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.

Human Papillomavirus Vaccination Among Transgender and Gender Diverse People in the United States: An Integrative Review.

Objective: This integrative review explores the barriers to and facilitators for human papillomavirus (HPV) vaccination among adult transgender and gender diverse (TGD) people in the United States. Data Source: A systematic search of electronic databases included PubMed/MEDLINE, CINAHL, and EMBASE from 1985 to 2020. Inclusion and Exclusion Criteria: Inclusion criteria included studies from the United States that described HPV vaccination barriers or facilitators and included adult TGD participants, both quantitative and qualitative studies. Exclusion criteria were studies that reported only HPV vaccine prevalence, non-English/non-U.S. studies, and studies limited to pediatric populations. Data Extraction: Two investigators used Covidence software to screen studies and manage data extraction. Quality of the quantitative studies was appraised using a checklist proposed by the Joanna Briggs Institute (JBI); qualitative studies were appraised using quality criteria informed by the literature. Data Synthesis: The Social Ecological Model guided the review to organize barriers to and facilitators for HPV vaccination at the patient-, provider-, and system-levels. Results: Database searches and hand-searching yielded 843 citations. After screening, eight articles were retained in the review. Seven were cross-sectional studies and one was a qualitative focus-group. All retained quantitative studies met six of the eight JBI quality checklist items. Conclusion: The low proportion of TGD participants in the retained studies highlights a gap in knowledge about HPV vaccination among this population. Future studies of HPV vaccination should recruit TGD people to better represent their perspectives.

Online health information seeking, health literacy, and human papillomavirus vaccination among transgender and gender-diverse people.

OBJECTIVE: The purpose of this study is to describe online health information seeking among a sample of transgender and gender diverse (TGD) people compared with cisgender sexual minority people to explore associations with human papillomavirus (HPV) vaccination, and whether general health literacy and eHealth literacy moderate this relationship. MATERIALS AND METHODS: We performed a cross-sectional online survey of TGD and cisgender sexual minority participants from The PRIDE Study, a longitudinal, U.S.-based, national health study of sexual and gender minority people. We employed multivariable logistic regression to model the association of online health information seeking and HPV vaccination. RESULTS: The online survey yielded 3258 responses. Compared with cisgender sexual minority participants, TGD had increased odds of reporting HPV vaccination (aOR, 1.5; 95% CI, 1.1-2.2) but decreased odds when they had looked for information about vaccines online (aOR, 0.7; 95% CI, 0.5-0.9). TGD participants had over twice the odds of reporting HPV vaccination if they visited a social networking site like Facebook (aOR, 2.4; 95% CI, 1.1-5.6). No moderating effects from general or eHealth literacy were observed. DISCUSSION: Decreased reporting of HPV vaccination among TGD people after searching for vaccine information online suggests vaccine hesitancy, which may potentially be related to the quality of online content. Increased reporting of vaccination after using social media may be related to peer validation. CONCLUSIONS: Future studies should investigate potential deterrents to HPV vaccination in online health information to enhance its effectiveness and further explore which aspects of social media might increase vaccine uptake among TGD people.

Characterizing shared and distinct symptom clusters in common chronic conditions through natural language processing of nursing notes.

Data-driven characterization of symptom clusters in chronic conditions is essential for shared cluster detection and physiological mechanism discovery. This study aims to computationally describe symptom documentation from electronic nursing notes and compare symptom clusters among patients diagnosed with four chronic conditions-chronic obstructive pulmonary disease (COPD), heart failure, type 2 diabetes mellitus, and cancer. Nursing notes (N = 504,395; 133,977 patients) were obtained for the 2016 calendar year from a single medical center. We used NimbleMiner, a natural language processing application, to identify the presence of 56 symptoms. We calculated symptom documentation prevalence by note and patient for the corpus. Then, we visually compared documentation for a subset of patients (N = 22,657) diagnosed with COPD (n = 3339), heart failure (n = 6587), diabetes (n = 12,139), and cancer (n = 7269) and conducted multiple correspondence analysis and hierarchical clustering to discover underlying groups of patients who have similar symptom profiles (i.e., symptom clusters) for each condition. As expected, pain was the most frequently documented symptom. All conditions had a group of patients characterized by no symptoms. Shared clusters included cardiovascular symptoms for heart failure and diabetes; pain and other symptoms for COPD, diabetes, and cancer; and a newly-identified cognitive and neurological symptom cluster for heart failure, diabetes, and cancer. Cancer (gastrointestinal symptoms and fatigue) and COPD (mental health symptoms) each contained a unique cluster. In summary, we report both shared and distinct, as well as established and novel, symptom clusters across chronic conditions. Findings support the use of electronic health record-derived notes and NLP methods to study symptoms and symptom clusters to advance symptom science.

Adverse event reporting in head and neck transoral robotic surgery: a MAUDE database study.

Transoral robotic surgery (TORS) using the da Vinci Surgical system was approved by the US Food and Drug Administration in 2009. Currently, most available safety information on TORS procedures describes adverse events occurring in the context of clinical trials or series at high-volume academic centers. The goal of this study was to catalog reported adverse events associated with the da Vinci device in head and neck procedures by querying an FDA database. A search was performed on the MAUDE database inspecting for TORS safety incident reports generated from January 2009 through May 2020 using key words "da Vinci" and "Intuitive Surgical". A total of 3312 medical device records were produced. Of these 36 head and neck adverse events, reports were identified through manual screening of the data by the authors. Death was found to be the most common adverse event reported overall, manifesting in 44% of all reported incidents. The most frequent source of mortality was found to be hemorrhaging in the perioperative period rather than incidents of device malfunction or structural damage from surgery. This was found to be similar to the results of other published series for transoral ablative surgery. This study suggests that the small number of reported adverse events related to TORS with the da Vinci system seems to mirror what would be expected from the same procedures using other methods for transoral surgery.

GeneLiFT: A novel test to facilitate rapid screening of genetic literacy in a diverse population undergoing genetic testing.

With the broader introduction of genomic medicine in research and clinical care, an increasing number of persons are offered genetic testing. Many factors, including genetic literacy, may impact the utilization of genetic results by patients and their families. We developed a rapid, self-administered measure of genetic literacy, called Genetic Literacy Fast Test (GeneLiFT). We next evaluated the association of GeneLiFT scores with the comprehension of limitations of genomic medicine in participants undergoing genetic testing in the NIH-sponsored eMERGE III study at Columbia University Irving Medical Center, New York. All participants underwent genetic screening for variants in 74 actionable genes associated with adult-onset disorders. A diverse cohort of 724 participants completed the survey (60% women, 45% less than 40 years old, and 53% self-reported White non-Hispanic ancestry). The GeneLiFT was validated using known group differences based on education, health literacy, and numeracy, and with questions assessing genetic knowledge. GeneLiFT identified multiple standard genetics terms, that is, jargon, not recognized by more than 50% of participants (including actionability and pathogenicity). Low genetic literacy, identified in 210 participants (29%), was significantly associated with poor understanding of the limitations of genetic testing (p-values < 10-9 ). This association was independent of education, health literacy, and numeracy levels, highlighting the importance of directly measuring genetic literacy. Low genetic literacy was also associated with low satisfaction with the informed consent process. GeneLiFT is a practical tool for rapid assessment of genetic literacy in large studies or clinical care. GeneLiFT will allow future research to efficiently assess the role of genetic literacy on the clinical impact of genetic testing.

Multi-Modal Methodology for Adapting Digital Health Tools to New Populations: Adaptation of the Video Information Provider (VIP) for Persons Living with HIV with HIV-Associated Non-AIDS (HANA) Conditions.

The goal of this study was to illustrate the translation of our extant eHealth intervention (VIP) into an mHealth app for persons living with HIV (PLWH) with HIV-Associated non-AIDS (HANA) conditions, a new clinical problem. We integrated different quantitative and qualitative methodologies from different disciplines to accomplish the task of adapting an eHealth system for a new set of clinical problems. Building off of our past development of the VIP website, we used a multi-modal, iterative user-centered design process to develop the VIP-HANA app. Our process was used to better understand the needs of a national sample of PLWH recruited online. Findings from the usability evaluation demonstrate a potentially useful and easy to use app. Integration of multi-modal methodologies from different fields to accomplish the tasks of adaptation and evaluation of a mobile app is an appealing, rigorous and useful approach.

Informatics and Data Science for the Precision in Symptom Self-Management Center.

The goal of the Precision in Symptom Self-Management (PriSSM) Center is to advance the science of symptom self-management for Latinos through a social ecological lens that takes into account variability in individual, interpersonal, organizational, and environmental factors across the life course. Informatics and data science methods are foundational to PriSSM's research activities including its pilot studies and research resources. This work highlights three areas: Latino Data Repository, Information Visualization, and Center Evaluation.

A systematic review of natural language processing and text mining of symptoms from electronic patient-authored text data.

OBJECTIVE: In this systematic review, we aim to synthesize the literature on the use of natural language processing (NLP) and text mining as they apply to symptom extraction and processing in electronic patient-authored text (ePAT). MATERIALS AND METHODS: A comprehensive literature search of 1964 articles from PubMed and EMBASE was narrowed to 21 eligible articles. Data related to purpose, text source, number of users and/or posts, evaluation metrics, and quality indicators were recorded. RESULTS: Pain (n = 18) and fatigue and sleep disturbance (n = 18) were the most frequently evaluated symptom clinical content categories. Studies accessed ePAT from sources such as Twitter and online community forums or patient portals focused on diseases, including diabetes, cancer, and depression. Fifteen studies used NLP as a primary methodology. Studies reported evaluation metrics including the precision, recall, and F-measure for symptom-specific research questions. DISCUSSION: NLP and text mining have been used to extract and analyze patient-authored symptom data in a wide variety of online communities. Though there are computational challenges with accessing ePAT, the depth of information provided directly from patients offers new horizons for precision medicine, characterization of sub-clinical symptoms, and the creation of personal health libraries as outlined by the National Library of Medicine. CONCLUSION: Future research should consider the needs of patients expressed through ePAT and its relevance to symptom science. Understanding the role that ePAT plays in health communication and real-time assessment of symptoms, through the use of NLP and text mining, is critical to a patient-centered health system.

Online cancer communities as informatics intervention for social support: conceptualization, characterization, and impact.

Objectives: The Internet and social media are revolutionizing how social support is exchanged and perceived, making online health communities (OHCs) one of the most exciting research areas in health informatics. This paper aims to provide a framework for organizing research of OHCs and help identify questions to explore for future informatics research. Based on the framework, we conceptualize OHCs from a social support standpoint and identify variables of interest in characterizing community members. For the sake of this tutorial, we focus our review on online cancer communities. Target audience: The primary target audience is informaticists interested in understanding ways to characterize OHCs, their members, and the impact of participation, and in creating tools to facilitate outcome research of OHCs. OHC designers and moderators are also among the target audience for this tutorial. Scope: The tutorial provides an informatics point of view of online cancer communities, with social support as their leading element. We conceptualize OHCs according to 3 major variables: type of support, source of support, and setting in which the support is exchanged. We summarize current research and synthesize the findings for 2 primary research questions on online cancer communities: (1) the impact of using online social support on an individual's health, and (2) the characteristics of the community, its members, and their interactions. We discuss ways in which future research in informatics in social support and OHCs can ultimately benefit patients.

Correlates of Dominicans' Identification of Cancer as a Worrisome Health Problem.

There is a paucity of studies centering on the correlates of cancer worry among Hispanics from the Dominican Republic and the potential informatics strategies to address such worries. Data were analyzed using descriptive and correlational statistics, and logistic regression with the dependent variable of cancer worry. Independent variables for the regression were: age, gender, marital status, education, socioeconomic status, previous diagnosis of cancer, anxiety, depression, sleep disturbance, and chronic burden. Four variables significantly increased cancer worry: married marital status (OR = 1.19 [95% CI 1.01, 1.41]), younger age (OR = .992 [95% CI 0.987, 0.997]), less depression (OR = .96 [95% CI 0.94, 0.98]), and cancer diagnosis (OR = 2.12 [95% CI 1.24, 3.65]). New knowledge was generated on the contextual factors that influence these health concerns in a major Hispanic sub-group. Implications for practice, research and education are discussed.

Reliability and validity of the patient activation measure in hospitalized patients.

OBJECTIVE: The purposes of this paper are to describe the internal consistency reliability and construct validity of the PAM-13 for hospitalized cardiology and oncology patients and to examine the predictors of low patient activation in the same population. METHODS: We evaluated the internal consistency reliability of the PAM-13 in the inpatient setting. Construct validity of the PAM-13 was then assessed using two approaches: expected known-groups differences between patients with planned and unplanned admissions PAM-13 levels and convergence of PAM-13 levels with other measures. RESULTS: The PAM demonstrated adequate internal consistency overall (Cronbach α=0.81). Patients with unplanned admissions were more likely to have low activation than patients with planned admissions (adjusted OR=5.7, p=0.008). The PAM-13 was modestly correlated (p<0.001) with each of the PROMIS Global Health components used in this study (global, physical and mental health). CONCLUSION: This study demonstrates the PAM-13 is a reliable and valid measure for use in the inpatient hospital setting and that type of admission (planned versus unplanned) is an important predictor of patient activation. PRACTICE IMPLICATIONS: By measuring patient activation with the PAM-13, clinicians and researchers can provide tailored communication and care strategies to meet patient's needs.

Interactive tools for inpatient medication tracking: a multi-phase study with cardiothoracic surgery patients.

OBJECTIVE: Prior studies of computing applications that support patients' medication knowledge and self-management offer valuable insights into effective application design, but do not address inpatient settings. This study is the first to explore the design and usefulness of patient-facing tools supporting inpatient medication management and tracking. MATERIALS AND METHODS: We designed myNYP Inpatient, a custom personal health record application, through an iterative, user-centered approach. Medication-tracking tools in myNYP Inpatient include interactive views of home and hospital medication data and features for commenting on these data. In a two-phase pilot study, patients used the tools during cardiothoracic postoperative care at Columbia University Medical Center. In Phase One, we provided 20 patients with the application for 24-48 h and conducted a closing interview after this period. In Phase Two, we conducted semi-structured interviews with 12 patients and 5 clinical pharmacists who evaluated refinements to the tools based on the feedback received during Phase One. RESULTS: Patients reported that the medication-tracking tools were useful. During Phase One, 14 of the 20 participants used the tools actively, to review medication lists and log comments and questions about their medications. Patients' interview responses and audit logs revealed that they made frequent use of the hospital medications feature and found electronic reporting of questions and comments useful. We also uncovered important considerations for subsequent design of such tools. In Phase Two, the patients and pharmacists participating in the study confirmed the usability and usefulness of the refined tools. CONCLUSIONS: Inpatient medication-tracking tools, when designed to meet patients' needs, can play an important role in fostering patient participation in their own care and patient-provider communication during a hospital stay.

Intercepting wrong-patient orders in a computerized provider order entry system.

STUDY OBJECTIVE: We evaluate the short- and long-term effect of a computerized provider order entry-based patient verification intervention to reduce wrong-patient orders in 5 emergency departments. METHODS: A patient verification dialog appeared at the beginning of each ordering session, requiring providers to confirm the patient's identity after a mandatory 2.5-second delay. Using the retract-and-reorder technique, we estimated the rate of wrong-patient orders before and after the implementation of the intervention to intercept these errors. We conducted a short- and long-term quasi-experimental study with both historical and parallel controls. We also measured the amount of time providers spent addressing the verification system, and reasons for discontinuing ordering sessions as a result of the intervention. RESULTS: Wrong-patient orders were reduced by 30% immediately after implementation of the intervention. This reduction persisted when inpatients were used as a parallel control. After 2 years, the rate of wrong-patient orders remained 24.8% less than before intervention. The mean viewing time of the patient verification dialog was 4.2 seconds (SD=4.0 seconds) and was longer when providers indicated they placed the order for the wrong patient (4.9 versus 4.1 seconds). Although the display of each dialog took only seconds, the large number of display episodes triggered meant that the physician time to prevent each retract-and-reorder event was 1.5 hours. CONCLUSION: A computerized provider order entry-based patient verification system led to a moderate reduction in wrong-patient orders that was sustained over time. Interception of wrong-patient orders at data entry is an important step in reducing these errors.

Response to a mobile health decision-support system for screening and management of tobacco use.

PURPOSE/OBJECTIVES: To describe the predictors of nurse actions in response to a mobile health decision-support system (mHealth DSS) for guideline-based screening and management of tobacco use. DESIGN: Observational design focused on an experimental arm of a randomized, controlled trial. SETTING: Acute and ambulatory care settings in the New York City metropolitan area. SAMPLE: 14,115 patient encounters in which 185 RNs enrolled in advanced practice nurse (APN) training were prompted by an mHealth DSS to screen for tobacco use and select guideline-based treatment recommendations. METHODS: Data were entered and stored during nurse documentation in the mHealth DSS and subsequently stored in the study database where they were retrieved for analysis using descriptive statistics and logistic regressions. MAIN RESEARCH VARIABLES: Predictor variables included patient gender, patient race or ethnicity, patient payer source, APN specialty, and predominant payer source in clinical site. Dependent variables included the number of patient encounters in which the nurse screened for tobacco use, provided smoking cessation teaching and counseling, or referred patients for smoking cessation for patients who indicated a willingness to quit. FINDINGS: Screening was more likely to occur in encounters where patients were female, African American, and received care from a nurse in the adult nurse practitioner specialty or in a clinical site in which the predominant payer source was Medicare, Medicaid, or State Children's Health Insurance Program. In encounters where the patient payer source was other, nurses were less likely to provide tobacco cessation teaching and counseling. CONCLUSIONS: mHealth DSS has the potential to affect nurse provision of guideline-based care. However, patient, nurse, and setting factors influence nurse actions in response to an mHealth DSS for tobacco cessation. IMPLICATIONS FOR NURSING: The combination of a reminder to screen and integration of guideline-based recommendations into the mHealth DSS may reduce racial or ethnic disparities to screening, as well as clinician barriers related to time, training, and familiarity with resources.

Usability testing of a computerized communication tool in a diverse urban pediatric population.

BACKGROUND: Developed in Norway, Sisom is an interactive, rigorously tested, computerized, communication tool designed to help children with cancer express their perceived symptoms/problems. Children travel virtually from island to island rating their symptoms/problems. While Sisom has been found to significantly improve communication in patient consultations in Norway, usability testing is warranted with US children prior to further use in research studies. OBJECTIVE: The objective of this study was to determine the usability of Sisom in a sample of English- and Spanish-speaking children in an urban US community. METHODS: A mixed-methods usability study was conducted with a purposive sample of healthy children and children with cancer. Semistructured interviews were used to assess healthy children's symptom recognition. Children with cancer completed 8 usability tasks captured with Morae 3.3 software. Data were downloaded, transcribed, and analyzed descriptively. RESULTS: Four healthy children and 8 children with cancer participated. Of the 44 symptoms assessed, healthy children recognized 15 (34%) pictorial symptoms immediately or indicated 13 (30%) pictures were good representations of the symptom. Six children with cancer completed all tasks. All children navigated successfully from one island to the next, ranking their symptom/problem severity, clicking the magnifying glass for help, or asking the researcher for assistance. All children were satisfied with the aesthetics and expressed an interest in using Sisom to communicate their symptoms/problems. CONCLUSIONS: A few minor suggestions for improvement and adjustment may optimize the use of Sisom for US children. IMPLICATIONS FOR PRACTICE: Sisom may help clinicians overcome challenges assessing children's complex symptoms/problems in a child-friendly manner.

Essential questions: accuracy, errors and user perceptions in a drag/drop user-composable electronic health record.

In previous work we have described the creation and user testing of a drag/drop user-composable electronic health record, MedWISE. Any new design poses new potential problems; here we discuss the accuracy, potential for new types of errors, and user reactions to the approach, including their perceptions of ease of use and usefulness. Our results come from a mixed methods laboratory study with 18 clinicians at a large academic medical center. 12 used MedWISE and 6 used the conventional system. MedWISE users had comparable assessment accuracy to use of the conventional system, low (1/10) risk of diagnosis momentum error, and overall favorable and even enthusiastic user perception. 10/12 said the system eased their cognitive process, Ease of use and usefulness were rated 3.79 and 4.00 on a 5-point Likert scale. Users were unconcerned about the possibility of increased errors due to their trust in colleagues and system similarities to current practice. After first describing the issues, we suggest a method to elucidate risks in innovative and current systems.

Mobile health-based approaches for smoking cessation resources.

PURPOSE/OBJECTIVES: To describe how the National Cancer Institute's Cancer Information Service (CIS) smoking-related resources on a mobile health (mHealth) platform were integrated into the workflow of RNs in advanced practice nurse (APN) training and to examine awareness and use of CIS resources and nurses' perceptions of the usefulness of those CIS resources. DESIGN: Descriptive analyses. SETTING: Acute and primary care sites affiliated with the School of Nursing at Columbia University. SAMPLE: 156 RNs enrolled in APN training. METHODS: The integration was comprised of (a) inclusion of CIS information into mHealth decision support system (DSS) plan of care, (b) addition of infobutton in the mHealth DSS, (c) Web-based information portal for smoking cessation accessible via desktop and the mHealth DSS, and (d) information prescriptions for patient referral. MAIN RESEARCH VARIABLES: Use and perceived usefulness of the CIS resources. FINDINGS: 86% of nurses used the mHealth DSS with integrated CIS resources. Of the 145 care plan items chosen, 122 were referrals to CIS resources; infobutton was used 1,571 times. Use of CIS resources by smokers and healthcare providers in the metropolitan area of New York City increased during the study period compared to the prestudy period. More than 60% of nurses perceived CIS resources as useful or somewhat useful. CONCLUSIONS: Integration of CIS resources into an mHealth DSS was seen as useful by most participants. IMPLICATIONS FOR NURSING: Implementation of evidence into workflow using an mHealth DSS can assist nurses in managing smoking cessation in patients and may expand their roles in referring smokers to reliable sources of information. KNOWLEDGE TRANSLATION: mHealth DSS and information prescriptions may support smoking cessation interventions in primary care settings. Smoking cessation interventions can be facilitated through informatics methods and mHealth platforms. Nurses' referrals of patients to smoking-related CIS resources may result in patients' use of the resources and subsequent smoking cessation.