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Background: The radiotherapy process relies on several metrics in determining a notion of "distance" from one three‐dimensional region‐of‐interest (ROI) to another. The majority are symmetric (or commutative) and do not contain information pertaining to directionality. Growth versus regression, for example, is not inherently distinguished by these metrics. Purpose: The purpose of this work was to formalize a unidirectional distance metric, motivated by radiotherapy margin concepts, which we term the migration distance. Informally, the migration distance from ROI X$X$ to Y$Y$ is the minimum isotropic expansion of X$X$ such that Y$Y$ is completely encompassed by the expansion. If Y$Y$ is contained within X$X$, the migration distance is negative with magnitude equal to the maximum isotropic contraction of X$X$ such that Y$Y$ remains contained within contraction. The metric is demonstrated by quantifying glioblastoma interfraction target changes. Methods: An explicit mathematical formulation of the migration distance is presented and contrasted with the related Hausdorff distance. The results are demonstrated for the gross tumor volume (GTV) dynamics of a glioblastoma cohort consisting of 111 patients that underwent standard chemoradiotherapy with offline MR imaging at planning, fraction 10, fraction 20, and 1‐month post radiotherapy. Results: The mean ± SD of the GTV migration distance relative to planning was 5.9 ± 3.9 mm at fraction 10, 6.2 ± 4.4 mm at fraction 20, and 7.9 ± 7.1 mm at 1‐month post radiotherapy. The maximum GTV migration distance across all patients at the same timepoints was 20.4, 20.7, and 45.5 mm, respectively. Conclusions: We have proposed and demonstrated a unidirectional distance metric. The migration distance may have applications in the quantification of anatomical changes, planning target volume designs, and dosimetric radiotherapy plan assessment. [ABSTRACT FROM AUTHOR]

Asthma is the most common chronic disease of childhood, and has several social, environmental, and demographic factors potentially influential to its disease burden. This study sought to determine the influence of these factors on hospital admissions and readmissions for pediatric asthma. This was a retrospective cohort study using data from the Indiana Network for Patient Care, a state-wide health information exchange in the United States. Study participants were children 2-18 years old admitted to the hospital with a respiratory diagnostic code between 2010 and 2021. Clinical variables were obtained from electronic health record data, and social and environmental determinants of health data were obtained from the Indiana Social Assets and Vulnerabilities Indicators using geocoding systems. Negative binomial models were used to examine community level social and environmental risk factors modifying the relationship between patient characteristics and the risk of asthma-related hospitalizations and 30-day readmissions. The study sample included 25,063 patients with an average follow-up of 9 (SD = 5) years. Of these, there were 17,816 asthma-related admissions. There were a total of 1,037 asthma-related 30-day readmissions, with an incidence rate of readmissions relative to total visits of 0.028 per person-year. A high social vulnerability index (SVI) was associated with an increased rate of hospital admissions (Proportion attributable ratio: 1.09, 95%CI (1.03,1.15), p < 0.05). No environmental determinants of health were significantly associated with hospitalization rate. High SVI was significantly associated with increased risk of total hospital admissions for pediatric asthma. [ABSTRACT FROM AUTHOR]

Background Study Design and Methods Results Discussion With the widespread adoption of Blood Establishment Computer Systems and other Blood Collection and Transfusion Service (BCTS) clinical information systems (CIS), electronic blood donor, product, and patient data are now routinely required for clinical, regulatory, operational, and quality needs. That data are often not readily accessible for such secondary use within CIS databases, particularly for applications with significant data availability requirements such as machine learning and artificial intelligence. Data replication provides one avenue by which CIS data can be made more readily available.Members of the AABB's Information Systems Committee along with institutional information technology colleagues provided a multi‐institutional viewpoint on data replication through the lens of BCTS specific use cases. Case studies of informatics offerings leveraging such technologies were also elicited.Six distinct use cases describe the potential role of data replication including the creation of data warehouses for frontline laboratory staff. Specific BCTS examples for each use case are presented to highlight the value of data replication, including visualization of critical inventory (O red blood cells, HLA‐compatible platelets) and utilization analytics for patient blood management. Two case studies describe the approach to implement such technologies to (1) optimize staffing via laboratory workload reporting and (2) improve access to blood via antigen‐negative blood product location services.Data replication and warehousing can empower BCTS analytic offerings not otherwise natively available through one's CIS to improve patient care and laboratory operations. [ABSTRACT FROM AUTHOR]

The overarching goal of the third scientific oral health symposium was to introduce the concept of a learning health system to the dental community and to identify and discuss cutting-edge research and strategies using data for improving the quality of dental care and patient safety. Conference participants included clinically active dentists, dental researchers, quality improvement experts, informaticians, insurers, EHR vendors/developers, and members of dental professional organizations and dental service organizations. This report summarizes the main outputs of the third annual OpenWide conference held in Houston, Texas, on October 12, 2022, as an affiliated meeting of the American Dental Association (ADA) 2022 annual conference. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic highlighted the necessity of equipping health professionals with knowledge and skills to effectively use digital technology for healthcare delivery. However, questions persist about the best approach to effectively educate future health professionals for this. A workshop at the 15th Nursing Informatics International Congress explored this issue. To report findings from an international participatory workshop exploring pre-registration informatics implementation experiences. A virtual workshop was held using whole and small group interactive methods aiming to 1) showcase international examples of incorporating health informatics into pre-registration education; 2) highlight essential elements and considerations for integrating health informatics into curricula; 3) identify integration models of health informatics; 4) identify core learning objectives, resources, and faculty capabilities for teaching informatics; and 5) propose curriculum evaluation strategies. The facilitators' recorded data and written notes were content analysed. Fourteen participants represented seven countries and a range of educational experiences. Four themes emerged: 1) Design: scaffolding digital health and technology capabilities; 2) Development: interprofessional experience of and engagement with digital health technology capabilities; 3) implementation strategies; and 4) Evaluation: multifaceted, multi-stakeholder evaluation of curricula. These themes were used to propose an implementation framework. Workshop findings emphasise global challenges in integrating health informatics into curricula. While course development approaches may appear linear, the learner-centred implementation framework based on workshop findings, advocates for a more cyclical approach. Iterative evaluation involving stakeholders, such as health services, will ensure that health professional education is progressive and innovative. The proposed implementation framework serves as a roadmap for successful health informatics implementation into health professional curricula. Prioritising engagement with health services and digital health industry is essential to ensure the relevance of implemented informatics curricula for the future workforce, acknowledging the variability in placement experiences and their influence on informatics exposure, experience, and learning. [ABSTRACT FROM AUTHOR]

Objectives To measure rates of potentially inappropriate pathology testing in the hospital setting. Methods Retrospective cross-sectional study in hospital setting from July 2021 to December 2021. We examined 3 potentially inappropriate uses: overordering, selection errors, and unnecessary repeat testing. Overordering included vitamin D and lipids (rarely required in acute hospital care). Selection error was the ratio of iron studies to standalone ferritin requests. Unnecessary repeats included any repeat vitamin D, lipids, iron, or ferritin in an episode of care or C-reactive protein (CRP) repeated within 3 days and N-terminal pro–brain natriuretic peptide (NT-proBNP) within 7 days and repeated previously abnormal CRP and NT-proBNP tests. Costs of inappropriate tests were estimated using the Australian Medicare Benefits Schedules. Results Among 55,904 test requests, 15% (n = 8120) were potentially inappropriate. Vitamin D was frequently ordered (n = 4498), as were lipids (n = 2872). Ratio of iron studies to standalone ferritin was 36. Of 19,233 repeat CRPs, 36% (n = 6947) were within 3 days and 62% (n = 179) of repeat NT-proBNPs were within 7 days of the first test. For initially abnormal tests, 89% of CRPs and 97% of NT-proBNPs remained abnormal. Inappropriate test costs accounted for 12% to 30% of costs. Conclusions Frequent potential inappropriate use and selection of pathology tests was observed in South Australian hospitals. [ABSTRACT FROM AUTHOR]

Purpose: The conclusion section of a radiology report is crucial for summarizing the primary radiological findings in natural language and essential for communicating results to clinicians. However, creating these summaries is time-consuming, repetitive, and prone to variability and errors among different radiologists. To address these issues, we evaluated a fine-tuned Text-To-Text Transfer Transformer (T5) model for abstractive summarization to automatically generate conclusions for neuroradiology MRI reports in a low-resource language. Methods: We retrospectively applied our method to a dataset of 232,425 neuroradiology MRI reports in Spanish. We compared various pre-trained T5 models, including multilingual T5 and those newly adapted for Spanish. For precise evaluation, we employed BLEU, METEOR, ROUGE-L, CIDEr, and cosine similarity metrics alongside expert radiologist assessments. Results: The findings are promising, with the models specifically fine-tuned for neuroradiology MRI achieving scores of 0.46, 0.28, 0.52, 2.45, and 0.87 in the BLEU-1, METEOR, ROUGE-L, CIDEr, and cosine similarity metrics, respectively. In the radiological experts' evaluation, they found that in 75% of the cases evaluated, the conclusions generated by the system were as good as or even better than the manually generated conclusions. Conclusion: The methods demonstrate the potential and effectiveness of customizing state-of-the-art pre-trained models for neuroradiology, yielding automatic MRI report conclusions that nearly match expert quality. Furthermore, these results underscore the importance of designing and pre-training a dedicated language model for radiology report summarization. [ABSTRACT FROM AUTHOR]

The article offers information on the implementation of iMDsoft's Metavision as Boston Children's Hospital's anesthesia information management system (AIMS) software in 2012. It discusses the development of a "low-flow" interface for the system by 2015 to enhance teaching and patient safety during the delivery of low flow anesthesia.

Nonlinear curve fitting is an important process in laboratory medicine, particularly with the increased use of highly sensitive antibody-based assays. Although the process is often automated in commercially available software, it is important that clinical scientists and physicians recognize the limitations of the various approaches used and are able to select the most appropriate model. This article summarizes the key nonlinear functions and demonstrates their application to common laboratory data. Following this, a basic overview of the statistical comparison of models is presented and then a discussion of important algorithms used in nonlinear curve fitting. An accompanying Microsoft Excel workbook is available that can be used to explore the content of this article. [ABSTRACT FROM AUTHOR]

The article informs about cystic fibrosis (CF) and its impact on airway health, focusing on the role of CFTR mutations in causing abnormal ion transport and subsequent lung complications. Topic include the approval of elexacaftor/tezacaftor/ivacaftor (ETI), a CFTR modulator therapy, and its potential to improve lung function in patients with CF, highlighting a retrospective analysis to determine its effect on Pseudomonas aeruginosa (PA) acquisition and chronic infection rates.

Existing outpatient parenteral antibiotic therapy (OPAT) registries are resource intensive, and OPAT programs struggle to produce objective data to show the value of their work. We describe the building and validation of an automated OPAT registry within our electronic medical record and provide objective data on the value of the program. Variables and outcomes include age, sex, race, ethnicity, primary insurance payor, antibiotic names, infection syndromes treated, discharge disposition, 30-day all-cause readmission and death rates, complications, and an estimate of the hospital days saved. Records for 146 OPAT episodes were reviewed manually to validate the registry. Data were displayed in a dashboard within the electronic medical record. Over the 4-year time frame, our registry collected 3956 unique patients who completed 4710 episodes (approximately 1200 episodes per year). A total of 400 complications during OPAT were identified. All variables had an accuracy of >90% on validation. The OPAT program resulted in a reduction in hospital length of stay by 88 820 days, or roughly 22 000 days per year. We intend our registry to serve as a blueprint for similar OPAT programs with limited administrative resources. Wider application of our system would allow for easier aggregation and comparisons of OPAT practice and address the lack interinstitutional standardization of OPAT data and outcomes. [ABSTRACT FROM AUTHOR]

Archaeologists seek to improve our understanding of the past by studying, preserving, protecting, and sharing nonreplaceable archaeological resources. Archaeological collections hold information that can assist these aims as long as they are properly cared for, identified, and accessible. One of the most serious barriers is the lack of large-scale coordinated efforts to make archaeological collections findable and accessible. This article suggests that developing and implementing the use of a standardized set of attributes regarding collections provides solutions and strategies to find collections. These attributes can connect and standardize existing archaeological collections from a variety of sources (federal and state agencies, CRM firms, Indigenous and descendant communities, and academic departments), serving the profession in multiple ways. Most critically, the baseline data can be synthesized to inform and direct priorities for future fieldwork, thereby decreasing redundancy in archaeological collections and improving curation efforts nationwide. Such efforts would also provide a resource to students and researchers looking to understand and interpret the past at multiple scales by encouraging more collections-based research and less archaeological site destruction. Access for descendant communities will also be improved with information about their cultural heritage. This, in turn, encourages transparency and collaboration between those communities and archaeologists. [ABSTRACT FROM AUTHOR]

Identification of similar and dissimilar spectra is an important part of analyzing X‐ray photoelectron spectroscopy (XPS) images. Cluster analysis (CA) is a commonly used exploratory data analysis (EDA) method that groups similar spectra in a data set. CA can be performed in either an agglomerative fashion, for example, using Ward's method, which involves successively linking together/clustering the most similar spectra in a data set, or in a divisive fashion, for example, using the K‐means approach, which involves partitioning all the data into a specified number of clusters. In this note, we show the application of CA to an XPS image dataset. The use of Ward's method identified two major clusters in the image, where one of the clusters appeared as two subclusters. The K‐means image based on two clusters agrees well with previous analyses of the same image. The average spectra corresponding to clusters helped confirm the assignments made by the CA algorithms, as did a multivariate curve resolution (MCR) analysis of the interior region identified in our cluster analysis. "Elbow" plots can help determine the number of clusters to keep in K‐means clustering. The combination of the agglomerative and divisive forms of CA, where the first informs the second, can be effective in revealing the structures of XPS image datasets. The Procrustean bed is a metaphor for overfitting and underfitting in EDA. [ABSTRACT FROM AUTHOR]

BackgroundObjectiveMethodsResultsConclusionsDigital health technology is progressively transforming physiotherapy practice. Despite a maturing body of literature relating to physiotherapy digital health capability, research examining digital health physiotherapy competency standards is both lacking and lagging.Examine international professional practice competency standards for physiotherapists to identify themes common to digital health practice competency, published by international peak organizations governing physiotherapy practice.Systematic meta-synthesis of international peak organization physiotherapy practice competency standards. The study was undertaken over nine stages. Competency statements related to digital health were extracted, and further coded into resultant themes.Eleven documents were analyzed. Fifty-two statements explicitly referenced digital health competency. Identified themes were as follows: 1) digital health data governance; 2) digital health data translation; and 3) digital health technologies. Where digital health-related competency statements do exist, they are skewed toward health information management activities.Digital health practice is currently under-represented in competency standards for physiotherapists. Workforce advancement in light of the burgeoning impact of digital health will prompt further updates to professional competency standards set by our peak organizations. This will have a flow on effect, whereby education providers (e.g. universities and other professional development providers) should consider curriculum and training that prepares individuals for digitally enabled practice. [ABSTRACT FROM AUTHOR]

The article presents the state of the art and methodology of the doctoral research project "Framework for modeling and simulation of maritime cyberdefense - MARCIM". The state of the art defined the background of the research problem, the state of scientific activity, trends and challenges related to MARCIM: cyberdefense, modeling and simulation in cyber security and cyberdefense; and maritime cybersecurity and cyberdefense. The methodology was established with a focus on modeling complex systems, by phases and application actors. The article mainly concludes that maritime cyberdefense at a strategic level behaves like a complex system, with dynamics, processes and elements that cannot be clearly identified, which require modeling and simulation, with a metaheuristic approach, to study the set of actions and interactions between its entities. [ABSTRACT FROM AUTHOR]

This article deals with situations related to solving arithmetic math problems. It is found that there is a lack of mathematical knowledge to adequately deal with standard arithmetic calculations in an electronic environment. The cases mentioned focus attention on the actuality of the relations mathematics-informatics-information technologies in education. The situations discussed in the article are related to solving mathematical problems in the process of training in informatics, information technologies and computer modeling that are solved in an analog environment. In the process of e-learning, these situations are challenges that can provoke additions to current levels in established taxonomies. Or to give view and direction to a new and up-to-date revision of existing ones models of known taxonomies in the field of education. [ABSTRACT FROM AUTHOR]

Background: Many educational disciplines, especially in health professions, are required by accrediting bodies to introduce or include health informatics (HI); however, faculty (academics) teaching this content may not be well prepared. Objective: The aim of this project was to explore how a doctoral physical therapy (DPT) program could more accurately represent compliance with HI accreditation requirements by identifying hidden instances of relevant content within the curriculum. Method: This exploratory, mixed methods, action research study utilised document review, questionnaires and interviews in the collection of quantitative and qualitative data to enable assessment of knowledge about HI, to determine if HI content was already incorporated in current courses, and, whether the content was accurately reflected in course student learning objectives (SLOs). Change in faculty understanding of HI as a result of this study was also assessed. Results: Of 16 DPT faculty, 13 participated in the pre-interview questionnaire; 8 (50%) representing 22/39 courses participated in the full study. Most were unfamiliar with HI and had unrecognised HI already incorporated in their courses leading to several SLO revisions and additions. Interview and post-interview questionnaire results documented significant increases in HI understanding among faculty. Conclusion: Physical therapy and HIM collaboration was successful in identifying HI content hiding in plain sight. Results revealed multiple instances of unrecognised HI content across the DPT curriculum. Revised and newly added SLOs, with others likely to follow due to this study, will assist faculty with future reaccreditation and in preparing graduates to more fully utilise HI in today's digital healthcare environments. [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]

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]

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]

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]

At a time when diverse forms of automated visual feedback systems on speech are introduced to the Human–Computer Interaction (HCI) community, our research investigates the possible design spaces and design implications to consider when creating them. We utilised a Wizard of Oz prototype that recognises fillers during speech and sends out real-time feedback in the form of a flickering screen and a post-report with graphic charts. We let 27 participants use this prototype and interviewed them about their general experience of using such systems. Based on thematic analysis, we propose eight design implications to consider when designing an automated visual feedback system on speech. Additionally, we discuss the possible future for automated visual feedback systems on speech where they collaborate with fields such as personal informatics (quantified self), self-determination theory (SDT) and motivation, and other socio-ethnic areas [ABSTRACT FROM AUTHOR]

Lack of service data for cardiac rehabilitation limits understanding of program delivery, benchmarking and quality improvement. This study aimed to describe current practices, management, utilisation and engagement with quality indicators in Australian programs. Cardiac rehabilitation programs (n=396) were identified from national directories and networks. Program coordinators were surveyed on service data capture, management systems and adoption of published national quality indicators. Text responses were coded and classified. Logistic regression determined independent associates of the use of data for quality improvement. A total of 319 (81%) coordinators completed the survey. Annual patient enrolments/programs were >200 (31.0%), 51−200 (46%) and ≤50 (23%). Most (79%) programs used an electronic system, alongside paper (63%) and/or another electronic system (19%), with 21% completely paper. While 84% knew of the national quality indicators, only 52% used them. Supplementary to patient care, data were used for reports to managers (57%) and funders (41%), to improve quality (56%), support funding (43%) and research (31%). Using data for quality improvement was more likely when enrolments where >200 (Odds ratio [OR] 3.83, 95% Confidence Interval [CI] 1.76−8.34) and less likely in Victoria (OR 0.24 95%, CI 0.08−0.77), New South Wales (OR 0.25 95%, CI 0.08−0.76) and Western Australia (OR 0.16 95%, CI 0.05−0.57). The collection of service data for cardiac rehabilitation patient data and its justification is diverse, limiting our capacity to benchmark and drive clinical practice. The findings strengthen the case for a national low-burden approach to data capture for quality care. [ABSTRACT FROM AUTHOR]

Aims: To identify different nursing informatics competence (NIC) profiles in nurses, examine the factors associated with profile memberships and examine the associations of the derived profiles with the nurses' perception of the usefulness of a health information system (HIS). Design: A cross‐sectional study. Methods: A sample of 3610 registered nurses responded to a nationwide survey in March 2020. A latent profile analysis was performed to identify NIC profiles based on three competence areas: nursing documentation, working in digital environment, and ethics and data protection. A multinomial logistic regression was carried out to examine the associations of demographic and background variables with the profile membership. Linear regression analyses were carried out to examine the association between the profile membership and perceived HIS usefulness. Results: Three NIC profiles were identified and labelled as low, moderate and high competence groups. A younger age, recent graduation year, sufficient orientation and high‐rated proficiency as an HIS user were associated with nurses belonging to a high or moderate competence group relative to a low competence group. Competence group membership was associated with perceived HIS usefulness. The high competence group consistently expressed the highest usefulness of the HIS and the low competence group the lowest. Conclusion: Tailored training and support should be provided for nurses with different levels of informatics competence, thereby facilitating their ability to respond to increasingly digitalized work. This could contribute to higher usefulness of the HIS in terms of supporting the nurses' work tasks and promoting the quality of care. Impact: This was the first study exploring latent profiles of informatics competence in nurses. Insights from this study are useful for nursing management to identify different competence profiles of their employees, provide support and training to meet their needs, and promote the successful use of an HIS. [ABSTRACT FROM AUTHOR]

Background: The U.S. Department of Veterans Affairs (VA) is undergoing an enterprise-wide transition from a homegrown electronic health record (EHR) system to a commercial off-the-shelf product. Because of the far-reaching effects of the EHR transformation through all aspects of the healthcare system, VA Health Services Research and Development identified a need to develop a research agenda that aligned with health system priorities so that work may inform evidence-based improvements in implementation processes and outcomes. Objective: The purpose of this paper is to report on the development of a research agenda designed to optimize the EHR transition processes and implementation outcomes in a large, national integrated delivery system. Design: We used a sequential mixed-methods approach (portfolio assessment, literature review) combined with multi-level stakeholder engagement approach that included research, informatics, and healthcare operations experts in EHR transitions in and outside the VA. Data from each stage were integrated iteratively to identify and prioritize key research areas within and across all stakeholder groups. Participants: VA informatics researchers, regional VA health system leaders, national VA program office leaders, and external informatics experts with EHR transition experience. Key Results: Through three rounds of stakeholder engagement, priority research topics were identified that focused on operations, user experience, patient safety, clinical outcomes, value realization, and informatics innovations. Conclusions: The resulting EHR-focused research agenda was designed to guide development and conduct of rigorous research evidence aimed at providing actionable results to address the needs of operations partners, clinicians, clinical staff, patients, and other stakeholders. Continued investment in research and evaluation from both research and operations divisions of VA will be critical to executing the research agenda, ensuring its salience and value to the health system and its end users, and ultimately realizing the promise of this EHR transition. [ABSTRACT FROM AUTHOR]

Background: Healthcare organizations regularly manage external stressors that threaten patient care, but experiences handling concurrent stressors are not well characterized. Objective: To evaluate the experience of Veterans Affairs (VA) clinicians and staff navigating simultaneous organizational stressors—an electronic health record (EHR) transition and the COVID-19 pandemic—and identify potential strategies to optimize management of co-occurring stressors. Design: Qualitative case study describing employee experiences at VA's initial EHR transition site. Participants: Clinicians, nurses, allied health professionals, and local leaders at VA's initial EHR transition site. Approach: We collected longitudinal qualitative interview data between July 2020 and November 2021 once before and 2–4 times after the date on which the health system transitioned; this timing corresponded with local surges of COVID-19 cases. Interviewers conducted coding and analysis of interview transcripts. For this study, we focused on quotes related to COVID-19 and performed content analysis to describe recurring themes describing the simultaneous impact of COVID-19 and an EHR transition. Key Results: We identified five themes related to participants' experiences: (1) efforts to mitigate COVID-19 transmission led to insufficient access to EHR training and support, (2) clinical practice changes in response to the pandemic impacted EHR workflows in unexpected ways, (3) lack of clear communication and inconsistent enforcement of COVID-19 policies intensified pre-existing frustrations with the EHR, (4) managing concurrent organizational stressors increased work dissatisfaction and feelings of burnout, and (5) participants had limited bandwidth to manage competing demands that arose from concurrent organizational stressors. Conclusion: The expected challenges of an EHR transition were compounded by co-occurrence of the COVID-19 pandemic, which had negative impacts on clinician experience and patient care. During simultaneous organizational stressors, health care facilities should be prepared to address the complex interplay of two stressors on employee experience. [ABSTRACT FROM AUTHOR]

Limited research explores the effectiveness of educational interventions in meeting telehealth technology competencies. A combined didactic and simulation intervention was implemented with 66 prelicensure and 15 nurse practitioner students. Telehealth knowledge, confidence, and attitudes were evaluated using the Telemedicine Objective Structured Clinical Exam survey. Results were analyzed using descriptive and inferential strategies, and responses to an open-ended question were content analyzed. Survey scores significantly increased from pre- to post-intervention. Learners recognized the value of telehealth and the educational intervention. This effective and well-received intervention can be used by schools of nursing to facilitate student attainment of telehealth competencies. [ABSTRACT FROM AUTHOR]

Background: Accurate segmentation of stroke lesions on MRI images is very important for neurologists in the planning of post-stroke care. Segmentation helps clinicians to better diagnose and evaluation of any treatment risks. However, manual segmentation of brain lesions relies on the experience of neurologists and is also a very tedious and time-consuming process. So, in this study, we proposed a novel deep convolutional neural network (CNN-Res) that automatically performs the segmentation of ischemic stroke lesions from multimodal MRIs. Methods: CNN-Res used a U-shaped structure, so the network has encryption and decryption paths. The residual units are embedded in the encoder path. In this model, to reduce gradient descent, the residual units were used, and to extract more complex information in images, multimodal MRI data were applied. In the link between the encryption and decryption subnets, the bottleneck strategy was used, which reduced the number of parameters and training time compared to similar research. Results: CNN-Res was evaluated on two distinct datasets. First, it was examined on a dataset collected from the Neuroscience Center of Tabriz University of Medical Sciences, where the average Dice coefficient was equal to 85.43%. Then, to compare the efficiency and performance of the model with other similar works, CNN-Res was evaluated on the popular SPES 2015 competition dataset where the average Dice coefficient was 79.23%. Conclusion: This study presented a new and accurate method for the segmentation of MRI medical images using a deep convolutional neural network called CNN-Res, which directly predicts segment maps from raw input pixels. [ABSTRACT FROM AUTHOR]

Aim: We explored the importance of digital technologies to health responses during the COVID‐19 pandemic. The benefits, challenges and barriers to developing digital capabilities are identified, and strategies to establish enduring digital proficiency among nurses and healthcare colleagues gained during the pandemic are canvassed. Background: Since the mid‐20th century, technology uptake by health practitioners has prioritised digital information and communication technology. The COVID‐19 pandemic accelerated the need to adapt digital communication to dangerous clinical workplaces. Organisational policies enabled digital capabilities to replace in‐person processes while preserving regulatory compliance, safety and security of patient information and staff deployment. Sources of Evidence: All evidence was accessed from publicly available sources. Discussion: The COVID‐19 pandemic was a catalyst for implementing Technology Enhanced Care Services. Health practitioners need appropriate digital capabilities for their roles and scope of practice. Nursing proficiency includes technological skills. Combining the Jisc Digital Capability Framework and the Health and Care Digital Capabilities Framework helps nurses achieve the technical expertise needed for clinical proficiency in contemporary healthcare environments. Conclusion: Healthcare workforce digital capability requires policies that resource digital technologies and individual user skills in dangerous COVID‐19 workplaces. All involved must be abreast of technological changes and monitor technology effectiveness in innovation in patient care, professional education and evidence‐based infectious disease management of healthcare systems. Implications for nursing practice and policy: Nurses and other practitioners in COVID‐19–compromised settings must be able to use the embedded digital technologies in patient care, clinical management and education. Policies securing resources for nurses to learn to use digital technologies will ensure that digital systems are regularly upgraded and that nurses develop proficiency in using technology in their clinical practice. Work and workplace redesign needs compatible computer systems and software to support nursing innovation and digital proficiency. [ABSTRACT FROM AUTHOR]

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 FROM AUTHOR]

Background: Literature has shown the integration of electronic alerts into patient care has the potential to improve clinicians' workflow by saving time, increasing efficiency, and improving patient safety. However, despite these possible benefits of alerts, studies have shown that alerts are often overridden by clinicians. Objective: The purpose of this study was to optimize the acceptance rates of medication point-of-prescribing alerts within the electronic medical record (EMR) of an ambulatory care organization. Methods: The study design evaluated the actions taken by clinicians when they were presented with medication point-of-prescribing alerts. These alerts were created by the clinical pharmacy informatics team to help promote cost-effective and safe prescribing. Alerts determined to be high value alerts were optimized to increase clinicians' likelihood of accepting each alert's recommended alternative. The primary objective was to increase acceptance rates of high value alerts. The exploratory objective was to identify the estimated annualized cost-savings when high value alerts were accepted, and a lower cost alternative prescription resulted. Results: The acceptance rate of the optimized point-of-prescribing alerts increased to 8.7%, compared to a 3.2% acceptance in the pre-modification period (P <.001). The lower cost alternative prescriptions that resulted from the accepted alerts translated into an estimated annualized cost-savings of over 2 million dollars. Conclusion: The use of point-of-prescribing alerts with optimized information and specific cost comparisons in an ambulatory setting led to an increase in the acceptance rates of the alerts and more cost-conscious prescribing. [ABSTRACT FROM AUTHOR]

Objectives Peripheral blood smear (PBS) interpretation represents a cornerstone of pathology practice and resident training but has remained largely static for decades. Here, we describe a novel PBS interpretation support tool. Methods In a mixed-methods quality improvement study, a web-based clinical decision support (CDS) tool to assist pathologists in PBS interpretation, PROSER, was deployed in an academic hospital over a 2-month period in 2022. PROSER interfaced with the hospital system's electronic health record and data warehouse to obtain and display relevant demographic, laboratory, and medication information for patients with pending PBS consults. PROSER used these data along with morphologic findings entered by the pathologist to draft a PBS interpretation using rule-based logic. We evaluated users' perceptions of PROSER with a Likert-type survey. Results PROSER displayed 46 laboratory values with corresponding reference ranges and abnormal flags, allowed for entry of 14 microscopy findings, and computed 2 calculations based on laboratory values; it composed automated PBS reports using a library of 92 prewritten phrases. Overall, PROSER was well received by residents. Conclusions In this quality improvement study, we successfully deployed a web-based CDS tool for PBS interpretation. Future work is needed to quantitatively evaluate this intervention's effects on clinical outcomes and resident training. [ABSTRACT FROM AUTHOR]

Simple Summary: Prostate cancer (PCa) is one of the most common cancers and the second leading cause of cancer-related deaths in men in the United States. Accurate diagnosis, management, and posttherapy surveillance are critical for optimizing survival and patient quality of life. Sharing information among providers is a challenge due to the use of different health information systems or data capture workflows which can lead to ambiguity and misinterpretation of shared information. The aim of our study was to formulate an expert panel-based consensus on PCa-specific key data elements. Using the Delphi method, PCa experts developed a two-tiered thirty-item list of treatment-related toxicities for standardized clinical data capture. Additionally, four multi-domain symptom questionnaires were ranked, and definitions on disease control metrics were formalized. These findings have been used to develop a comprehensive operational ontology for PCa care that can facilitate knowledge sharing and scalable machine learning approaches. Background: Clinical data collection related to prostate cancer (PCa) care is often unstructured or heterogeneous among providers, resulting in a high risk for ambiguity in its meaning when sharing or analyzing data. Ontologies, which are shareable formal (i.e., computable) representations of knowledge, can address these challenges by enabling machine-readable semantic interoperability. The purpose of this study was to identify PCa-specific key data elements (KDEs) for standardization in clinic and research. Methods: A modified Delphi method using iterative online surveys was performed to report a consensus agreement on KDEs by a multidisciplinary panel of 39 PCa specialists. Data elements were divided into three themes in PCa and included (1) treatment-related toxicities (TRT), (2) patient-reported outcome measures (PROM), and (3) disease control metrics (DCM). Results: The panel reached consensus on a thirty-item, two-tiered list of KDEs focusing mainly on urinary and rectal symptoms. The Expanded Prostate Cancer Index Composite (EPIC-26) questionnaire was considered most robust for PROM multi-domain monitoring, and granular KDEs were defined for DCM. Conclusions: This expert consensus on PCa-specific KDEs has served as a foundation for a professional society-endorsed, publicly available operational ontology developed by the American Association of Physicists in Medicine (AAPM) Big Data Sub Committee (BDSC). [ABSTRACT FROM AUTHOR]

Australia is no different to any other country in that information technology (IT) and the speed of its advancement has a huge impact on health care and therefore on health libraries. Australian health librarians are valuable members of health care teams and strive to integrate services and resources across hospitals. This article looks at the role Australian health libraries play in the broader health information landscape and the importance of information governance and health informatics as a tenet of the work undertaken by libraries. Of particular focus in this is the Health Libraries Australia/Telstra Health Digital Health Innovation Award, offered annually, to help focus on particular technological challenges. Three cases studies are explored demonstrating impact on the systematic review process, inter‐library loan system automation and a room booking service. Also discussed are the ongoing professional development opportunities, which help upskill the Australian health library workforce. Australian health libraries also face many challenges with piecemeal IT systems across the nation, resulting in lost opportunities. Also, many Australian health services do not have a qualified librarian on staff, which undermines information governance. However, resiliency shines through with strong professional health library networks working to challenge the status quo in an effort to improve the application of health informatics. [ABSTRACT FROM AUTHOR]

OBJECTIVES: Identifying modifiable risk factors associated with central line-associated bloodstream infections (CLABSIs) may lead to modifications to central line (CL) management. We hypothesize that the number of CL accesses per day is associated with an increased risk for CLABSI and that a significant fraction of CL access may be substituted with non-CL routes. DESIGN: We conducted a retrospective cohort study of patients with at least one CL device day from January 1, 2015, to December 31, 2019. A multivariate mixed-effects logistic regression model was used to estimate the association between the number of CL accesses in a given CL device day and prevalence of CLABSI within the following 3 days. SETTING: A 395-bed pediatric academic medical center. PATIENTS: Patients with at least one CL device day from January 1, 2015, to December 31, 2019. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: There were 138,411 eligible CL device days across 6,543 patients, with 639 device days within 3 days of a CLABSI (a total of 217 CLABSIs). The number of per-day CL accesses was independently associated with risk of CLABSI in the next 3 days (adjusted odds ratio, 1.007; 95% CI, 1.003–1.012; p = 0.002). Of medications administered through CLs, 88% were candidates for delivery through a peripheral line. On average, these accesses contributed a 6.3% increase in daily risk for CLABSI. CONCLUSIONS: The number of daily CL accesses is independently associated with risk of CLABSI in the next 3 days. In the pediatric population examined, most medications delivered through CLs could be safely administered peripherally. Efforts to reduce CL access may be an important strategy to include in contemporary CLABSI-prevention bundles. [ABSTRACT FROM AUTHOR]

Background: The Nutrition Dashboard is an interactive nutrition technology platform that displays food provision and intake data used to categorise the nutrition risk of hospitalised individuals. The present study aimed to investigate the Nutrition Dashboard's ability to identify malnutrition compared with a validated malnutrition screening tool (MST). Methods: A retrospective observational study at a 99‐bed hospital was conducted using medical record and food intake data presented via the Nutrition Dashboard. Inter‐Rater Reliability of food intake estimation between hospital catering staff and a dietitian reported good agreement across 912 food items (κ = 0.69, 95% confidence interval = 0.65–0.72, p < 0.001). Default nutritional adequacy thresholds of 4500 kJ and 50 g protein were applied for Nutrition Dashboard categorisation of supply and intake. Generalised estimating equation regression models explored the association between the Nutrition Dashboard risk categories and the MST, with and without controlling for patient demographic characteristics. Results: Analyses from 216 individuals (1783 hospital‐stay days) found that those in the highest risk Nutrition Dashboard category were 1.93 times more likely to have a MST score indicating risk compared to the lowest Nutrition Dashboard category (unadjusted odds ratio = 1.93, 95% confidence interval = 1.17–3.19, p < 0.01). When patient weight was added to the model, lower weight became the only significant predictor of MST ≥ 2 (p < 0.01) Conclusions: The present study indicates a role for nutrition intake technology in malnutrition screening. Further adaptions that address the complexities of applying this technology could improve the use of the Nutrition Dashboard to support identification of malnutrition. Key points: 1.Timely, accurate identification of malnutrition is essential in the acute care setting, but under‐identification of malnutrition remains common despite best practice guidelines for malnutrition screening.2.The present study identified that an interactive platform that displays food intake and nutrient data for hospitalised patients has potential to improve the identification of malnutrition when used in parallel with existing malnutrition screening.3.The Nutrition Dashboard may improve the management of malnutrition by providing dietitians with malnutrition risk information directly rather than completely relying on the multi‐disciplinary team to initiate screening and referrals. [ABSTRACT FROM AUTHOR]

As palliative care (PC) programs rapidly grow and expand across settings, the need to measure, improve, and standardize high-quality PC has also grown. The electronic health record (EHR) is a key component of these efforts as a central hub of care delivery and a repository of patient and system data. Deliberate efforts to leverage the EHR for PC quality improvement (QI) can help PC programs and health systems improve care for patients with serious illnesses. This article, written by clinicians with experience in QI, informatics, and clinical program development, provides practical tips and guidance on EHR strategies and tools for QI and quality measurement. [ABSTRACT FROM AUTHOR]

Background: The implementation of digital healthcare systems in hospitals globally and in Australia has led to the introduction of the informatics pharmacist as a career in the healthcare system. However, informatics pharmacists are not yet part of routine clinical services in Australia, so their perspective and roles are not well understood. Aim: To explore pharmacists' and other health professionals' perspectives of the roles of informatics pharmacists within interprofessional teams in Australian health care. Method: This study used semi‐structured interviews with experts in pharmacy and/or informatics. They were recruited using convenience sampling and snowballing. The interviews were audio‐recorded and transcribed and analysed using inductive thematic techniques to identify major themes. Ethical approval was received from the local institutional Human Research Ethics Committee (Approval No: 2020000069). Results: The process of inductive thematic analysis was used to analyse the interview transcriptions of 11 participants. Six themes were identified: (1) a promising future for the informatics pharmacists, (2) education, (3) specific skills, (4) scope of informatics role, (5) impacts, and (6) barriers. Participants described the career of informatics pharmacists as an emerging specialty in today's healthcare systems. The roles of informatics pharmacists in Australian health care are described together with the skills and knowledge required for these roles. Conclusion: A key role of informatics pharmacists is to facilitate the appropriate use of digital systems to prevent medication errors and improve patients' safety. While international experience has shown the potential scope for an informatics pharmacist, this research shows the use of informatics pharmacists in Australia is in its infancy. [ABSTRACT FROM AUTHOR]

Advanced artificial intelligence (AI) techniques have led to significant developments in optical character recognition (OCR) technologies. OCR applications, using AI techniques for transforming images of typed text, handwritten text, or other forms of text into machine-encoded text, provide a fair degree of accuracy for general text. However, even after decades of intensive research, creating OCR with human-like abilities has remained evasive. One of the challenges has been that OCR models trained on general text do not perform well on localized or personalized handwritten text due to differences in the writing style of alphabets and digits. This study aims to discuss the steps needed to create an adaptive framework for OCR models, with the intent of exploring a reasonable method to customize an OCR solution for a unique dataset of English language numerical digits were developed for this study. We develop a digit recognizer by training our model on the MNIST dataset with a convolutional neural network and contrast it with multiple models trained on combinations of the MNIST and custom digits. Using our methods, we observed results comparable with the baseline and provided recommendations for improving OCR accuracy for localized or personalized handwritten text. This study also provides an alternative perspective to generating data using conventional methods, which can serve as a gold standard for custom data augmentation to help address the challenges of scarce data and data imbalance. [ABSTRACT FROM AUTHOR]

The aim of this research is to define information crime in the relevant systems, including the Saudi antiinformatics crime system, as well as the definition of information crime tools and their characteristics. The national and international level. The study followed the analytical approach, then relied on secondary and primary information collection sources represented in books, references, and magazines. The most important findings of the researcher were the importance of knowing the nature and characteristics of information crime, clarifying the criteria, means and methods of committing it, indicating its difficulties, and encouraging researchers to research information crimes. And in the interpretation and application of laws to combat information crimes developed. [ABSTRACT FROM AUTHOR]

During 2014-2019, the Utah Department of Health (UDOH) enhanced its surveillance program for acute hepatitis C virus (HCV) infections by mandating electronic reporting of negative HCV test results in 2015 and liver function test results in 2016. UDOH also engaged with blood and plasma donation centers beginning in 2014 and syringe exchange programs in 2018 to encourage manual reporting of negative HCV test results from facilities without electronic reporting capabilities. UDOH hepatitis surveillance staff also provided training for case investigations in 2017. The number of cases detected increased 14-fold, from 9 during 2012 to 127 during 2019. In 2019, of 127 cases, 55% (n = 70) were detected through negative HCV test results reported electronically before positive test results (ie, recent seroconversions), 25% (n = 32) through positive HCV test results and elevated liver function test results, 18% (n = 23) through manually reported negative HCV test results, and 2% (n = 2) through positive HCV test results and clinical evidence. Challenges to surveillance included accessing patients for investigations and engaging donation centers in reporting negative test results. Utah's experience demonstrates practical considerations for improving surveillance of acute HCV infections. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this project was to develop and optimize a dashboard and registry to manage the distribution, utilization, and monitoring of coronavirus disease 2019 (COVID-19) emergency use–authorized medications (CEUAMs). Summary CEUAMs have specific requirements that must be met for prescribing, monitoring, and compliance. When remdesivir, the first COVID-19 medication with emergency use authorization (EUA), was approved, it immediately became necessary for the Veterans Health Administration, a national integrated health system, to describe the requirements for EUA, to distribute the medication in a fair and equitable manner, and to ensure compliance with all EUA requirements. A dashboard was developed and iteratively updated as additional CEUAMs were approved. The dashboard tracked CEUAM distribution and monitoring at the national, regional, facility, and patient level. Par stock levels were initially determined at the national level. Facilities were also able to request an additional allotment of medication based on demand and allocated supplies from the Department of Health and Human Services. Providers completed a questionnaire for the CEUAM for each patient to ensure all requirements for the medication were met. If there were data integrity concerns, the entry was flagged for review at the facility level and, upon evaluation, corrections were made. Conclusion Development of the dashboard was resource intensive but provided an excellent mechanism to share information among facilities and national offices. Other healthcare systems can develop similar dashboards to ensure appropriate use of CEUAMs for their patients while meeting all CEUAM requirements. [ABSTRACT FROM AUTHOR]

Background: Regional development must be creative and able to create and increase potential sources of income from parking services, one of the regional revenues. Supervision, parking management is still classified as uncontrolled, local revenue is not on target, from parking which is managed by the government. Purpose: The purpose of this study is to supervise the management of parking fees in increasing regional income. Mc. Farland, provides a definition of supervision (controlling), supervision is a process in which the leader wants to know whether the results of the implementation of the work carried out by his subordinates are in accordance with the plans, orders, goals or policies that have been determined. Method: Descriptive qualitative approach method, critical thinking about the situation, social phenomena that are illustrated relevant to the problem being studied, the process of carrying out tasks and solving problems with the supervision of parking Results: The results in this study, it should be noted that the management of parking fees has not been able to run properly because supervision is carried out by the Department of Transportation, Communication and Information of the City of Tanjungpinnag has not been maximized so that there is a leakage of revenue from parking fees and the existence of illegal parking which causes parking revenue not to enter the regional treasury. Conclusion: The conclusion of supervision of the management of parking fees by the Tanjungpinang City Dishubkominfo on parking fees objects on public roads is said to be not optimal, because there are still problems in managing parking fees activities on public roads and leakage of fees resulting so that the revenue target every year is not achieved. [ABSTRACT FROM AUTHOR]

The microbiomes associated with bee nests influence colony health through various mechanisms, although it is not yet clear how honeybee congeners differ in microbiome assembly processes, in particular the degrees to which floral visitations and the environment contribute to different aspects of diversity. We used DNA metabarcoding to sequence bacterial 16S rRNA from honey and stored pollen from nests of 4 honeybee species (Apis cerana, A. dorsata, A. florea, and A. laboriosa) sampled throughout Yunnan, China, a global biodiversity hotspot. We developed a computational pipeline integrating multiple databases for quantifying key facets of diversity, including compositional, taxonomic, phylogenetic, and functional ones. Further, we assessed candidate drivers of observed microbiome dissimilarity, particularly differences in floral visitations, habitat disturbance, and other key environmental variables. Analyses revealed that microbiome alpha diversity was broadly equivalent across the study sites and between bee species, apart from functional diversity which was very low in nests of the reclusive A. laboriosa. Turnover in microbiome composition across Yunnan was driven predominantly by pollen composition. Human disturbance negatively impacted both compositional and phylogenetic alpha diversity of nest microbiomes, but did not correlate with microbial turnover. We herein make progress in understanding microbiome diversity associated with key pollinators in a biodiversity hotspot, and provide a model for the use of a comprehensive informatics framework in assessing pattern and drivers of diversity, which enables the inclusion of explanatory variables both subtly and fundamentally different and enables elucidation of emergent or unexpected drivers. [ABSTRACT FROM AUTHOR]

Enormous recent progress in diagnostic testing can enable more accurate diagnosis and improved clinical outcomes. Yet these tests are increasingly challenging and frustrating; the volume and diversity of results may overwhelm the diagnostic acumen of even the most dedicated and experienced clinician. Because they are gathered and processed within the "silo" of each diagnostic discipline, diagnostic data are fragmented, and the electronic health record does little to synthesize new and existing data into usable information. Therefore, despite great promise, diagnoses may still be incorrect, delayed, or never made. Integrative diagnostics represents a vision for the future, wherein diagnostic data, together with clinical data from the electronic health record, are aggregated and contextualized by informatics tools to direct clinical action. Integrative diagnostics has the potential to identify correct therapies more quickly, modify treatment when appropriate, and terminate treatment when not effective, ultimately decreasing morbidity, improving outcomes, and avoiding unnecessary costs. Radiology, laboratory medicine, and pathology already play major roles in medical diagnostics. Our specialties can increase the value of our examinations by taking a holistic approach to their selection, interpretation, and application to the patient's care pathway. We have the means and rationale to incorporate integrative diagnostics into our specialties and guide its implementation in clinical practice. Key points: Although an overall boon to clinical diagnosis, increasingly voluminous, diverse, and fragmented diagnostic data can overwhelm physicians and frustrate patients. Data are gathered and processed within "silos" of the diagnostic disciplines, including radiology and pathology. The EHR does little to intelligently organize and synthesize these disparate data to facilitate diagnosis. ID envisions a process in which data from the entire arsenal of in vivo and in vitro diagnostics, together with clinical data from the EHR, are aggregated and contextualized to enhance diagnosis and direct clinical action [ABSTRACT FROM AUTHOR]

Clinical decision-making for diagnosing and treating oral and dental diseases consolidates multiple sources of complex information, yet individual clinical judgements are often made intuitively on limited heuristics to simplify decision making, which may lead to errors harmful to patients. This study aimed at systematically evaluating dental practitioners' clinical decision-making processes during diagnosis and treatment planning under uncertainty. A scoping review was chosen as the optimal study design due to the heterogeneity and complexity of the topic. Key terms and a search strategy were defined, and the articles published in the repository of the National Library of Medicine (MEDLINE/PubMed) were searched, selected, and analysed in accordance with PRISMA-ScR guidelines. Of the 478 studies returned, 64 relevant articles were included in the qualitative synthesis. Studies that were included were based in 27 countries, with the majority from the UK and USA. Articles were dated from 1991 to 2022, with all being observational studies except four, which were experimental studies. Six major recurring themes were identified: clinical factors, clinical experience, patient preferences and perceptions, heuristics and biases, artificial intelligence and informatics, and existing guidelines. These results suggest that inconsistency in treatment recommendations is a real possibility and despite great advancements in dental science, evidence-based practice is but one of a multitude of complex determinants driving clinical decision making in dentistry. In conclusion, clinical decisions, particularly those made individually by a dental practitioner, are potentially prone to sub-optimal treatment and poorer patient outcomes. [ABSTRACT FROM AUTHOR]