population, and also suggests that engagement is an important variable to be considered in digital phenotyping work more broadly.

Promoting Latino Self-Management Through Use of Information Visualizations: A Case Study in New York City.

Social determinants of health, including low health literacy and limited English proficiency, and other factors place Latinos at high risk for health disparities related to chronic diseases. Such diseases require self-management skills as well as medical management. Well-designed visualizations are suitable for visualizing data related to self-management because they can help narrow the comprehension gap between individuals with low and high levels of health literacy by leveraging existing visual analysis skills while reducing the demand on literacy and numeracy competencies. Use of information visualizations also supports a common visual representation across languages to address limited English proficiency. This report illustrates the use of information visualizations for communication related to self-management through research-based case examples and summarizes key lessons from studies with Latinos in New York City.

Mobile Electrocardiogram Monitoring and Health-Related Quality of Life in Patients With Atrial Fibrillation: Findings From the iPhone Helping Evaluate Atrial Fibrillation Rhythm Through Technology (iHEART) Study.

BACKGROUND: Atrial fibrillation (AF) is associated with high recurrence rates and poor health-related quality of life (HRQOL) but few effective interventions to improve HRQOL exist. OBJECTIVE: The aim of this study was to examine the impact of the "iPhone Helping Evaluate Atrial Fibrillation Rhythm through Technology" (iHEART) intervention on HRQOL in patients with AF. METHODS: We randomized English- and Spanish-speaking adult patients with AF to receive either the iHEART intervention or usual care for 6 months. The iHEART intervention used smartphone-based electrocardiogram monitoring and motivational text messages. Three instruments were used to measure HRQOL: the Atrial Fibrillation Effect on Quality of Life (AFEQT), the 36-item Short-Form Health survey, and the EuroQol-5D. We used linear mixed models to compare the effect of the iHEART intervention on HRQOL, quality-adjusted life-years, and AF symptom severity. RESULTS: A total of 238 participants were randomized to the iHEART intervention (n = 115) or usual care (n = 123). Of the participants, 77% were men and 76% were white. More than half (55%) had an AF recurrence. Both arms had improved scores from baseline to follow-up for AFEQT and AF symptom severity scores. The global AFEQT score improved 18.5 and 11.2 points in the intervention and control arms, respectively (P < .05). There were no statistically significant differences in HRQOL, quality-adjusted life-years, or AF symptom severity between groups. CONCLUSIONS: We found clinically meaningful improvements in AF-specific HRQOL and AF symptom severity for both groups. Additional research with longer follow-up should examine the influence of smartphone-based interventions for AF management on HRQOL and address the unique needs of patients diagnosed with different subtypes of AF.

Health informatics and health equity: improving our reach and impact.

Health informatics studies the use of information technology to improve human health. As informaticists, we seek to reduce the gaps between current healthcare practices and our societal goals for better health and healthcare quality, safety, or cost. It is time to recognize health equity as one of these societal goals-a point underscored by this Journal of the American Medical Informatics Association Special Focus Issue, "Health Informatics and Health Equity: Improving our Reach and Impact." This Special Issue highlights health informatics research that focuses on marginalized and underserved groups, health disparities, and health equity. In particular, this Special Issue intentionally showcases high-quality research and professional experiences that encompass a broad range of subdisciplines, methods, marginalized populations, and approaches to disparities. Building on this variety of submissions and other recent developments, we highlight contents of the Special Issue and offer an assessment of the state of research at the intersection of health informatics and health equity.

A semi-automated approach for analyzing collages to inform the design of a family health information management system for Hispanic dementia caregivers.

Culturally- and linguistically-tailored health communication is needed for vulnerable populations to manage their health and the health of their families. This presents a significant design challenge. The use of collages is an increasingly popular technique with the flexibility to capture the needs and experiences of individuals with various cultural and language preferences. Collage analysis has typically remained qualitative in nature. We introduce a novel, objective, semi-automated approach that enhances collage analysis to elucidate pattern differences that may not be detectable by natural perception. We present a case scenario of collage analysis based on the expressed experience and self-management needs of Hispanic dementia caregivers (n = 24). We demonstrate how our innovative approach may reveal cultural differences between language groups that could have otherwise been missed using traditional techniques.

Correction to: Association Between Health Literacy and Medication Adherence Among Hispanics with Hypertension.

Please note the following correction in the second paragraph of the Results section of this article, in the sentences that read, "Table 2 shows the association of health literacy level, as well as each of the included covariates with adherence.

Models of collaboration and dissemination for nursing informatics innovations in the 21st century.

BACKGROUND: Nursing informatics innovations are constantly adapting to a rapidly changing health care environment. PURPOSE: This study aims to present the lessons learned from 4 nursing informatics projects and rationale for development decisions to inform future informatics innovations. METHODS: Using a comparative cross-case analysis, four case studies of informatics projects led by nurse scientists were described and analyzed through the lens of the Informatics Research Organizing Model which was modified to include policy and interoperability contexts. FINDINGS: The comparison analysis examined dynamic relationships between processes and constructs in nursing informatics interventions and also highlighted the scientific, intellectual property, technical, and policy challenges encountered among the four case studies. DISCUSSION: The analysis provided implications for future intervention development and implementation in consideration of multiple contexts for nursing informatics innovations.

Behavioral Interventions Using Consumer Information Technology as Tools to Advance Health Equity.

The digital divide related to consumer information technologies (CITs) has diminished, thus increasing the potential to use CITs to overcome barriers of access to health interventions as well as to deliver interventions situated in the context of daily lives. However, the evidence base regarding the use and impact of CIT-enabled interventions in health disparity populations lags behind that for the general population. Literature and case examples are summarized to demonstrate the use of mHealth, telehealth, and social media as behavioral intervention platforms in health disparity populations, identify challenges to achieving their use, describe strategies for overcoming the challenges, and recommend future directions. The evidence base is emerging. However, challenges in design, implementation, and evaluation must be addressed for the promise to be fulfilled. Future directions include (1) improved design methods, (2) enhanced research reporting, (3) advancement of multilevel interventions, (4) rigorous evaluation, (5) efforts to address privacy concerns, and (6) inclusive design and implementation decisions.