Dataset Information

Research on Injury Disparities: A Scoping Review.

ABSTRACT: Background: Research on disparities in traumatic injury has not been well characterized, limiting understanding of gaps in research and development of successful interventions. We conducted a scoping review to identify and synthesize research on disparities in intentional and unintentional traumatic injuries. Methods: The review was guided by PRISMA Extension for Scoping Reviews. PubMed, PsycINFO, Web of Science, and CINAHL and systematic reviews from 2007 to 2017 were searched. Eligible articles were peer reviewed; conducted in the United States; and reported on clearly defined physical trauma and disparity, defined by Cochrane PROGRESS-Plus criteria. One reviewer assessed article titles and a second reviewer validated the inclusion with a random sample. Abstract and full-text review by two reviewers determined final inclusion. Results: Of 7382 unique articles screened, 653 articles were included; inter-rater agreement was high (K=0.995). Studies reported on disparities in the acute hospital setting (104) or postacute/rehabilitation (86), with fewer focused on prevention (57) and policy development (6). Research methods used were quantitative (593) with 25 intervention studies, qualitative (45), qualitative/quantitative (7), and community-based participatory research (8). Age ranges of included studies were all ages (124), adults (318), pediatric/youth/adolescents (172), and older adults (40). Racial disparities were most commonly measured (439 studies); 38 created a white/nonwhite binary. Other commonly measured disparities were place of residence (122), insurance (111 studies), gender (89), age (75), and socioeconomic status measures (61). Disparities were noted in all of the categories. Studies commonly aggregated all types of traumatic injuries (129) or all types of violence (105). Conclusions: The extant injury literature lacks research on prevention and policy to address disparities. Many studies aggregated types of trauma and patient groups, preventing an understanding of distinctions between groups and potential interventions. Intervention and community-based research strategies were limited. Future research can better specify measurement of understudied equity categories, trauma types and intent, and racial groups.

SUBMITTER: Moore M

PROVIDER: S-EPMC6798805 | biostudies-other | 2019

REPOSITORIES: biostudies-other

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Research on Injury Disparities: A Scoping Review.

Moore Megan M Conrick Kelsey M KM Fuentes Molly M Rowhani-Rahbar Ali A Graves Janessa M JM Patil Divya D Herrenkohl Madeline M Mills Brianna B Rivara Frederick P FP Ebel Beth B Vavilala Monica S MS

Health equity 20191017 1

<b>Background:</b> Research on disparities in traumatic injury has not been well characterized, limiting understanding of gaps in research and development of successful interventions. We conducted a scoping review to identify and synthesize research on disparities in intentional and unintentional traumatic injuries. <b>Methods:</b> The review was guided by PRISMA Extension for Scoping Reviews. PubMed, PsycINFO, Web of Science, and CINAHL and systematic reviews from 2007 to 2017 were searched. El ...[more]

PMID: 31637361

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Project description:BackgroundHealth systems and providers across America are increasingly employing telehealth technologies to better serve medically underserved low-income, minority, and rural populations at the highest risk for health disparities. The Patient-Centered Outcomes Research Institute (PCORI) has invested US $386 million in comparative effectiveness research in telehealth, yet little is known about the key early lessons garnered from this research regarding the best practices in using telehealth to address disparities.ObjectiveThis paper describes preliminary lessons from the body of research using study findings and case studies drawn from PCORI seminal patient-centered outcomes research (PCOR) initiatives. The primary purpose was to identify common barriers and facilitators to implementing telehealth technologies in populations at risk for disparities.MethodsA systematic scoping review of telehealth studies addressing disparities was performed. It was guided by the Arksey and O'Malley Scoping Review Framework and focused on PCORI's active portfolio of telehealth studies and key PCOR identified by study investigators. We drew on this broad literature using illustrative examples from early PCOR experience and published literature to assess barriers and facilitators to implementing telehealth in populations at risk for disparities, using the active implementation framework to extract data. Major themes regarding how telehealth interventions can overcome barriers to telehealth adoption and implementation were identified through this review using an iterative Delphi process to achieve consensus among the PCORI investigators participating in the study.ResultsPCORI has funded 89 comparative effectiveness studies in telehealth, of which 41 assessed the use of telehealth to improve outcomes for populations at risk for health disparities. These 41 studies employed various overlapping modalities including mobile devices (29/41, 71%), web-based interventions (30/41, 73%), real-time videoconferencing (15/41, 37%), remote patient monitoring (8/41, 20%), and store-and-forward (ie, asynchronous electronic transmission) interventions (4/41, 10%). The studies targeted one or more of PCORI's priority populations, including racial and ethnic minorities (31/41, 41%), people living in rural areas, and those with low income/low socioeconomic status, low health literacy, or disabilities. Major themes identified across these studies included the importance of patient-centered design, cultural tailoring of telehealth solutions, delivering telehealth through trusted intermediaries, partnering with payers to expand telehealth reimbursement, and ensuring confidential sharing of private information.ConclusionsEarly PCOR evidence suggests that the most effective health system- and provider-level telehealth implementation solutions to address disparities employ patient-centered and culturally tailored telehealth solutions whose development is actively guided by the patients themselves to meet the needs of specific communities and populations. Further, this evidence shows that the best practices in telehealth implementation include delivery of telehealth through trusted intermediaries, close partnership with payers to facilitate reimbursement and sustainability, and safeguards to ensure patient-guided confidential sharing of personal health information.

Project description:INTRODUCTION:The rising popularity of social media, since their inception around 20 years ago, has been echoed in the growth of health-related research using data derived from them. This has created a demand for literature reviews to synthesise this emerging evidence base and inform future activities. Existing reviews tend to be narrow in scope, with limited consideration of the different types of data, analytical methods and ethical issues involved. There has also been a tendency for research to be siloed within different academic communities (eg, computer science, public health), hindering knowledge translation. To address these limitations, we will undertake a comprehensive scoping review, to systematically capture the broad corpus of published, health-related research based on social media data. Here, we present the review protocol and the pilot analyses used to inform it. METHODS:A version of Arksey and O'Malley's five-stage scoping review framework will be followed: (1) identifying the research question; (2) identifying the relevant literature; (3) selecting the studies; (4) charting the data and (5) collating, summarising and reporting the results. To inform the search strategy, we developed an inclusive list of keyword combinations related to social media, health and relevant methodologies. The frequency and variability of terms were charted over time and cross referenced with significant events, such as the advent of Twitter. Five leading health, informatics, business and cross-disciplinary databases will be searched: PubMed, Scopus, Association of Computer Machinery, Institute of Electrical and Electronics Engineers and Applied Social Sciences Index and Abstracts, alongside the Google search engine. There will be no restriction by date. ETHICS AND DISSEMINATION:The review focuses on published research in the public domain therefore no ethics approval is required. The completed review will be submitted for publication to a peer-reviewed, interdisciplinary open access journal, and conferences on public health and digital research.

Project description:BackgroundData provenance refers to the origin, processing, and movement of data. Reliable and precise knowledge about data provenance has great potential to improve reproducibility as well as quality in biomedical research and, therefore, to foster good scientific practice. However, despite the increasing interest on data provenance technologies in the literature and their implementation in other disciplines, these technologies have not yet been widely adopted in biomedical research.ObjectiveThe aim of this scoping review was to provide a structured overview of the body of knowledge on provenance methods in biomedical research by systematizing articles covering data provenance technologies developed for or used in this application area; describing and comparing the functionalities as well as the design of the provenance technologies used; and identifying gaps in the literature, which could provide opportunities for future research on technologies that could receive more widespread adoption.MethodsFollowing a methodological framework for scoping studies and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines, articles were identified by searching the PubMed, IEEE Xplore, and Web of Science databases and subsequently screened for eligibility. We included original articles covering software-based provenance management for scientific research published between 2010 and 2021. A set of data items was defined along the following five axes: publication metadata, application scope, provenance aspects covered, data representation, and functionalities. The data items were extracted from the articles, stored in a charting spreadsheet, and summarized in tables and figures.ResultsWe identified 44 original articles published between 2010 and 2021. We found that the solutions described were heterogeneous along all axes. We also identified relationships among motivations for the use of provenance information, feature sets (capture, storage, retrieval, visualization, and analysis), and implementation details such as the data models and technologies used. The important gap that we identified is that only a few publications address the analysis of provenance data or use established provenance standards, such as PROV.ConclusionsThe heterogeneity of provenance methods, models, and implementations found in the literature points to the lack of a unified understanding of provenance concepts for biomedical data. Providing a common framework, a biomedical reference, and benchmarking data sets could foster the development of more comprehensive provenance solutions.

Project description:The degree to which artificial intelligence healthcare research is informed by data and stakeholders from community settings has not been previously described. As communities are the principal location of healthcare delivery, engaging them could represent an important opportunity to improve scientific quality. This scoping review systematically maps what is known and unknown about community-engaged artificial intelligence research and identifies opportunities to optimize the generalizability of these applications through involvement of community stakeholders and data throughout model development, validation, and implementation. Embase, PubMed, and MEDLINE databases were searched for articles describing artificial intelligence or machine learning healthcare applications with community involvement in model development, validation, or implementation. Model architecture and performance, the nature of community engagement, and barriers or facilitators to community engagement were reported according to PRISMA extension for Scoping Reviews guidelines. Of approximately 10,880 articles describing artificial intelligence healthcare applications, 21 (0.2%) described community involvement. All articles derived data from community settings, most commonly by leveraging existing datasets and sources that included community subjects, and often bolstered by internet-based data acquisition and subject recruitment. Only one article described inclusion of community stakeholders in designing an application-a natural language processing model that detected cases of likely child abuse with 90% accuracy using harmonized electronic health record notes from both hospital and community practice settings. The primary barrier to including community-derived data was small sample sizes, which may have affected 11 of the 21 studies (53%), introducing substantial risk for overfitting that threatens generalizability. Community engagement in artificial intelligence healthcare application development, validation, or implementation is rare. As healthcare delivery occurs primarily in community settings, investigators should consider engaging community stakeholders in user-centered design, usability, and clinical implementation studies to optimize generalizability.

Dataset Information

Research on Injury Disparities: A Scoping Review.

Publications

Research on Injury Disparities: A Scoping Review.

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