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Copyright of Sociología del Trabajo is the property of Universidad Complutense de Madrid and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Itobiad: Journal of the Human & Social Science Researches / İnsan ve Toplum Bilimleri Araştırmaları Dergisi is the property of Itobiad: Journal of the Human & Social Science Researches and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Clinical practice settings have increasingly become dependent on the use of digital or eHealth technologies such as electronic health records. It is vitally important to support nurses in adapting to digitalized health care systems; however, little is known about nursing graduates' experiences as they transition to the workplace. Objective: This study aims to (1) describe newly qualified nurses' experiences with digital health in the workplace, and (2) identify strategies that could help support new graduates' transition and practice with digital health. Methods: An exploratory descriptive qualitative design was used. A total of 14 nurses from Eastern and Western Canada participated in semistructured interviews and data were analyzed using inductive content analysis. Results: Three themes were identified: (1) experiences before becoming a registered nurse, (2) experiences upon joining the workplace, and (3) suggestions for bridging the gap in transition to digital health practice. Findings revealed more similarities than differences between participants with respect to gaps in digital health education, technology-related challenges, and their influence on nursing practice. Conclusions: Digital health is the foundation of contemporary health care; therefore, comprehensive education during nursing school and throughout professional nursing practice, as well as organizational support and policy, are critical pillars. Health systems investing in digital health technologies must create supportive work environments for nurses to thrive in technologically rich environments and increase their capacity to deliver the digital health future. [ABSTRACT FROM AUTHOR]

Background: Given the dearth of resources to support rural public health practice, the solutions in health analytics for rural equity across the northwest dashboard (SHAREdash) was created to support rural county public health departments in northwestern United States with accessible and relevant data to identify and address health disparities in their jurisdictions. To ensure the development of useful dashboards, assessment of usability should occur at multiple stages throughout the system development life cycle. SHAREdash was refined via user-centered design methods, and upon completion, it is critical to evaluate the usability of SHAREdash. Objective: This study aims to evaluate the usability of SHAREdash based on the system development lifecycle stage 3 evaluation goals of efficiency, satisfaction, and validity. Methods: Public health professionals from rural health departments from Washington, Idaho, Oregon, and Alaska were enrolled in the usability study from January to April 2022. The web-based evaluation consisted of 2 think-aloud tasks and a semistructured qualitative interview. Think-aloud tasks assessed efficiency and effectiveness, and the interview investigated satisfaction and overall usability. Verbatim transcripts from the tasks and interviews were analyzed using directed content analysis. Results: Of the 9 participants, all were female and most worked at a local health department (7/9, 78%). A mean of 10.1 (SD 1.4) clicks for task 1 (could be completed in 7 clicks) and 11.4 (SD 2.0) clicks for task 2 (could be completed in 9 clicks) were recorded. For both tasks, most participants required no prompting—89% (n=8) participants for task 1 and 67% (n=6) participants for task 2, respectively. For effectiveness, all participants were able to complete each task accurately and comprehensively. Overall, the participants were highly satisfied with the dashboard with everyone remarking on the utility of using it to support their work, particularly to compare their jurisdiction to others. Finally, half of the participants stated that the ability to share the graphs from the dashboard would be "extremely useful" for their work. The only aspect of the dashboard cited as problematic is the amount of missing data that was present, which was a constraint of the data available about rural jurisdictions. Conclusions: Think-aloud tasks showed that the SHAREdash allows users to complete tasks efficiently. Overall, participants reported being very satisfied with the dashboard and provided multiple ways they planned to use it to support their work. The main usability issue identified was the lack of available data indicating the importance of addressing the ongoing issues of missing and fragmented public health data, particularly for rural communities. [ABSTRACT FROM AUTHOR]

Background: Connecting individuals to existing community resources is critical to addressing social needs and improving population health. While there is much ongoing informatics work embedding social needs screening and referrals into health care systems and their electronic health records, there has been less focus on the digital ecosystem and needs of community-based organizations (CBOs) providing or connecting individuals to these resources. Objective: We used human-centered design to develop a digital platform for CBOs, focused on identification of health and social resources and communication with their clients. Methods: Centered in the Develop phase of the design process, we conducted in-depth interviews in 2 phases with community-based organizational leadership and staff to create and iterate on the platform. We elicited and mapped participant feedback to theory-informed domains from the Technology Acceptance Model, such as Usefulness and Ease of Use, to build the final product and summarized all major design decisions as the platform development proceeded. Results: Overall, we completed 22 interviews with 18 community-based organizational leadership and staff in 2 consecutive Develop phases. After coding of the interview transcripts, there were 4 major themes related to usability, relevance, and external factors impacting use. Specifically, CBOs expressed an interest in a customer relationship management software to manage their client interactions and communications, and they needed specific additional features to address the scope of their everyday work, namely (1) digital and SMS text messaging communication with clients and (2) easy ways to identify relevant community resources based on diverse client needs and various program eligibility criteria. Finally, clear implementation needs emerged, such as digital training and support for staff using new platforms. The final platform, titled "Mapping to Enhance the Vitality of Engaged Neighborhoods (MAVEN)," was completed in the Salesforce environment in 2022, and it included features and functions directly mapped to the design process. Conclusions: Engaging community organizations in user-centered design of a health and social resource platform was essential to tapping into their deep expertise in serving local communities and neighborhoods. Design methods informed by behavioral theory can be similarly employed in other informatics research. Moving forward, much more work will be necessary to support the implementation of platforms specific to CBOs' needs, especially given the resources, training, and customization needed in these settings. [ABSTRACT FROM AUTHOR]

OBJECTIVE: Suicide is of primary public concern for adolescents and young adults (AYAs) who commonly use social media platforms to express their suicidal thoughts and behaviors. Understanding how AYAs communicate their suicide-related thoughts and behaviors in texts can support early detection of suicide risk from their social media posts. Therefore, this study sought to identify themes relevant to suicide risk in AYAs and explore words or terms used by AYAs when they described suicidal thoughts and behaviors. METHOD: This secondary data analysis utilized an existing data set collected from 255 AYAs between 12 and 25 years of age, who provided brief descriptions of how they and their peers expressed their experiences of self-harm, suicidal thinking, and attempts. Text analysis was conducted using KH Coder software. Three-step theory of suicide was used to guide a content analysis to explore the key themes from the narratives. RESULTS: A word co-occurrence network with 24 clusters of words was generated from the text analysis. These word clusters were further grouped into pain or hopelessness, connectedness, and capacity to attempt suicide in the content analysis. Six subthemes corresponding to these three themes were identified to provide detailed information: psychological or physical pain, hopelessness, relationship, help seeking, methods, and outcomes. Moreover, several slang terms and acronyms (e.g., Kermit Sewage Slide, KMS) were also identified. CONCLUSIONS: The findings of this study, including themes and slang terms and acronyms, are valuable to facilitate the use of terms or phrases within social media texts to identify suicide risk in AYAs. [ABSTRACT FROM AUTHOR]

The integration of machine/deep learning and sensing technologies is transforming healthcare and medical practice. However, inherent limitations in healthcare data, namely scarcity, quality, and heterogeneity, hinder the effectiveness of supervised learning techniques which are mainly based on pure statistical fitting between data and labels. In this article, we first identify the challenges present in machine learning for pervasive healthcare and we then review the current trends beyond fully supervised learning that are developed to address these three issues. Rooted in the inherent drawbacks of empirical risk minimization that underpins pure fully supervised learning, this survey summarizes seven key lines of learning strategies, to promote the generalization performance for real-world deployment. In addition, we point out several directions that are emerging and promising in this area, to develop data-efficient, scalable, and trustworthy computational models, and to leverage multi-modality and multi-source sensing informatics, for pervasive healthcare. [ABSTRACT FROM AUTHOR]

Within the field of social reintegration and re-education, this paper presents an educational experience carried out at the Iquitos Penitentiary Center, Lima, Peru, with the aim of providing an introduction to informatics to 25 inmates who volunteered to take part in the project. Twenty students and a teacher from the Scientific University of the South also in Peru, were responsible for initiating the transmission of knowledge from the university to inmates, with the collaboration and participation of the penitentiary coordinator. The main objectives of the case study were to validate both the suitability of the CS unplugged proposal and the adaptability of the L2T2L pedagogic strategy to the transmission of knowledge to adults, specifically penitentiary inmates. This strategy had been originally designed to transmit informatics knowledge from university to primary school. The validity and effectiveness of the experience was assessed using surveys. Results confirm that inmates achieved a good level of understanding when endeavoring to resolve most of the CS unplugged assignments designed for them. It was also seen that L2T2L is adaptable and valid for different scenarios other than those for which it was initially designed. Indeed, it was proven to be valid for transmitting knowledge to the prison population. Finally, it should be pointed out that the experience is easily replicable and that it brings an opportunity to introduce informatics into education programs in prisons, something which can contribute enormously to social reintegration and re-education, facilitating the subsequent reentry of inmates into the community once their period of imprisonment has ended. [ABSTRACT FROM AUTHOR]

Heliophysics and space weather research encompass the effects of solar output on practically the entire Solar System and are fundamentally cross-disciplinary. Cross-domain science investigations, such as in Sun-heliosphere interactions, solar wind-magnetosphere interactions, or magnetosphere-ionosphere coupling, often require the use of data, models, and other digital resources pertaining to different heliophysical domains: the Sun, the solar wind, the magnetosphere, the ionosphere, the thermosphere and the mesosphere. Due to differences in measurement platforms, techniques and instruments, heliophysics data obtained from different domains are diverse and complex, making the resource landscape difficult for untrained users to navigate. Without proper and adequate guidance from domain experts, it is often difficult for early-career scientists and non-domain experts to discover useful datasets and to know from where and how to obtain and understand the data they need to support their research. This paper describes the roles of metadata in providing the identification, location, access protocol, and detailed content description of a digital resource. More specifically, we point out that metadata written according to the Space Physics Archive Search and Extract (SPASE) metadata model are fully compatible with the FAIR principles so that digital resources described using the SPASE model can be uniformly Findable, Accessible, Interoperable, and Reusable. SPASE metadata can thus be the key element, the lingua franca so to speak, that enables unfettered information flow between data systems and services throughout the heliophysics data environment and lowers the understandability barrier of the resources to ensure their independent usability. After describing various components of the heliophysics data environment, their metadata requirements for effective operations, and some essential features of the SPASE metadata model, we then illustrate how metadata in SPASE can enable or facilitate the performance of different science tasks. The current status and future outlook of SPASE are also presented. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Social Research & Behavioral Sciences / Sosyal Araştırmalar ve Davranış Bilimleri Dergisi is the property of Journal of Social Research & Behavioral Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aim:To describe barriers to implementation of diabetic retinopathy (DR) teleretinal screening programs and artificial intelligence (AI) integration at the University of California (UC). Methods:Institutional representatives from UC Los Angeles, San Diego, San Francisco, Irvine, and Davis were surveyed for the year of their program's initiation, active status at the time of survey (December 2021), number of primary care clinics involved, screening image quality, types of eye providers, image interpretation turnaround time, and billing codes used. Representatives were asked to rate perceptions toward barriers to teleretinal DR screening and AI implementation using a 5-point Likert scale. Results:Four UC campuses had active DR teleretinal screening programs at the time of survey and screened between 246 and 2,123 patients at 1–6 clinics per campus. Sites reported variation between poor-quality photos (<5% to 15%) and average image interpretation time (1–5 days). Patient education, resource availability, and infrastructural support were identified as barriers to DR teleretinal screening. Cost and integration into existing technology infrastructures were identified as barriers to AI integration in DR screening. Conclusions:Despite the potential to increase access to care, there remain several barriers to widespread implementation of DR teleretinal screening. More research is needed to develop best practices to overcome these barriers. [ABSTRACT FROM AUTHOR]

INTRODUCTION: The medication regimen complexity-intensive care unit (MRC-ICU) score has been developed and validated as an objective predictive metric for patient outcomes and pharmacist workload in the adult critically ill population. The purpose of this study was to explore the MRC-ICU and other workload metrics in the pediatric ICU (PICU). METHODS: This study was a retrospective cohort of pediatric ICU patients admitted to a single institution between February 2, 2022 - August 2, 2022. Two scores were calculated, including the MRC-ICU and the pediatric Daily Monitoring System (pDMS). Data were extracted from the electronic health record. The primary outcome was the correlation of the MRC-ICU to mortality, as measured by Pearson correlation coefficient. Additionally, the correlation of MRC-ICU to number of orders was evaluated. Secondary analyses explored the correlation of the MRC-ICU with pDMS and with hospital and ICU length of stay. RESULTS: A total of 2,232 patients were included comprising 2,405 encounters. The average age was 6.9 years (standard deviation [SD] 6.3 years). The average MRC-ICU score was 3.0 (SD 3.8). For the primary outcome, MRC-ICU was significantly positively correlated to mortality (0.22 95% confidence interval [CI 0.18 - 0.26]), p<0.05. Additionally, MRC-ICU was significantly positively correlated to ICU length of stay (0.38 [CI 0.34 - 0.41]), p<0.05. The correlation between the MRC-ICU and pDMS was (0.72 [CI 0.70 - 0.73]), p<0.05. CONCLUSION: In this pilot study, MRC-ICU demonstrated an association with existing prioritization metrics and with mortality and length of ICU stay in PICU population. Further, larger scale studies are required. [ABSTRACT FROM AUTHOR]

Purpose: To determine the impact of a business intelligence dashboard tool to optimize automated dispensing cabinets (ADCs). Methods: A pre-post implementation design was used to evaluate key performance indicators (KPI) before and after the implementation of a dashboard tool to optimize ADCs. Eleven ADCs were optimized in 2 phases according to dashboard recommendations: (1) removal of unused medications over 90 days, (2) adjusting periodic automatic replenishment (PAR) levels, and (3) addition of commonly dispensed medications. The KPI measures that were assessed included inventory cost, no. of stocked medications, stockout percentage, vend to refill ratio, and missing dose messages from nursing. An interrupted-time-series regression was used to quantify the impact of ADCs on the means of measured KPIs. Results: Differences in mean distribution of all KPIs, except missing dose, between the pre- and post-ADC periods during the Phase 1 period were statistically significant: inventory cost (54.2 vs 56), stockout percentage (1.55 vs 1.12), vend to refill ratio (6.83 vs 6.14), and missing dose messages (221 vs 229). Only the mean ADC utilization (57.3 vs 64) and missing dose (228 vs 179) were statistically different between the pre- and post-ADC periods in Phase 2. The interrupted-time-series analysis showed that Phase 1 optimization significantly reduced the cost of inventory (β = −$1.238.00, P <.01), no. Stocked medications (β = −8.2, P <.01), percent stockout (β = −.49%, P <.01), vend-to-refill ratio (β = −1.29%, P<.01) and ADC utilization (β = −.2, P <.01). Conclusion: Automated dispensing cabinets optimization, through the use of a dashboard tool, had a positive impact on almost all measured KPIs. [ABSTRACT FROM AUTHOR]

The aim of this study was to assess appropriateness scoring and structured order entry after the implementation of an artificial intelligence (AI) tool for analysis of free-text indications. Advanced outpatient imaging orders in a multicenter health care system were recorded 7 months before (March 1, 2020, to September 21, 2020) and after (October 20, 2020, to May 13, 2021) the implementation of an AI tool targeting free-text indications. Clinical decision support score (not appropriate, may be appropriate, appropriate, or unscored) and indication type (structured, free-text, both, or none) were assessed. The χ2 and multivariate logistic regression adjusting for covariables with bootstrapping were used. In total, 115,079 orders before and 150,950 orders after AI tool deployment were analyzed. The mean patient age was 59.3 ± 15.5 years, and 146,035 (54.9%) were women; 49.9% of orders were for CT, 38.8% for MR, 5.9% for nuclear medicine, and 5.4% for PET. After deployment, scored orders increased to 52% from 30% (P <.001). Orders with structured indications increased to 67.3% from 34.6% (P <.001). On multivariate analysis, orders were more likely to be scored after tool deployment (odds ratio [OR], 2.7, 95% CI, 2.63-2.78; P <.001). Compared with physicians, orders placed by nonphysician providers were less likely to be scored (OR, 0.80; 95% CI, 0.78-0.83; P <.001). MR (OR, 0.84; 95% CI, 0.82-0.87) and PET (OR, 0.12; 95% CI, 0.10-0.13) were less likely to be scored than CT (; P <.001). After AI tool deployment, 72,083 orders (47.8%) remained unscored, 45,186 (62.7%) with free-text-only indications. Embedding AI assistance within imaging clinical decision support was associated with increased structured indication orders and independently predicted a higher likelihood of scored orders. However, 48% of orders remained unscored, driven by both provider behavior and infrastructure-related barriers. [Display omitted] [ABSTRACT FROM AUTHOR]

Despite technological advances, challenges exist in US dental care, including variations in quality of care, access and untreated dental needs. The implementation of learning health systems (LHSs) in dentistry can help to address these challenges. LHSs use robust informatics infrastructure including data and technology to continuously measure and improve the quality and safety of care and can help to reduce costs and improve patient outcomes. The use of EHRs and standardized diagnostic terminologies are highlighted, as they allow for the storage and sharing of patient data, providing a comprehensive view of a patient's medical and dental history, and can be used to identify patterns and trends to improve the delivery of care. The BigMouth Dental Data Repository is an example of an informatic platform that aggregates patient data from multiple institutions and is being used to for scientific inquiry to improve oral health. [ABSTRACT FROM AUTHOR]

Copyright of REMAH Journal is the property of Research & Development of Human Recourses Center (REMAH) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background Patient-generated health data (PGHD) are data collected through technologies such as mobile devices and health apps. The integration of PGHD into health care workflows can support the care of chronic conditions such as multiple sclerosis (MS). Patients are often willing to share data with health care professionals (HCPs) in their care team; however, the benefits of PGHD can be limited if HCPs do not find it useful, leading patients to discontinue data tracking and sharing eventually. Therefore, understanding the usefulness of mobile health (mHealth) solutions, which provide PGHD and serve as enablers of the HCPs' involvement in participatory care, could motivate them to continue using these technologies. Objective The objective of this study is to explore the perceived utility of different types of PGHD from mHealth solutions which could serve as tools for HCPs to support participatory care in MS. Method A mixed-methods approach was used, combining qualitative research and participatory design. This study includes three sequential phases: data collection, assessment of PGHD utility, and design of data visualizations. In the first phase, 16 HCPs were interviewed. The second and third phases were carried out through participatory workshops, where PGHD types were conceptualized in terms of utility. Results The study found that HCPs are optimistic about PGHD in MS care. The most useful types of PGHD for HCPs in MS care are patients' habits, lifestyles, and fatigue-inducing activities. Although these subjective data seem more useful for HCPs, it is more challenging to visualize them in a useful and actionable way. Conclusion HCPs are optimistic about mHealth and PGHD as tools to further understand their patients' needs and support care in MS. HCPs from different disciplines have different perceptions of what types of PGHD are useful; however, subjective types of PGHD seem potentially more useful for MS care. [ABSTRACT FROM AUTHOR]

This article elucidates the technocratic utopia envisioned by Academician Axel Berg, detailing his perspective on the future and the strategies he believed would bring it to fruition. Specific initiatives undertaken by Berg are highlighted, notably the establishment of the Scientific Council "Cybernetics"—a nexus for the advancement of cybernetics in the former Soviet Union and the Russian Federation—and his endeavors in digital education. Two distinct articles within this compilation further consider these domains of Berg's work and of those who continued his legacy. [ABSTRACT FROM AUTHOR]

Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of the College Of Basic Education is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Kafkas University, Journal of Economics & Administrative Sciences Faculty / Kafkas Üniversitesi Iktisadi ve Idari Bilimler Fakültesi Dergisi is the property of University of Kafkas, Faculty of Economics & Administrative Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

BACKGROUND: Cirrhosis, or scarring of the liver, is a debilitating condition that affects millions of US adults. Early identification, linkage to care, and retention of care are critical for preventing severe complications and death from cirrhosis. OBJECTIVE: The purpose of this study is to conduct a preimplementation formative evaluation to identify factors that could impact implementation of the Population-Based Cirrhosis Identification and Management System (P-CIMS) in clinics serving patients with cirrhosis. P-CIMS is a web-based informatics tool designed to facilitate patient outreach and cirrhosis care management. METHODS: Semistructured interviews were conducted between January and May 2016 with frontline providers in liver disease and primary care clinics at 3 Veterans Health Administration medical centers. A total of 10 providers were interviewed, including 8 physicians and midlevel providers from liver-related specialty clinics and 2 primary care providers who managed patients with cirrhosis. The Consolidated Framework for Implementation Research guided the development of the interview guides. Inductive consensus coding and content analysis were used to analyze transcribed interviews and abstracted coded passages, elucidated themes, and insights. RESULTS: The following themes and subthemes emerged from the analyses: outer setting: needs and resources for patients with cirrhosis; inner setting: readiness for implementation (subthemes: lack of resources, lack of leadership support), and implementation climate (subtheme: competing priorities); characteristics of individuals: role within clinic; knowledge and beliefs about P-CIMS (subtheme: perceived and realized benefits; useful features; suggestions for improvement); and perceptions of current practices in managing cirrhosis cases (subthemes: preimplementation process for identifying and linking patients to cirrhosis care; structural and social barriers to follow-up). Overall, P-CIMS was viewed as a powerful tool for improving linkage and retention, but its integration in the clinical workflow required leadership support, time, and staffing. Providers also cited the need for more intuitive interface elements to enhance usability. CONCLUSIONS: P-CIMS shows promise as a powerful tool for identifying, linking, and retaining care in patients living with cirrhosis. The current evaluation identified several improvements and advantages of P-CIMS over current care processes and provides lessons for others implementing similar population-based identification and management tools in populations with chronic disease.

Glycoproteomics is a powerful yet analytically challenging research tool. Software packages aiding the interpretation of complex glycopeptide tandem mass spectra have appeared, but their relative performance remains untested. Conducted through the HUPO Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates solutions for system-wide glycopeptide analysis. The same mass spectrometrybased glycoproteomics datasets from human serum were shared with participants and the relative team performance for N- and O-glycopeptide data analysis was comprehensively established by orthogonal performance tests. Although the results were variable, several high-performance glycoproteomics informatics strategies were identified. Deep analysis of the data revealed key performance-associated search parameters and led to recommendations for improved 'high-coverage' and 'high-accuracy' glycoproteomics search solutions. This study concludes that diverse software packages for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies and specifies key variables that will guide future software developments and assist informatics decision-making in glycoproteomics.

The COVID-19 pandemic has once again highlighted the ubiquity and persistence of health inequities along with our inability to respond to them in a timely and effective manner. There is an opportunity to address the limitations of our current approaches through new models of informatics-enabled research and clinical practice that shift the norm from small- to large-scale patient engagement. We propose augmenting our approach to address health inequities through informatics-enabled citizen science, challenging the types of questions being asked, prioritized, and acted upon. We envision this democratization of informatics that builds upon the inclusive tradition of community-based participatory research (CBPR) as a logical and transformative step toward improving individual, community, and population health in a way that deeply reflects the needs of historically marginalized populations.

ObjectiveTo evaluate antimicrobial stewards' experiences of using a dashboard display integrating local and national antibiotic use data implemented in the U.S. Department of Veterans Affairs (VA). This paper reports early formative evaluation.DesignQualitative interviewing.SettingEight VA hospitals participated with established antimicrobial stewardship (AS) programs participated in the pilot.ParticipantsSix infectious disease physicians and eight clinical pharmacists agreed to be interviewed (n = 14).MethodsA 3-part qualitative interview script was used involving a description of local stewardship activities, a Critical Incident description of dashboard use, and general questions regarding attitudes towards the tool. An inductive open coding approach was used for analysis.ResultsWe found 4 themes showing the complexities of using stewardship tools: (1) Data validity is socially negotiated; (2) Performance feedback motivates and persuades social goals when situated in an empirical distribution; (3) Shared problem awareness is aided by authoritative data; and (4) The AS dashboard encourages connections with local quality improvement culture.ConclusionsSocial dimensions of AS tool use emerged as distinct from, and equally important as decision support provided by the dashboard. Successful stewardship tools should be designed to support both the social and cognitive needs of users.

ObjectiveTo describe the development of the Pediatric Epilepsy Outcome-Informatics Project (PEOIP) at Alberta Children's Hospital (ACH), which was created to provide standardized, point-of-care data entry; near-time data analysis; and availability of outcome dashboards as a baseline on which to pursue quality improvement.MethodsStakeholders involved in the PEOIP met weekly to determine the most important outcomes for patients diagnosed with epilepsy, create a standardized electronic note with defined fields (patient demographics, seizure and syndrome type and frequency and specific outcomes- seizure type and frequency, adverse effects, emergency department visits, hospitalization, and care pathways for clinical decision support. These were embedded in the electronic health record from which the fields were extracted into a data display platform that provided patient- and population-level dashboards updated every 36 hours. Provider satisfaction and family experience surveys were performed to assess the impact of the standardized electronic note.ResultsIn the last 5 years, 3,245 unique patients involving 13, 831 encounters had prospective, longitudinal, standardized epilepsy data accrued via point-of-care data entry into an electronic note as part of routine clinical care. A provider satisfaction survey of the small number of users involved indicated that the vast majority believed that the note makes documentation more efficient. A family experience survey indicated that being provided with the note was considered "valuable" or "really valuable" by 86% of respondents and facilitated communication with family members, school, and advocacy organizations.SignificanceThe PEOIP serves as a proof of principle that information obtained as part of routine clinical care can be collected in a prospective, standardized, efficient manner and be used to construct filterable process/outcome dashboards, updated in near time (36 hours). This information will provide the necessary baseline data on which multiple of QI projects to improve meaningful outcomes for children with epilepsy will be based.

Marginalized populations often experience health disparities due to the significant obstacles to care associated with social, economic, and environmental inequities. When compared with advantaged social groups, these populations frequently experience increased risks, poorer health outcomes, and reduced quality of life (QoL). This research examines the clinical and demographic characteristics—age, gender, and race—related to patients with varying stages of type 2 diabetes mellitus (T2DM), comparing the utilization of telemedicine (TM) with traditional healthcare face-to-face (F2F) appointments in an urban medically underserved population area (UMUPA). A logistic regression model, was used to analyze retrospective electronic patient health records (EHRs) from 1 January 2019 to 30 June 2021 of 265 patients with T2DM who had 3357 healthcare appointments. The overall percentage of healthcare provider appointments using TM was 46.7%, in comparison with 53.3% traditional F2F visits. Compared to patients with prediabetes, those with uncontrolled diabetes were more likely to utilize the TM mode of care rather than the traditional F2F mode (adjusted odds ratio (AoR), 1.33; confidence interval (CI), 1.07 to 1.64) after controlling for the other covariates in the model. Compared to patients in the age group 20–49 years, those in the age groups 50–64 years and ≥65 years had significantly lower odds (AoR, 0.78; CI, 0.65 to 0.94 and AoR, 0.71; CI, 0.58 to 0.88, respectively) of utilization of TM than the traditional F2F mode of care. White patients had significantly higher odds of using telemedicine rather than the traditional F2F mode (AoR, 1.25; CI, 1.07 to 1.47) when compared to the Black patients. Gender differences did not exist in the care utilization mode. As healthcare and public health continue to strive for health equity by eliminating health disparities within marginalized populations, it is essential that the mode of care for patients, such as those with T2DM, must evolve and adapt to the needs and resources of the patients. Multisectoral partners have the opportunity to employ a systems thinking approach to improve the technological elements related to the global health disparities crisis. An essential goal is to to create a user-friendly interface that prioritizes easy navigation, affordability, and accessiblity for populations in medically underserved regions to improve overall population health outcomes.

Abstract Digital pathology (DP) adoption in Latin America has expanded slower than in developed regions, probably due to many barriers not seen in the latter areas. This article aims to present the current scenario in the region, highlighting barriers and possible solutions to encourage its adoption in Latin American countries. Methods An expert panel of 9 Latin American medical pathologists and 1 information technology specialist participated in an online modified Delphi panel, utilizing a third-party platform (iAdvise, Within3, USA). Thirteen pre-prepared questions were answered interactively. Results Experts' observations confirm the paucity of labs in the region that utilize digital pathology technology. The panel ranked obtaining second opinions and presenting images remotely as the main benefit of a digital pathology system, although many others were cited as well. Cost of implantation was the main barrier mentioned by the experts. Payers' and decision makers' lack of awareness of benefits ranked second as a barrier to DP implementation. Internet infrastructure was also mentioned as a concerning issue in the region. Besides diagnostic pathology services, proposed revenue incomes included commercialization of digital services to other institutions, loan agreements of equipment and software, and organizing courses for pathologists or residents. The need for alternative reimbursement methods for diagnostic services was also mentioned. A regional network of collaborating institutions was also suggested as a viable solution to reach distant areas and laboratories lacking the technology. Conclusions The benefits of DP are clear to the expert panel, but cost and lack of awareness of its benefit may be hampering its widespread adoption in Latin America.

This study aims to produce learning modules for informatics learning modules for the 10th grade that are appropriate to the Independent Curriculum and make it easier for teachers to present teaching material and make it easier for students to learn. The model which was used in this development was the Dick and Carey development model. The results of this development research are in the form of a learning module for informatics, which is designed systematically, operationally, in a directed manner and completed by some guides for teachers on how to use the language that the speakers easily understand. In the development process to obtain products that are appropriate with the objectives, validation is carried out by material experts, design experts, colleagues, and student responses. The results of validation by material experts obtained a total score of 161 percentage 87% worthy category, design experts obtained a total score of 138 with a percentage of 89% worthy category, while colleagues obtained a total score of 63 percentage 90% very worthy in the category.The test was carried out three times, the first on the individual test obtained an average total score of 34.33 percentage 86% worthy category, the second small group test obtained an average total score of 68 percent 91% very worthy in the category, and the three large group tests obtained average score 69.53 percentage 93% very decent category.Thus, when the product is developed it was concluded that the learning module was very worthy to use in learning Informatics subjects.

Mobile software applications (apps) have transformed how individuals oversee and maintain their own health. One way that girls can monitor their menstrual cycles is through the increasingly widespread use of mobile menstrual tracking apps. This study aimed to examine menstrual symptom tracking for adolescents in English and Chinese apps, exploring menstrual literacy, cross-cultural differences, and framing, or presentation, of symptoms. The mixed-methods content analysis involved 15 popular free menstrual tracking apps in English (n = 8) and Chinese (n = 7), sampled from December 2022 to January 2023. A quantitative analysis of qualitative data was conducted through manual coding of content and automatically analyzing sentiment, or emotional tone, using a computational approach. We found that (1) menstrual literacy on symptom management or treatment was generally insufficient, (2) there were more available emotional than physical symptoms in English than Chinese apps, and (3) symptoms were framed more negatively than positively somewhat more in Chinese than English apps. Our findings emphasize the urgency to provide better evidence-informed communication about symptoms, either presented more positively or neutrally, in menstrual tracking apps for adolescent users. Since adolescence is a critical developmental stage that requires ample support, we recommend that digital menstrual trackers be crucially improved and future research should investigate how they can uniquely shape attitudes and experiences, and subsequent sexual and reproductive health empowerment and bodily autonomy.