Electronic Repositories Research Articles

Utilizing data to foster equity in infection prevention outreach among skilled nursing facilities in Michigan

Background: Since October 2020, the Infection Prevention Resource and Assessment Team (IPRAT) has provided infection prevention guidance and support to congregate-care settings throughout Michigan. Specifically, outreach to skilled nursing facilities (SNFs) in response to reported positive COVID-19 resident and staff cases. Case rates provide limited data and do not factor in additional variables, such as staffing shortages, geographical location, or access to supplies, which can increase the vulnerability of staff and residents to outbreaks. To facilitate equitable outreach, a risk assessment was developed using variables related to infection prevention and poor COVID-19 outcomes utilizing local, state, and federal data reporting websites. Methods: A retrospective data review of IPRAT’s electronic data repository was performed, and 2 distinct periods were identified between November 6, 2020, and December 5, 2022. Outreach method 1 involved only using case counts from November 6, 2020, to September 24, 2021. Outreach method 2 (new risk-assessment–based outreach) involved additional data points from April 12, 2021, to December 5, 2022. Data included 17 self-reported items from the NHSN, 3 characteristics regarding facilities’ COVID-19 units, and 7 community-level variables derived from county vaccine rates, social vulnerability index (SVI), and COVID-19 community transmission level. The scoring of each data point ranged from 0–10, and outreach was prioritized to facilities with the highest overall scores. Successful referrals (resulting in a site visit) were compared to the SVI and healthcare emergency regional maps to determine whether the new outreach method reached more facilities in vulnerable communities. Results: Of 358 outreach attempts, IPRAT had a higher success rate with method 2 (6.9%) compared to method 1 (5.3%) and improved outreach in rural Michigan regions 7 and 8 (15% vs 3%). Site visits in counties with a high SVI rating with method 2 were 14.5% versus 10.6% using method 1. COVID-19 prevention referral success rates were higher (4.4% vs 3.1%) using method 2. Conclusions: The risk-assessment–based outreach method showed improvement in overall referral success rates among facilities in rural and higher-SVI counties. These communities tend to experience higher health disparities and poorer health outcomes. Incorporating the more nuanced data variables correlated with at-risk congregate-care settings receiving timelier outreach. The limitations of the study include sample size, period of data collected (2 years), and the complexity of objectively measuring equity.Disclosures: None

Developing electronic clinical quality measures to assess the cancer diagnostic process.

Measures of diagnostic performance in cancer are underdeveloped. Electronic clinical quality measures (eCQMs) to assess quality of cancer diagnosis could help quantify and improve diagnostic performance. We developed 2 eCQMs to assess diagnostic evaluation of red-flag clinical findings for colorectal (CRC; based on abnormal stool-based cancer screening tests or labs suggestive of iron deficiency anemia) and lung (abnormal chest imaging) cancer. The 2 eCQMs quantified rates of red-flag follow-up in CRC and lung cancer using electronic health record data repositories at 2 large healthcare systems. Each measure used clinical data to identify abnormal results, evidence of appropriate follow-up, and exclusions that signified follow-up was unnecessary. Clinicians reviewed 100 positive and 20 negative randomly selected records for each eCQM at each site to validate accuracy and categorized missed opportunities related to system, provider, or patient factors. We implemented the CRC eCQM at both sites, while the lung cancer eCQM was only implemented at the VA due to lack of structured data indicating level of cancer suspicion on most chest imaging results at Geisinger. For the CRC eCQM, the rate of appropriate follow-up was 36.0% (26 746/74 314 patients) in the VA after removing clinical exclusions and 41.1% at Geisinger (1009/2461 patients; P < .001). Similarly, the rate of appropriate evaluation for lung cancer in the VA was 61.5% (25 166/40 924 patients). Reviewers most frequently attributed missed opportunities at both sites to provider factors (84 of 157). We implemented 2 eCQMs to evaluate the diagnostic process in cancer at 2 large health systems. Health care organizations can use these eCQMs to monitor diagnostic performance related to cancer.

Bipartite Ranking Fairness Through a Model Agnostic Ordering Adjustment.

Recently, with the applications of algorithms in various risky scenarios, algorithmic fairness has been a serious concern and received lots of interest in machine learning community. In this article, we focus on the bipartite ranking scenario, where the instances come from either the positive or negative class and the goal is to learn a ranking function that ranks positive instances higher than negative ones. We are interested in whether the learned ranking function can cause systematic disparity across different protected groups defined by sensitive attributes. While there could be a trade-off between fairness and performance, we propose a model agnostic post-processing framework xOrder for achieving fairness in bipartite ranking and maintaining the algorithm classification performance. In particular, we optimize a weighted sum of the utility as identifying an optimal warping path across different protected groups and solve it through a dynamic programming process. xOrder is compatible with various classification models and ranking fairness metrics, including supervised and unsupervised fairness metrics. In addition to binary groups, xOrder can be applied to multiple protected groups. We evaluate our proposed algorithm on four benchmark data sets and two real-world patient electronic health record repositories. xOrder consistently achieves a better balance between the algorithm utility and ranking fairness on a variety of datasets with different metrics. From the visualization of the calibrated ranking scores, xOrder mitigates the score distribution shifts of different groups compared with baselines. Moreover, additional analytical results verify that xOrder achieves a robust performance when faced with fewer samples and a bigger difference between training and testing ranking score distributions.

Հայագիտական և տեղեկատու մատենագիտության ենթաբաժնի քարտարանների դերն ու նշանակությունը

Thus, Armenian studies and Earth science are of great importance in the preservation, development and transmission of written heritage to the next generations. Bibliographic theories, seminars, discussions and exhibitions are organized on the basis of theoretical knowledge and acquired experience. In the era of modern technological developments, Armenian studies and reference bibliographic works are carried out most effectively. In addition to paper card files, electronic card files and repositories are also of great informational importance, which enable a wide range of readers to use the Armenian printed cultural heritage without mediation. It should be added that a number of issues of updating and management of bibliographic and information files related to the digitization of files remain controversial.

Завдання цифрової трансформації науково-інформаційного середовища

The article discusses the issues of building interoperable scientific and informational structures based on the use of modern information technologies. Tasks related to the creation of theoretical and methodological foundations for the development of the Ukrainian fragment of the global digital interoperable environment of scientific knowledge are defined. The importance of permanent and unambiguous identification of digital resources to ensure their availability and reusability is noted. A synergistic approach to building an integrated digital environment of publishing houses and libraries is proposed. Attention is paid to the need to create a cooperative cataloging center in Ukraine to ensure one-time entry of scientific data and their subsequent multiple and multifaceted use by all interested institutions. The need for a fundamental solution to the problem of functional interaction of the conglomerate of scientific and information structures is emphasized, which will require the development of a new generation of information systems in which the problem of interoperability will be considered one of the main ones. Ukraine’s successes in creating electronic repositories are noted.

Bibliometric analysis in retrospective of the qualitative development&#x0D; of the journal «Forests of Russia and economy in them»

A qualitative assessment of the development of the journal in retrospect was given on the basis of bibliometric analysis on various parameters: topics, geography of research, citation rate, number of articles per issue. The main subject of the study was electronic versions of the journal in the electronic repository of the university. As a result of the analysis, a characteristic of the “scientific identity” of the journal was compiled, expressed in the scientific interests of the authors in the fields of reforestation, forest taxation, forest pyrology, and the study of individual forest crops, more commonly, of Scots pine. Based on the data obtained, the dependence of citation on correctly presented metadata was&#x0D; revealed. The positive dynamics of citation of works over time&#x0D; indicates the relevance of the subject in the scientific community. At the same time, on the basis of data on the absence of positive dynamics in the expansion of the geography of research in publications it is concluded that it is necessary to change the editorial policy to attract authors from other regions for further qualitative growth of the journal.

The Impact of Virtual Reality in Medical Ionizing Radiation Sciences Education: A Systematic Review of the International Literature

Studies in medical ionizing radiation sciences apply to a wide range of medical and allied health professions. The students in those sciences learn the basic principles and effects of ionizing radiation on patients for diagnostic and therapeutic purposes, as well as the theoretical background in biomedical equipment operation. It is fundamental for those students to receive proper hands-on training, to successfully connect the theory with practice. In addition, the COVID-19 pandemic has pushed education to a new normal, establishing the use of emerging technologies to facilitate distance learning and virtual interaction. In this paper, we reviewed the literature for applications of virtual reality (VR) learning environments in the education of medical ionizing radiation sciences. We performed a literature search in the databases PubMed and Epistemonikos for the last decade (2012-2022), using combinations of keywords. We also performed a manual search in ResearchGate electronic repository. We identified 15 studies investigating the impact of the application of VR learning environments on students in medicine and allied health professions relevant to medical ionizing radiation sciences. The application of VR can lead to the improvement of learning outcomes, the development of clinical and soft skills, facilitate the comprehension of theoretical concepts through visualization and increase the level of confidence of students before clinical practice. In addition, it is an attractive method of training, offering the benefits of repetition and practice in a safe environment for the students. None of the studies refer that VR learning environments have replaced the clinical placements of the students, which are considered a critical component of their clinical practice. Concluding, there is only a little, regional, and relatively recent quantitative evidence, demonstrating the successful incorporation of VR learning environments in curricula of medical ionizing radiation sciences. From our perspective, VR can become a valuable pedagogical tool for those curricula, helping the connection of theory with clinical practice and enhancing the confidence of students.

Machine learning computational tools to assist the performance of systematic reviews: A mapping review

BackgroundWithin evidence-based practice (EBP), systematic reviews (SR) are considered the highest level of evidence in that they summarize the best available research and describe the progress in a determined field. Due its methodology, SR require significant time and resources to be performed; they also require repetitive steps that may introduce biases and human errors. Machine learning (ML) algorithms therefore present a promising alternative and a potential game changer to speed up and automate the SR process. This review aims to map the current availability of computational tools that use ML techniques to assist in the performance of SR, and to support authors in the selection of the right software for the performance of evidence synthesis.MethodsThe mapping review was based on comprehensive searches in electronic databases and software repositories to obtain relevant literature and records, followed by screening for eligibility based on titles, abstracts, and full text by two reviewers. The data extraction consisted of listing and extracting the name and basic characteristics of the included tools, for example a tool’s applicability to the various SR stages, pricing options, open-source availability, and type of software. These tools were classified and graphically represented to facilitate the description of our findings.ResultsA total of 9653 studies and 585 records were obtained from the structured searches performed on selected bibliometric databases and software repositories respectively. After screening, a total of 119 descriptions from publications and records allowed us to identify 63 tools that assist the SR process using ML techniques.ConclusionsThis review provides a high-quality map of currently available ML software to assist the performance of SR. ML algorithms are arguably one of the best techniques at present for the automation of SR. The most promising tools were easily accessible and included a high number of user-friendly features permitting the automation of SR and other kinds of evidence synthesis reviews.

Clinical remission in paired phase two and three studies in inflammatory bowel disease: a systematic review with meta-analysis.

Discrepancies in phase two and three studies can result in significant patient and financial burden, as well as the nonapproval of potentially efficacious drugs. We aimed to determine whether this discrepancy exists for clinical trials in inflammatory bowel disease (IBD). Electronic databases (MEDLINE and Embase) and clinical trial repositories were searched from 1 January 1946 to 12 March 2021, for paired phase two and three studies of advanced therapies for Crohn's disease and ulcerative colitis. The primary outcome was to compare clinical remission rates between paired phase two and three studies for Crohn's disease and ulcerative colitis. Multivariable mixed-model meta-analysis was performed to calculate odds ratios (OR) with 95% confidence intervals (CI). The Cochrane risk-of-bias tool was used to grade the risk of bias. Of 2642 studies, 29 were included. Fifteen were phase three, 11 were phase two, one was phase one/two, and two were phase two/three. There were no differences in clinical remission rates between phase two and three studies for Crohn's disease (OR, 1.07; 95% CI, 0.86-1.34; P = 0.54) and ulcerative colitis (OR, 0.81; 95% CI, 0.48-1.36; P = 0.43). Furthermore, there was a lack of any appreciable differences in study characteristics, inclusion criteria and patient demographics among paired phase two and three studies. Most studies were considered low risk of bias. Overall, paired phase two and three studies demonstrate similar clinical remission rates for advanced therapies in IBD. Whether this applies to newer outcomes, such as endoscopic and mucosal healing remains to be determined.

Collections of the Central Scientific Library named after Yakub Kolas of the National Academy of Sciences of Belarus as a “haven of cartesianism”

TThis article is devoted to exposing and considering the most unique and interesting book monuments stored in the collections of the Central Scientific Library named after Yakub Kolas of the National Academy of Sciences of Belarus. It reveals the features of some copies of the French philosopher and naturalist Rene Descartes’ works dated to the XVII–XX centuries. The main part of the research is based on studying the traces of existence of individual copies from the National Library of the National Academy of Sciences of Belarus, including the lifetime edition of Rene Descartes "Discours sur la method". The description of these copies’ specific features (stamps, records, marks of previous owners) is presented.This study aim consists in demonstrating the need to identify rare and valuable monuments of book culture stored in libraries and often hidden from the employees themselves. The methods used in the study are that of heuristic search and attribution of copies of book culture. The article reflects one of the most relevant and productive areas of research work in academic libraries: that is search, identification and scientific description of book monuments stored in their collections, and their presentation in electronic repositories. The identification of 14 works by Rene Descartes and the description of the most interesting of them has become the result of the study. The material is interesting for library specialists working with rare and ancient documents and engaged in the study and popularization of library collections.

Periodontal disease as a non-traditional risk factor for acute coronary syndrome: a systematic review and meta-analysis.

Previous observational studies have suggested an association between periodontal disease (PD) and cardiovascular and cerebrovascular diseases. Nonetheless, evidence linking PD with coronary heart disease (CHD) and acute coronary syndrome (ACS) is still contradictory. We aim to systematically review the role of PD as a risk factor for ACS (myocardial infarction and unstable angina). The protocol was registered in PROSPERO (CRD42021286278) and we followed the recommendations of the PRISMA and AMSTAR 2 guidelines. We systematically searched for 7 databases and electronic thesis repositories from inception to February 2022. We included articles without language restriction following the PECO strategy (population: "adult participants"; exposure: "periodontal disease"; comparator: "no periodontal disease"; outcome: "acute coronary syndrome" OR "acute myocardial infarction" OR "unstable angina"). Odds ratios (OR) with 95% confidence intervals (95% CI) were pooled using random effects and heterogeneity was quantified by Cochran's Q and Higgins' I2 statistics. Subgroup analyses were carried out according to the participants' sex, type of diagnosis of PD, type of study, and continent of origin of studies. We included 46 papers (17 cohort, 25 case-control, and 4 cross-sectional studies) that met the inclusion criteria. This meta-analysis includes a total of 6,806,286 participants and at least 68,932 ACS events, mainly myocardial infarction (MI). In accordance with our results, PD is associated with a higher risk of ACS (OR 1.35; 95% CI 1.25-1.45). However, clinical and methodological heterogeneity was significant (I2=86%, p<0.05). In the sensitivity analysis, the exclusion of some studies with "extreme" results (outliers) did not significantly affect the overall estimate or heterogeneity. In subgroup analysis, we found no statistically significant differences between men and women according to subgroup difference tests (I2=0%, p=0.67). Conversely, there were differences according to the type of diagnosis of PD (clinical or self-reported diagnosis), type of study (cohort, case-control, or cross-sectional study), and the continent of origin (North America, South America, Asia, or Europe) of the studies (I2=79%-96%, p<0.10). Of the 46 studies, only 4 had a high risk of bias. Additionally, the funnel plot suggested publication bias. PD may be an important non-traditional risk factor for ACS. Although, this meta-analysis brings together more studies, and therefore more evidence, than any other previous similar study, its results should be interpreted with caution due to the great heterogeneity and the potential presence of bias.

Concurrent validity of the marijuana purchase task: a meta-analysis of trait-level cannabis demand and cannabis involvement.

The Marijuana Purchase Task (MPT) is increasingly used to measure cannabis reinforcing value and has potential use for cannabis etiological and regulatory research. This meta-analysis sought to evaluate for the first time the MPT's concurrent validity in relation to cannabis involvement. Electronic databases and pre-print repositories were searched for MPT studies that examined the cross-sectional relationship between frequency and quantity of cannabis use, problems, dependence, and five MPT indicators: intensity (i.e. unrestricted consumption), Omax (i.e. maximum consumption), Pmax (i.e. price at which demand becomes elastic), breakpoint (i.e. first price at which consumption ceases), and elasticity (i.e. sensitivity to rising costs). Random effects meta-analyses of cross-sectional effect sizes were conducted, with Q tests for examining differences by cannabis variables, meta-regression to test quantitative moderators, and publication bias assessment. Moderators included sex, number of MPT prices, variable transformations, and year of publication. Populations included community and clinical samples. The searches yielded 14 studies (n = 4077, median % females: 44.8%: weighted average age = 29.08 [SD = 6.82]), published between 2015 and 2022. Intensity, Omax , and elasticity showed the most robust concurrent validity (|r's| = 0.147-325, ps < 0.014) with the largest significant effect sizes for quantity (|r| intensity = 0.325) and cannabis dependence (|r| Omax = 0.320, |r| intensity = 0.305, |r| elasticity = 0.303). Higher proportion of males was associated with increased estimates for elasticity-quantity and Pmax -problems. Higher number of MPT prices significantly altered magnitude of effects sizes for Pmax and problems, suggesting biased estimations if excessively low prices are considered. Methodological quality was generally good, and minimal evidence of publication bias was observed. The marijuana purchase task presents adequateconcurrent validity to measure cannabis demand, most robustly for intensity, Omax , and elasticity. Moderating effects by sex suggest potentially meaningful sex differences in the reinforcing value of cannabis.

Evaluation of Evidence-based Presentations in a Postgraduate Program at a U.S. Dental Institution: A Retrospective Study

Objective: The objective of this retrospective study was to appraise the level of evidence of presentations gathered from an electronic repository of an advanced postgraduate program in pediatric dentistry at a single U.S.-based dental institute. Methods: After the ethical approval was obtained, the presentations were assessed, and themes were identified. Using the cited references, the respective level of evidence was collected based on: the year of publication, reference source, choice of journal, journal impact factor, study design, altmetric score of the articles, and h-index of the authors. STATA version 15.1 (College Station, TX, USA) and Microsoft Excel software were used for statistical analysis. Results and Discussion: A sum of 690 references between the years 2015 to 2020 have been used in a total of 74 presentations. Presentations related to special health care needs accounted for 29.7% (n= 22) of the total presentations; followed by oral diagnosis/pathology/medicine (n= 17; 23%). The median number of references used in each presentation was eight, and the most common study design was unfiltered. The median number of the first author’s h-index was 25, and the median number of the altmetric score was four. Conclusion: This study appraised the level of evidence used in resident presentations in a postgraduate program in pediatric dentistry at a U.S. dental institute. The findings of this study could provide useful data to postgraduate program directors who wish to address the level of evidence used in their programs. Additionally, by using the altmetric scores and h-indexes presented in this study, future studies can compare the level of evidence between similar academic institutions or programs.

Assessment of the quality and content of clinical practice guidelines (CPGs) for vitamin D and for immigrants using the AGREE-II instrument: a protocol for systematic review

IntroductionWorldwide, more immigrants experience vitamin D (vitD) deficiency than non-immigrants, which is attributed to ethnic variations, place or region of birth, skin pigmentation, clothing style, and resettlement-related changes in diet, physical activity, and sun exposure. Current recommendations in clinical practice guidelines (CPGs) concerning vitD are inadequate to address vitD deficiency among immigrants. CPGs may also lack guidance for physicians on vitD supplementation for immigrants. Moreover, there are concerns about the overall quality of these CPGs.ObjectivesThis systematic review will collate and critically appraise CPGs relevant to immigrants’ health and vitD. Moreover, we will evaluate whether the CPGs of vitD including recommendations for immigrants and clarify whether the CPGs of immigrants include recommendations on vitD.MethodsA systematic search of Ovid MEDLINE® ALL, EMBASE, and Turning Research Into Practice (TRIP) electronic databases, guideline repositories, and gray literature will be conducted to identify relevant CPGs. Two reviewers will independently evaluate the methodological quality of the retrieved guidelines using the Appraisal of Guidelines, Research, and Evaluation-II (AGREE-II) instrument. CPGs scoring ≥60% in at least four domains, including “rigor of development,” will be considered high quality.ConclusionEvaluating the quality and content of relevant CPGs may support researchers in developing national and global guidelines for immigrants. Furthermore, it may support vitD testing, nutritional counseling, and supplementation for vulnerable immigrant sub-populations.Systematic review registrationPROSPERO CRD42021240562.

The creativity model of age and innovation with IT: why older users are less innovative and what to do about it

ABSTRACT To realise the full potential of their information technology (IT) infrastructure, successful firms encourage users to innovate with IT. However, older users are much less innovative with IT than younger ones. This situation is alarming because the workforce is ageing rapidly at the very same time as organisational technologies are proliferating. Using the concepts of mediation and moderation, the present investigation proposes the creativity model of age and innovation with IT. This model postulates that the age differences in user innovation are due to age-related changes in the perceived ability to be creative with IT. It also postulates that the negative effect of age on user innovation can be mitigated by three factors: job control, IT support, and user enjoyment. Two studies were conducted to test the model. The first one was a large-scale survey of IT users who work with various technologies, and the second one was a more specific survey of knowledge workers who use electronic knowledge repositories. The results largely support the model. Thus the model provides a well-founded theoretical framework, not only for explaining why older users are less innovative with IT, but also for determining what managers and systems designers should do about it.

Natural Language Processing of Symptoms Preceding Diagnosis and Palliative Radiotherapy for Bone Metastases

<h3>Purpose/Objective(s)</h3> In patients with bone metastases (BM), the goal of palliative radiotherapy (RT) is to ameliorate pain and other symptoms. We sought to apply natural language processing (NLP) techniques to routine clinical documentation to characterize symptoms associated with diagnosis of BM and initiation of palliative RT. We hypothesized that there may be disparities in symptom presentation for patients with BM receiving palliative RT. <h3>Materials/Methods</h3> We used International Classification of Diseases (ICD) codes along with Current Procedural Terminology (CPT) codes to create a de-identified, single tertiary-care institution cohort of patients with BM who received palliative external beam RT or stereotactic body RT between 2013 and 2021. Clinical data, clinical notes, and meta-data on clinical notes for the patient cohort were computationally extracted from an institutional electronic health record repository. We applied a previously validated clinical Text Analysis and Knowledge Extraction System (cTAKES) pipeline to extract Common Terminology Criteria for Adverse Events (CTCAE) encoded symptoms from all notes in the 30 days preceding BM diagnosis and in the 30 days preceding each course of palliative RT. Chi-squared tests were used to compare symptom distributions across groups. <h3>Results</h3> There were 1,021 patients who received 1,551 courses of palliative RT for BM. Median age at BM diagnosis was 63 years (IQR: 54-71). Median time from BM diagnosis to first course of palliative RT for BM was 2.3 months (IQR: 0.7-14.9). Most patients were male (57.5%), English-speaking (86.2%), and white (59.2%). The most common symptoms prior to BM diagnosis were pain (75.6%), nausea (44.9%), fatigue (41.6%), and palpation of a mass (38.4%). Across RT courses, the most common symptoms prior to palliative RT were pain (90.4%), nausea (67.9%), fatigue (67.6%), and constipation (54.2%). On subgroup analysis of symptoms prior to RT, there were increased NLP-derived reports of pain in clinical notes among patients who were female (94.9% vs male: 87.0%, p < 0.001), non-white (93.3% vs white: 88.8%, p = 0.007), and non-English speaking (97.0% vs English: 89.5%, p = 0.002). Compared to their respective counterparts, female (33.2% vs male: 24.6%, p < 0.001) and non-English speaking patients (36.5% vs English: 27.2%, p = 0.012) were more likely to have experienced pathologic fractures prior to RT. <h3>Conclusion</h3> Patients who were women, non-white, or non-English speaking were documented to have higher rates of pain and/or pathologic fracture prior to palliative RT. These findings may reflect disparities in patient presentation, clinical documentation, or decision-making for which patients are offered palliative RT sooner in the disease trajectory. Future research coupling NLP techniques with machine learning may be useful for predicting which patients would benefit most from earlier initiation of palliative RT.

Rural and Urban Hispanic Patients of the Veterans Health Administration.

Hispanic Veterans are the largest growing racial and ethnic minority group in the Veterans Health Administration (VA) system. Though recent research has found increasing suicide rates in this population and a growing rural-urban disparity, literature on core population characteristics remains sparse. We used extensive patient demographic and clinical data from VA's electronic medical record repository to examine geographic and longitudinal variation in Hispanic VA patients from 2001 to 2018. As the first such detailed characterization of this population, this study was largely descriptive in nature, and included heatmaps of Hispanic patient residence across rural and urban US counties, along with descriptive measures of patient characteristics by rurality, and first year of VA use. We found that Hispanic patients (n = 722,893) represented 5.2% of new VA users between 2001 and 2018, a proportion which grew nearly 90% from 4.0% (2001-2006) to 7.5% (2013-2018). Hispanic patients were largely White, male, under age 50, and had minimal illness or disability. The highest prevalence of Hispanic patients was in the Southwest US/Mexico border region, while the Midwest experienced the largest growth of Hispanic patients. Rural Hispanic patients were more likely to be older, male, and to live in areas characterized by small foreign-born populations and high socioeconomic deprivation. Compared with Hispanic patients entering the VA system in 2001-2006, patients in 2013-2018 were younger, more likely to be female, and to live in urban areas. These findings illustrate the wide range of demographic, clinical, and geographic experiences in the growing VA Hispanic population and demonstrate that culturally competent care for Hispanic Veterans must reflect their intra-ethnic diversity.

The Approaches Utilized in Queuing Modeling: A Systematic Literature Review

Queue scheduling is an important process that is used when processes can be divided into different classes based on the scheduling needs. In general, queue lengths and waiting times can be predicted with the use of a queuing model; especially, the importance of the services provided by any sector or organization for delivering effective services to their consumers highly depends on managing the queues in an effective manner. So, in general, analyzing and evaluating queues is more significant in fulfilling customer needs in a limited time. The applications and tactics developed earlier would not provide satisfactory solutions to solve this problem. But the studies done in the recent past have utilized newer technologies. Especially by incorporating Machine Learning techniques and various queuing models. During this study, a thorough analysis was carried out to discover the different strategies used in optimizing the queues by presenting a Systematic Literature Review (SLR) by examining available research perspective to queue management systems from 2016 to 2022. Initially 200 studies selected using seven electronic repositories and finally selected 14 for this analysis. The study’s findings reveals that most of the studies have used machine learning approaches, utilizing tools like ARENA,SIMIO and adapting various queuing algorithms to solve this problem.

Driver drowsiness detection methods using EEG signals: a systematic review

Electroencephalography (EEG) is a complex signal that may require several years of training, advanced signal processing, and feature extraction methodologies to interpret correctly. Recently, many methods have been used to extract and classify EEG data. This study reviews 62 papers that used EEG signals to detect driver drowsiness, published between January 2018 and 2022. We extract trends and highlight interesting approaches from this large body of literature to inform future research and formulate recommendations. To find relevant papers published in scientific journals, conferences, and electronic preprint repositories, researchers searched major databases covering the domains of science and engineering. For each investigation, many data items about (1) the data, (2) the channels used, (3) the extraction and classification procedure, and (4) the outcomes were extracted. These items were then analyzed one by one to uncover trends. Our analysis reveals that the amount of EEG data used across studies varies. We saw that more than half the studies used simulation driving experimental. About 21% of the studies used support vector machine (SVM), while 19% used convolutional neural networks (CNN). Overall, we can conclude that drowsiness and fatigue impair driving performance, resulting in drivers who are more exposed to risky situations.

Adamant: a JSON schema-based metadata editor for research data management workflows.

The web tool Adamant has been developed to systematically collect research metadata as early as the conception of the experiment. Adamant enables a continuous, consistent, and transparent research data management (RDM) process, which is a key element of good scientific practice ensuring the path to Findable, Accessible, Interoperable, Reusable (FAIR) research data. It simplifies the creation of on-demand metadata schemas and the collection of metadata according to established or new standards. The approach is based on JavaScript Object Notation (JSON) schema, where any valid schema can be presented as an interactive web-form. Furthermore, Adamant eases the integration of numerous available RDM methods and software tools into the everyday research activities of especially small independent laboratories. A programming interface allows programmatic integration with other software tools such as electronic lab books or repositories. The user interface (UI) of Adamant is designed to be as user friendly as possible. Each UI element is self-explanatory and intuitive to use, which makes it accessible for users that have little to no experience with JSON format and programming in general. Several examples of research data management workflows that can be implemented using Adamant are introduced. Adamant (client-only version) is available from: https://plasma-mds.github.io/adamant.