Integrated Surveillance of Disparities in Vaccination Coverage and Morbidity during the COVID-19 Pandemic: A Cohort Study in Southeast Sweden.

We aimed to use the digital platform maintained by the local health service providers in Southeast Sweden for integrated monitoring of disparities in vaccination and morbidity during the COVID-19 pandemic. The monitoring was performed in the adult population of two counties (n = 657,926) between 1 February 2020 and 15 February 2022. The disparities monitored were relocated (internationally displaced), substance users, and suffering from a psychotic disorder. The outcomes monitored were COVID-19 vaccination, SARS-CoV-2 test results, and hospitalization with COVID-19. Relocated residents displayed an increased likelihood of remaining unvaccinated and a decreased likelihood of testing as well as increased risks of primary SARS-CoV-2 infection and hospitalization compared with the general population. Suffering from a major psychiatric disease was associated with an increased risk of remaining unvaccinated and an increased risk of hospitalization but a decreased risk of SARS-CoV-2 infection. From the digital monitoring, we concluded that the relocated minority received insufficient protection during the pandemic, suggesting the necessity for comprehensive promotion of overall social integration. Persons with major psychiatric diseases underused vaccination, while they benefitted from proactively provided testing, implying a need for active encouragement of vaccination. Further research is warranted on legal and ethical frameworks for digital monitoring in vaccination programs.

A Study Examining the Impact of County-Level Demographic, Socioeconomic, and Political Affiliation Characteristics on COVID-19 Vaccination Patterns in Indiana.

The COVID-19 vaccination campaign resulted in uneven vaccine uptake throughout the United States, particularly in rural areas, areas with socially and economically disadvantaged groups, and populations that exhibited vaccine hesitancy behaviors. This study examines how county-level sociodemographic and political affiliation characteristics differentially affected patterns of COVID-19 vaccinations in the state of Indiana every month in 2021. We linked county-level demographics from the 2016-2020 American Community Survey Five-Year Estimates and the Indiana Elections Results Database with county-level COVID-19 vaccination counts from the Indiana State Department of Health. We then created twelve monthly linear regression models to assess which variables were consistently being selected, based on the Akaike Information Criterion (AIC) and adjusted R-squared values. The vaccination models showed a positive association with proportions of Bachelor's degree-holding residents, of 40-59 year-old residents, proportions of Democratic-voting residents, and a negative association with uninsured and unemployed residents, persons living below the poverty line, residents without access to the Internet, and persons of Other Race. Overall, after April, the variables selected were consistent, with the model's high adjusted R2 values for COVID-19 cumulative vaccinations demonstrating that the county sociodemographic and political affiliation characteristics can explain most of the variation in vaccinations. Linking county-level sociodemographic and political affiliation characteristics with Indiana's COVID-19 vaccinations revealed inherent inequalities in vaccine coverage among different sociodemographic groups. Increased vaccine uptake could be improved in the future through targeted messaging, which provides culturally relevant advertising campaigns for groups less likely to receive a vaccine, and increasing access to vaccines for rural, under-resourced, and underserved populations.

Fine-Tuned Large Language Model for Extracting Patients on Pretreatment for Lung Cancer from a Picture Archiving and Communication System Based on Radiological Reports.

This study aimed to investigate the performance of a fine-tuned large language model (LLM) in extracting patients on pretreatment for lung cancer from picture archiving and communication systems (PACS) and comparing it with that of radiologists. Patients whose radiological reports contained the term lung cancer (3111 for training, 124 for validation, and 288 for test) were included in this retrospective study. Based on clinical indication and diagnosis sections of the radiological report (used as input data), they were classified into four groups (used as reference data): group 0 (no lung cancer), group 1 (pretreatment lung cancer present), group 2 (after treatment for lung cancer), and group 3 (planning radiation therapy). Using the training and validation datasets, fine-tuning of the pretrained LLM was conducted ten times. Due to group imbalance, group 2 data were undersampled in the training. The performance of the best-performing model in the validation dataset was assessed in the independent test dataset. For testing purposes, two other radiologists (readers 1 and 2) were also involved in classifying radiological reports. The overall accuracy of the fine-tuned LLM, reader 1, and reader 2 was 0.983, 0.969, and 0.969, respectively. The sensitivity for differentiating group 0/1/2/3 by LLM, reader 1, and reader 2 was 1.000/0.948/0.991/1.000, 0.750/0.879/0.996/1.000, and 1.000/0.931/0.978/1.000, respectively. The time required for classification by LLM, reader 1, and reader 2 was 46s/2539s/1538s, respectively. Fine-tuned LLM effectively extracted patients on pretreatment for lung cancer from PACS with comparable performance to radiologists in a shorter time.

Geographic disparities and temporal changes of diabetes-related mortality risks in Florida: a retrospective study.

Background: Over the last few decades, diabetes-related mortality risks (DRMR) have increased in Florida. Although there is evidence of geographic disparities in pre-diabetes and diabetes prevalence, little is known about disparities of DRMR in Florida. Understanding these disparities is important for guiding control programs and allocating health resources to communities most at need. Therefore, the objective of this study was to investigate geographic disparities and temporal changes of DRMR in Florida. Methods: Retrospective mortality data for deaths that occurred from 2010 to 2019 were obtained from the Florida Department of Health. Tenth International Classification of Disease codes E10-E14 were used to identify diabetes-related deaths. County-level mortality risks were computed and presented as number of deaths per 100,000 persons. Spatial Empirical Bayesian (SEB) smoothing was performed to adjust for spatial autocorrelation and the small number problem. High-risk spatial clusters of DRMR were identified using Tango's flexible spatial scan statistics. Geographic distribution and high-risk mortality clusters were displayed using ArcGIS, whereas seasonal patterns were visually represented in Excel. Results: A total of 54,684 deaths were reported during the study period. There was an increasing temporal trend as well as seasonal patterns in diabetes mortality risks with high risks occurring during the winter. The highest mortality risk (8.1 per 100,000 persons) was recorded during the winter of 2018, while the lowest (6.1 per 100,000 persons) was in the fall of 2010. County-level SEB smoothed mortality risks varied by geographic location, ranging from 12.6 to 81.1 deaths per 100,000 persons. Counties in the northern and central parts of the state tended to have high mortality risks, whereas southern counties consistently showed low mortality risks. Similar to the geographic distribution of DRMR, significant high-risk spatial clusters were also identified in the central and northern parts of Florida. Conclusion: Geographic disparities of DRMR exist in Florida, with high-risk spatial clusters being observed in rural central and northern areas of the state. There is also evidence of both increasing temporal trends and Winter peaks of DRMR. These findings are helpful for guiding allocation of resources to control the disease, reduce disparities, and improve population health.

The Impact of Real-Time Documentation of In-Hospital Medication Changes on Preventing Undocumented Discrepancies at Discharge and Improving Physician-Pharmacist Communication: A Retrospective Cohort Study and Survey.

Background: Transitional medication safety is crucial, as miscommunication about medication changes can lead to significant risks. Unclear or incomplete documentation during care transitions can result in outdated or incorrect medication lists at discharge, potentially causing medication errors, adverse drug events, and inadequate patient education. These issues are exacerbated by extended hospital stays and multiple care events, making accurate medication recall challenging at discharge. Objective: Thus, we aimed to investigate how real-time documentation of in-hospital medication changes prevents undocumented medication changes at discharge and improves physician-pharmacist communication. Methods: We conducted a retrospective cohort study in a tertiary hospital. Two pharmacists reviewed medical records of patients admitted to the acute medical unit from April to June 2020. In-hospital medication discrepancies were determined by comparing preadmission and hospitalization medication lists and it was verified whether the physician's intent of medication changes was clarified by documentation. By a documentation rate of medication changes of 100% and <100%, respectively, fully documented (FD) and partially documented (PD) groups were defined. Any undocumented medication changes at discharge were considered a "documentation error at discharge". Pharmacists' survey was conducted to assess the impact of appropriate documentation on the pharmacists. Results: After reviewing 400 medication records, patients were categorized into FD (61.3%) and PD (38.8%) groups. Documentation errors at discharge were significantly higher in the PD than in the FD group. Factors associated with documentation errors at discharge included belonging to the PD group, discharge from a non-hospitalist-managed ward, and having three or more intentional discrepancies. Pharmacists showed favorable attitudes towards physician's documentation. Conclusion: Appropriate documentation of in-hospital medication changes, facilitated by free-text communication, significantly decreased documentation errors at discharge. This analysis underlines the importance of communication between pharmacists and hospitalists in improving patient safety during transitions of care.

During transitions of care, communication failures among healthcare professionals can lead to medication errors. Therefore, effective sharing of information is essential, especially when intentional changes in prescription orders are made. Documenting medication changes facilitates real-time communication, potentially improving medication reconciliation and reducing discrepancies. However, inadequate documentation of medication changes is common in clinical practice. This retrospective cohort study underlines the importance of real-time documentation of in-hospital medication changes. There was a significant reduction in documentation errors at discharge in fully documented group, where real-time documentation of medication changes was more prevalent. Pharmacists showed favorable attitudes toward the physician's real-time documenting of medication changes because it provided valuable information on understanding the physician's intent and improving communication and also saved time for pharmacists. This study concludes that physicians' documentation on medication changes may reduce documentation errors at discharge, meaning that proper documentation of medication changes could enhance patient safety through effective communication.

Innovative BIM technology application in the construction management of highway.

Within the global architecture, engineering, and construction industry, the use of Building Information Modeling (BIM) technology has significantly expanded. However, given the unique characteristics of road infrastructure, the application of BIM technology is still being explored. This article focuses on the Yuanchen Expressway, exploring innovative applications of BIM technology in comprehensive construction management. The project employs advanced technologies, including BIM, Geographic Information Systems (GIS), and the Internet of Things (IoT), to precisely identify critical nodes and breakthroughs. Supported by a detailed BIM model and a multi-level, diversified digital management platform, the project effectively addresses construction challenges in multiple tunnels, bridges, and complex interchanges, achieving intelligent construction innovation throughout the Yuanchen Expressway with BIM technology. By guiding construction through BIM models, utilizing a BIM+GIS-based management cloud platform system, and employing VR safety briefings, the project effectively reduces the difficulty of communication and coordination in project management, shortens the project measurement cycle, improves on-site work efficiency, and ensures comprehensive control and safety management. This article provides an exemplary case for the application of full-line construction management using BIM technology in the highway sector both in China and globally, offering new perspectives and strategies for highway construction management.

Computed tomography and magnetic resonance imaging in Brazil: an epidemiological study on the distribution of equipment and frequency of examinations, with comparisons between the public and private sectors.

Objective: To compare information on highly complex radiological procedures-computed tomography (CT) and magnetic resonance imaging (MRI)-between the public and private health care systems, across the five regions of Brazil, in terms of the numbers of radiological devices and examinations performed, between 2015 and 2021. Materials and Methods: This was a descriptive time series analysis of secondary data in the public domain, available from the Information Technology Department of the Brazilian Unified Health Care System, an entity of the Brazilian National Ministry of Health (NMH) that is responsible for collecting and storing health-related information in Brazil. The analysis included the numbers of CT and MRI scanners; the volumes and types of examinations; the type of institution (public or private); the regions of the country; and the years (2015 to 2021). Results: Progressive increases in the numbers of CT and MRI devices, as well as in the volumes of examinations, were observed over the years in all regions of the country. The private sector showed higher rates of equipment acquisition and of growth in the number of examinations. However, the public health care system did not reach the equipment targets set by the NMH, whereas the private health care system surpassed those targets. A greater number of examinations were performed in the private sector than in the public sector. Conclusion: During the period evaluated, the public health care system did not meet the equipment or examination targets recommended by the NMH, in any of the regions of the country, unlike the private health care system, which exceeded both in all of the regions.

Objetivo: Comparar informações sobre procedimentos radiológicos de alta complexidade ­ tomografia computadorizada (TC) e ressonância magnética (RM) ­, considerando o número de aparelhos e o quantitativo de exames nas esferas pública e privada nas cinco regiões brasileiras entre 2015 e 2021. Materiais e Métodos: Trata-se de um estudo descritivo de série temporal que utilizou dados secundários do Departamento de Informática do Sistema Único de Saúde, órgão do Ministério da Saúde (MS) responsável pela coleta e armazenamento das informações relacionadas à saúde no Brasil. Analisamos os números de aparelhos e de exames de TC e RM, considerando os tipos de aparelhos e exames, instituição (pública ou privada), região brasileira e ano (2015 a 2021). Resultados: Houve aumento de aparelhos e exames de TC e RM em todas as regiões ao longo dos anos. A esfera privada apresentou maior aquisição desses aparelhos e crescimento no número de exames. O sistema público não atingiu o número de aparelhos preconizado pelo MS, enquanto o sistema privado superou a recomendação. Observou-se maior número de exames na esfera privada quando comparada à pública. Conclusão: O sistema público não atendeu aos números de aparelhos e exames realizados preconizados pelo MS, diferentemente da esfera privada, em todas as regiões no período estudado.

Clinical, epidemiological characteristics and mortality of pregnant and postpartum women associated with COVID-19 in Brazil: cohort study.

Objective: To analyze the death of Brazilian pregnant and postpartum women due to COVID-19 or unspecific cause. Methods: This is retrospective, descriptive-exploratory, population-based study carried out with the Sistema de Informação de Vigilância Epidemiológica da Gripe (SIVEP-Gripe) database, with pregnant and postpartum women of reproductive age who died from confirmed COVID-19 between 2020 and 2021. The chosen variables were: age, gestational period, type and number of comorbidities, skin color, using the statistical software R Foundation for Statistical Computing Platform, version 4.0.3 and Statistical Package for Social Science, version 29.0 for analysis. Results: A total of 19,333 cases of pregnant and postpartum women aged between 10 and 55 years diagnosed with SARS were identified, whether due to confirmed COVID-19 or unspecific causes. Of these, 1,279 died, these cases were classified into two groups according to the cause of death: deaths from COVID-19 (n= 1,026) and deaths from SARS of unspecific cause (n= 253). Conclusion: The risk of death increased among black and brown women, in the postpartum period and with the presence of comorbidities, mainly diabetes, cardiovascular diseases and obesity. The data presented here draw attention to the number of deaths from SARS, especially among sociodemographic profiles, precarious access to health, such as the black population. In addition, limitations in adequate access to health care are reinforced by even lower rates of ICU admissions among women who died from SARS of an unspecified cause.

GIS-based spatiotemporal mapping of malaria prevalence and exploration of environmental inequalities.

Malaria poses a significant threat to global health, with particular severity in Nigeria. Understanding key factors influencing health outcomes is crucial for addressing health disparities. Disease mapping plays a vital role in assessing the geographical distribution of diseases and has been instrumental in epidemiological research. By delving into the spatiotemporal dynamics of malaria trends, valuable insights can be gained into population dynamics, leading to more informed spatial management decisions. This study focused on examining the evolution of malaria in Nigeria over twenty years (2000-2020) and exploring the impact of environmental factors on this variation. A 5-year-period raster map was developed using malaria indicator survey data for Nigeria's six geopolitical zones. Various spatial analysis techniques, such as point density, spatial autocorrelation, and hotspot analysis, were employed to analyze spatial patterns. Additionally, statistical methods, including Principal Component Analysis, Spearman correlation, and Ordinary Least Squares (OLS) regression, were used to investigate relationships between indicators and develop a predictive model. The study revealed regional variations in malaria prevalence over time, with the highest number of cases concentrated in northern Nigeria. The raster map illustrated a shift in the distribution of malaria cases over the five years. Environmental factors such as the Enhanced Vegetation Index, annual land surface temperature, and precipitation exhibited a strong positive association with malaria cases in the OLS model. Conversely, insecticide-treated bed net coverage and mean temperature negatively correlated with malaria cases in the same model. The findings from this research provide valuable insights into the spatiotemporal patterns of malaria in Nigeria and highlight the significant role of environmental drivers in influencing disease transmission. This scientific knowledge can inform policymakers and aid in developing targeted interventions to combat malaria effectively.

Transforming experimental radiology: Design and implementation of an innovative ePACS image storage system for AI imaging research environments.

INTRODUCTION AND PURPOSE: We present the needs, design, development, implementation, and accessibility of a crafted experimental PACS (ePACS) system to securely store images, ensuring efficiency and ease of use for AI processing, specifically tailored for research scenarios, including phantoms, animal and human studies and quality assurance (QA) exams. The ePACS system plays a crucial role in any medical imaging departments that handle non-care profile studies, such as protocol adjustments and dummy runs. By effectively segregating non-care profile studies from the healthcare assistance, the ePACS usefully prevents errors both in clinical practice and storage security. METHODS AND RESULTS: The developed ePACS system considers the best practices for management, maintenance, access, long-term storage and backups, regulatory audits, and economic aspects. Moreover, key aspects of the ePACS system include the design of data flows with a focus on incorporating data security and privacy, access control and levels based on user profiles, internal data management policies, standardized architecture, infrastructure and application monitorization and traceability, and periodic backup policies. A new tool called DicomStudiesQA has been developed to standardize the analysis of DICOM studies. The tool automatically identifies, extracts, and renames series using a consistent nomenclature. It also detects corrupted images and merges separated dynamic series that were initially split, allowing for streamlined post-processing. DISCUSSION AND CONCLUSIONS: The developed ePACS system encompasses a successful implementation, both in hospital and research environments, showcasing its transformative nature and the challenging yet crucial transfer of knowledge to industry. This underscores the practicality and real-world applicability of our innovative approach, highlighting the significant impact it has on the field of experimental radiology.

The Paradoxes of Digital Tools in Hospitals: Qualitative Interview Study.

BACKGROUND: Digital tools are progressively reshaping the daily work of health care professionals (HCPs) in hospitals. While this transformation holds substantial promise, it leads to frustrating experiences, raising concerns about negative impacts on clinicians' well-being. OBJECTIVE: The goal of this study was to comprehensively explore the lived experiences of HCPs navigating digital tools throughout their daily routines. METHODS: Qualitative in-depth interviews with 52 HCPs representing 24 medical specialties across 14 hospitals in Switzerland were performed. RESULTS: Inductive thematic analysis revealed 4 main themes: digital tool use, workflow and processes, HCPs' experience of care delivery, and digital transformation and management of change. Within these themes, 6 intriguing paradoxes emerged, and we hypothesized that these paradoxes might partly explain the persistence of the challenges facing hospital digitalization: the promise of efficiency and the reality of inefficiency, the shift from face to face to interface, juggling frustration and dedication, the illusion of information access and trust, the complexity and intersection of workflows and care paths, and the opportunities and challenges of shadow IT. CONCLUSIONS: Our study highlights the central importance of acknowledging and considering the experiences of HCPs to support the transformation of health care technology and to avoid or mitigate any potential negative experiences that might arise from digitalization. The viewpoints of HCPs add relevant insights into long-standing informatics problems in health care and may suggest new strategies to follow when tackling future challenges.

Detrimental Increase of Spin-Phonon Coupling in Molecular Qubits on Substrates.

Molecular qubits are a promising platform for quantum information systems. Although single molecule and ensemble studies have assessed the performance of S = 1/2 molecules, it is understood that to function in devices, regular arrays of addressable qubits supported by a substrate are needed. The substrate imposes mechanical and electronic boundary conditions on the molecule; however, the impact of these effects on spin-lattice relaxation times is not well understood. Here we perform electronic structure calculations to assess the effects of a graphene (Cgr) substrate on the molecular qubit copper phthalocyanine (CuPc). We use a progressive Hessian approach to efficiently calculate and separate the substrate contributions. We also use a simple thermal model to predict the impact of these changes on the spin-phonon coupling from 0 to 200 K. Further analysis of the individual vibrational modes with and without Cgr shows that an overall increase in SPC between the vibrations modes of CuPc with the surface reduces the spin-lattice relaxation time T1. We explain these changes by examining how the substrate lifts symmetries of CuPc in the absorbed configuration. Our work shows that a surface can have a large unintentional impact on SPC and that ways to reduce this coupling need to be found to fully exploit arrays of molecular qubits in device architectures.

Architectural design of national evidence based medicine information system based on electronic health record.

BACKGROUND: The global implementation of Electronic Health Records has significantly enhanced the quality of medical care and the overall delivery of public health services. The incorporation of Evidence-Based Medicine offers numerous benefits and enhances the efficacy of decision-making in areas such as prevention, prognosis, diagnosis, and therapeutic approaches. OBJECTIVE: The objective of this paper is to propose an architectural design of an Evidence-Based Medicine information system based on the Electronic Health Record, taking into account the existing and future level of interoperability of health information systems in Greece. METHODS: A study of the suggested evidence-based medicine architectures found in the existing literature was conducted. Moreover, the interoperability architecture of health information systems in Greece was analyzed. The architecture design reviewed by specialized personnel and their recommendations were incorporated into the final design of the proposed architecture. RESULTS: The proposed integrated architecture of an Evidence-Based Medicine system based on the Electronic Health Record integrates and utilizes citizens' health data while leveraging the existing knowledge available in the literature. CONCLUSIONS: Taking into consideration the recently established National Interoperability Framework, which aligns with the European Interoperability Framework, the proposed realistic architectural approach contributes to improving the quality of healthcare provided through the ability to make safe, timely and accurate decisions by physicians.

Census tract geospatial analysis comparing social determinants of health with tooth loss in California seniors: An ecologic study.

OBJECTIVES: Individual-level social determinant of health (SDOH) measures alone may insufficiently explain disparities in edentulism among seniors. Therefore, the authors examined the correlation of census tract-level SDOH and residential racial segregation measures with edentulism in Californian adults aged ≥65 years old. METHODS: Explanatory variables were obtained from Healthy Places Index (HPI), the National Cancer Institute and diversitydatakids.org. The edentulism outcome variable was obtained from CDC's PLACES small area estimates from the 2018 Behavioral Risk Factor Surveillance System data. Pearson and Spearman rank correlations were estimated. Multiple linear regression and multi-collinearity evaluations were performed. The Global Moran's I statistic assessed partial autocorrelation within census tracts. RESULTS: Pearson and Spearman correlations were similar, supporting robustness. HPI, an area measure of advantage, strongly negatively correlated with edentulism prevalence [correlation coefficient: -0.87; 95% confidence interval (CI): -0.87, -0.86]. A change of 1.0 in HPI corresponded to an estimated decrease in edentulism prevalence of 5.9% (linear model adjusted R2 = 0.78). Racially segregated census tracts with Hispanics or Blacks alone were positively correlated with edentulism prevalence [0.60, 95% CI: 0.58, 0.62; and 0.33, 95% CI: 0.31, 0.35, respectively]. The converse was seen in census tracts with non-Hispanic Whites alone [-0.57, 95% CI: -0.58, -0.55]. Global Moran's I statistic for edentulism (0.13) and HPI scores (0.19) were significant (both p < .001) indicating geospatial autocorrelation. CONCLUSIONS: Higher disadvantage and minority racial segregation within census tracts were positively correlated with edentulism prevalence. Future research and policy should consider possible interventions improving SDOH to reduce oral health inequities.

Activity, triage levels and impact of the pandemic on hospital emergency departments: A multicentre cross-sectional study.

AIM: Describe the activity of hospital emergency departments (EDs) and the sociodemographic profile of patients in the eight public hospitals in Spain, according to the different triage levels, and to analyse the impact of the SARS-CoV-2 pandemic on patient flow. DESIGN: An observational, descriptive, cross-sectional and retrospective study was carried out. METHODS: Three high-tech public hospitals and five low-tech hospitals consecutively included 2,332,654 adult patients seen in hospital EDs from January 2018 to December 2021. Hospitals belonging to the Catalan Institute of Health. The main variable was triage level, classified according to a standard for the Spanish structured triage system known as Sistema Español de Triaje. For each of the five triage levels, a negative binomial regression model adjusted for year and hospital was performed. The analysis was performed with the R 4.2.2 software. RESULTS: The mean age was 55.4 years. 51.4% were women. The distribution of patients according to the five triage levels was: level 1, 0.41% (n = 9565); level 2, 6.10% (n = 142,187); level 3, 40.2% (n = 938,203); level 4, 42.6% (n = 994,281); level 5, 10.6% (n = 248,418). The sociodemographic profile was similar in terms of gender and age: as the level of severity decreased, the number of women, mostly young, increased. In the period 2020-2021, the emergency rate increased for levels 1, 2 and 3, but levels 4 and 5 remained stable. CONCLUSION: More than half of the patients attended in high-technology hospital EDs were of low severity. The profile of these patients was that of a young, middle-aged population, mostly female. The SARS-CoV2 pandemic did not change this pattern, but an increase in the level of severity was observed. IMPACT: What problem did the study address? There is overcrowding in hospital EDs. What were the main findings? This study found that more than half of the patients attended in high-technology hospital EDs in Spain have low or very low levels of severity. Young, middle-aged women were more likely to visit EDs with low levels of severity. The SARS-CoV2 pandemic did not change this pattern, but an increase in severity was observed. Where and on whom will the research have an impact? The research will have an impact on the functioning of hospital EDs and their staff. PATIENT OR PUBLIC CONTRIBUTION: Not applicable.

Artificial Intelligence in Nursing: Perspectives from Norwegian Nurses.

Nurses continue to face challenges in leading health information technology innovations such as Artificial Intelligence (AI). There is an acknowledged need to explore the attitude of nurses towards AI and nurses' acceptance of AI in clinical settings. We sought to address this gap in knowledge about the perceptions of AI by nursing-related professionals in their work and as a content area in the education of nursing students. Norwegian nurses and healthcare personnel interested in the topic met in a seminar in Oslo in 2023 to explore their perspectives on AI. Following a lecture on AI, audience members offered their insights in a recorded discussion. Data analysis consisted of inductive coding of concepts in the transcribed recording. Three major themes emerged: Expectations, Identified needs and related recommendations; and Policy to guard safety; as well as recommendations new to the literature.

Social Determinants of Health Screening, Referral, and Outcomes: Toward an Evidence-Based Simulation Model.

A more complete conceptual model of the social determinants of health (SDOH) screening and referral process is needed to identify effective interventions to address unmet social needs that impact health outcomes. The objective was to develop an evidence-based, complex, multi-factorial model that makes explicit the behaviors and experiences of both patients and the care team (factors) who use an SDOH platform to facilitate patient connections to community resources. The resulting model organized 88 factors among five main stages in the process and among health outcomes. Factors were grouped into eight categories among person, system, and organization levels. Most factors were related to the screening process, with sparse factors related to referral completion. The resulting model is offered as an initial step toward the development of a simulation model to assess interventions before implementation in real-world settings.

Gender Harmony: A Case for Nursing Informatics.

The design of digital health information systems around a conflated gender/sex binary contributes to health inequities. Lack of specific information that supports affirming communication lead to inappropriate care, disrespectful encounters with healthcare staff, and avoidance of health services by clients who have been harmed by misgendering, deadnaming and being outed. The HL7 International Gender Harmony Model (HL7 GHM) supports the design, implementation and use of DHIS that enable affirming clinical interactions and care. This case study will demonstrate how applying the HL7 GHM can address the harms reported in a recently published account of one patient in Canada.

Applying a Master Project Plan Methodology to Develop an Age-Friendly 4Ms Clinical Documentation Tool.

The issue of lacking standardized organizational guidance is examined in the context of providing patient-centered care to meet the needs of an aging population. Standardization across an integrated organization is increasingly recognized as a social justice concern in the pursuit of equitable and timely healthcare delivery, particularly as the healthcare industry grapples with a severe nursing shortage in the United States. A master project plan methodology (MPPM) was tested to effectively develop an electronic Age-Friendly 4Ms documentation tool using the system development lifecycle (SDLC) framework. The MPPM successfully guided the design and national implementation, achieving an 84% installation rate across 124 facilities within one of America's largest integrated healthcare systems.

Health information systems with technology acceptance model approach: A systematic review.

In the rapidly evolving landscape of information technologies, individuals and organizations must adapt to the digital age. Given the diversity in users' knowledge and experience with technology, their acceptance levels also vary. Over the past 30 years, various theoretical models have been introduced to provide a framework for understanding user acceptance of technology. Among these, the Technology Acceptance Model (TAM) stands out as a key theoretical framework, offering insights into why new technologies are either accepted or rejected. Analyzing user acceptance of technology has thus become a critical area of study. Healthcare organizations aim to assess the perceived efficacy and user-friendliness of a given technology. This will help health organisations design and implement HIS that meet users' needs and preferences. In this context, how does the TAM clarify the acceptance and use of Health Information Systems (HIS)? To address this inquiry, a comprehensive literature review will be carried out. The systematic review involved 29 studies issued between 2018 and 2023 and searched the databases Pubmed, Scopus, Wos and Ulakbim TR Index. The PRISMA flowchart was used to identify the included studies. According to the results, some variables stand out in the acceptance and utilisation of HIS. Among the users of HIS, it can be said that the results relating to nurses stand out. In particular, there are studies which emphasise that 'gender' is a crucial factor in explaining the models. Another crucial finding of the current systematic review is the need to train users in the acceptance and use of HIS.