The Automatic Context Measurement Tool (ACMT) to Compile Participant-Specific Built and Social Environment Measures for Health Research: Development and Usability Study.

BACKGROUND: The environment shapes health behaviors and outcomes. Studies exploring this influence have been limited to research groups with the geographic information systems expertise required to develop built and social environment measures (eg, groups that include a researcher with geographic information system expertise). OBJECTIVE: The goal of this study was to develop an open-source, user-friendly, and privacy-preserving tool for conveniently linking built, social, and natural environmental variables to study participant addresses. METHODS: We built the automatic context measurement tool (ACMT). The ACMT comprises two components: (1) a geocoder, which identifies a latitude and longitude given an address (currently limited to the United States), and (2) a context measure assembler, which computes measures from publicly available data sources linked to a latitude and longitude. ACMT users access both of these components using an RStudio/RShiny-based web interface that is hosted within a Docker container, which runs on a local computer and keeps user data stored in local to protect sensitive data. We illustrate ACMT with 2 use cases: one comparing population density patterns within several major US cities, and one identifying correlates of cannabis licensure status in Washington State. RESULTS: In the population density analysis, we created a line plot showing the population density (x-axis) in relation to distance from the center of the city (y-axis, using city hall location as a proxy) for Seattle, Los Angeles, Chicago, New York City, Nashville, Houston, and Boston with the distances being 1000, 2000, 3000, 4000, and 5000 m. We found the population density tended to decrease as distance from city hall increased except for Nashville and Houston, 2 cities that are notably more sprawling than the others. New York City had a significantly higher population density than the others. We also observed that Los Angeles and Seattle had similarly low population densities within up to 2500 m of City Hall. In the cannabis licensure status analysis, we gathered neighborhood measures such as age, sex, commute time, and education. We found the strongest predictive characteristic of cannabis license approval to be the count of female children aged 5 to 9 years and the proportion of females aged 62 to 64 years who were not in the labor force. However, after accounting for Bonferroni error correction, none of the measures were significantly associated with cannabis retail license approval status. CONCLUSIONS: The ACMT can be used to compile environmental measures to study the influence of environmental context on population health. The portable and flexible nature of ACMT makes it optimal for neighborhood study research seeking to attribute environmental data to specific locations within the United States.

Data quality in hospital information systems: Lessons learned from analyzing 30 years of patient data in a regional German hospital.

BACKGROUND: The integration of Hospital Information Systems (HIS) into healthcare delivery has significantly enhanced patient care and operational efficiency. Nonetheless, the rapid acceleration of digital transformation has led to a substantial increase in the volume of data managed by these systems. This emphasizes the need for robust mechanisms for data management and quality assurance. OBJECTIVE: This study addresses data quality issues related to patient identifiers within the Hospital Information System (HIS) of a regional German hospital, focusing on improving the accuracy and consistency of these administrative data entries. METHODS: Employing a combination of data analysis and expert interviews, this study reviews and programmatically cleanses a dataset with over 2,000,000 patient data entries extracted from the HIS. The areas of investigation are patient admissions, discharges, and geographical data. RESULTS: The analysis revealed that roughly 25% of the dataset was rendered unusable by errors and inconsistencies. By implementing a thorough data cleansing process, we significantly enhanced the utility of the dataset. In doing so, we identified the primary issues affecting data quality, including ambiguities among similar variables and a gap between the intended and actual use of the system. CONCLUSION: The findings highlight the critical importance of enhancing data quality in healthcare information systems. This study shows the necessity of a careful review of data extracted from the HIS before it can be reliably utilized for machine learning tasks, thereby rendering the data more usable for both clinical and analytical purposes.

Trends in continuity of treatment among children and adolescents living with HIV in 14 districts in South Africa from 2018-2023: A retrospective program analysis.

Objectives: UNAIDS estimates 152,984 children under 15 years living with HIV (C/ALHIV) by 2022 in South Africa. Monitoring the continuity of antiretroviral treatment remains challenging without electronic health records. We explored treatment cohort growth and interruption trends in 14-USAID-PEPFAR-supported districts. Methods: We reviewed data from 2018 to 2023. We triangulated this data with NAOMI HIV estimates. We used Tableau version 2023.2 for analysis to understand heterogeneity in outcomes. Results: HIV incidence halved from 4.3 per 1000 in 2017 to 2.5 per 1000 in 2022. HIV testing doubled: 188,371 in FY19Q1 to 399,708 in FY23Q4 while testing positivity declined from 3.3% to 0.7%. Linkage to treatment increased from 67% to 102%, viral suppression increased from 79% to 84%. C/ALHIV treatment cohort started at 82,897 in FY19Q1 and increased to 105,107 in FY20Q2. Subsequently, the cohort decreased to 79,288 in FY23Q4 despite 42,498 initiations and 62,256 returns. Conclusions: The C/ALHIV treatment and viral suppression increased substantially commensurate with expected trends. Subsequent cohort decline was aligned to vertical transmission reduction, HIV incidence decline, and expected aging. We highlight the inadequacy of the information systems to quantify losses. We underscore a need for resources to enhance program monitoring and interventions to address this gap.

Examining the development and utilisation of Community-Based Health Information Systems (CBHIS) in Africa: A Scoping Review.

Introduction: The community-based health information system (CBHIS) is a vital component of the community health system, as it assesses community-level healthcare service delivery and generates data for community health programme planning, monitoring, and evaluation. CBHIS promotes data-driven decision-making, by identifying priority interventions and programs, guiding resource allocation, and contributing to evidence-based policy development. Objective: This scoping review aims to comprehensively examine the use of CBHIS in African countries, focusing on data generation, pathways, utilization of CBHIS data, community accessibility to the data and use of the data to empower communities. Methods: We utilised Arksey and O'Malley's scoping review methodology. We searched eight databases: PubMed, EMBASE, HINARI, Cochrane Library, Web of Science, Scopus, Google Scholar, and grey literature databases (Open Grey and OAIster). We synthesized findings using a thematic approach. Results: Our review included 55 articles from 27 African countries, primarily in Eastern and Southern Africa, followed by West Africa. Most of the studies were either quantitative (42%) or qualitative (33%). Paper-based systems are primarily used for data collection in most countries, but some have adopted electronic/mobile-based systems or both. The data flow for CBHIS varies by country and the tools used for data collection. CBHIS data informs policies, resource allocation, staffing, community health dialogues, and commodity supplies for community health programmes. Community dialogue is the most common approach for community engagement, empowerment, and sharing of CBHIS data with communities. Community empowerment tends towards health promotion activities and health provider-led approaches. Conclusion: CBHIS utilizes both paper-based and electronic-based systems to collect and process data. Nevertheless, most countries rely on paper-based systems. Most of the CBHIS investments have focused on its digitization and enhancing data collection, process, and quality. However, there is a need to shift the emphasis towards enabling data utilisation at the community level and community empowerment.

For community health services and systems to work well, health managers and other data users, including policy and decision-makers, need a community-based health information system (CBHIS) that produces reliable and timely information on how well these services are working and that supports the use of CBHIS data to improve community health service delivery. This scoping review aimed to explore the use of CBHIS in African countries. It focused on data generation, pathways, use of CBHIS data, community data access, and use of CBHIS data to empower communities. The review authors collected and analysed all relevant studies to answer this question and found 55 articles from 27 African countries. The review found that most countries use paper-based information systems for data collection, while some have adopted electronic and digital systems. CBHIS also collects information on human resources, medicines, and supply systems. CBHIS data are used to guide policy development, allocate resources, track commodities supplies, staff for community health programmes and organise community health dialogues. Community dialogue is the most common approach for engaging, empowering, and sharing CBHIS data with communities. Community empowerment involves activities that promote health and health provider-led approaches. There is a need to focus on enabling the use of data at the community level and empowerment.

Development of a practical framework and indicators for monitoring integrated long-term health and care needs and service use.

This case study presents an evidence-building approach to support policy planning for integrated health and care delivery for older adults. We developed an integrated needs-assessment framework to monitor the complex long-term medical and care needs of older individuals, using routinely collected, standardized needs-assessment and utilization data from the public health and long-term care (LTC) insurance systems in South Korea. We also developed a set of misuse indicators and analyzed service utilization patterns, while accounting for their varying types of needs. Approximately 11 % of older Koreans were identified as having complex long-term medical and care needs, which were categorized into four distinct need groups. More than one-third of those in the higher-medical/lower-care needs group stayed in LTC hospitals for six months or more during the year, and about one-third of those in the higher-medical/higher-care needs group inappropriately resided in LTC facilities, where medical services are limited. The newly developed integrated needs-assessment framework and misuse indicator set provide practical tools for monitoring the extent and nature of complex needs, as well as patterns of over- or under-utilization of health and care services over time. The empirical evidence gathered here highlights the need for reforms in South Korea's health and LTC systems.

Implementing telemedicine with 5G technologies in a nursing home for reducing emergency admissions- study protocol of a mixed-methods study.

BACKGROUND: By transmitting various types of data, telemedical care enables the provision of care where physicians and patients are physically separated. In nursing homes, telemedicine has the potential to reduce hospital admissions in nonemergency situations. In this study, telemedicine devices were implemented with the new 5G mobile communications standard in selected wards of a large nursing home in Northwest Germany. The main aim of this study is to investigate which individual and organizational factors are associated with the use of telemedicine devices and how users perceive the feasibility and implementation of such devices. Moreover, it is investigated whether the telemedical devices help to reduce the number of emergency admissions. METHODS: Telemedicine devices are implemented over an 18-month period using a private 5G network, and all users receive training. This study uses qualitative and quantitative methods: To assess the individual and organizational factors associated with the use of telemedicine devices, survey data from employees before and after the implementation of these devices are compared. To assess the perception of the implementation process as well as the feasibility and usability of the telemedical devices, the nursing staff, physicians, medical assistants and residents are interviewed individually. Moreover, every telemedicine consultation is evaluated with a short survey. To assess whether the number of emergency admissions decreased, data from one year before implementation and one year after implementation are compared. The data are provided by the integrated dispatch centre and emergency medical services (EMS) protocols. The interview data are analysed via structured qualitative content analysis according to Kuckartz. Survey data are analysed using multivariable regression analysis. DISCUSSION: Learnings from the implementation process will be used to inform future projects implementing telemedicine in care organizations, making the final telemedicine implementation and care concept available to more nursing homes and hospitals. Moreover, the study results can be used to provide use cases for appropriate and targeted application of telemedicine in nursing homes and to define the role of 5G technologies in these use cases. If the intervention is proven successful, the results will be used to promote 5G network rollout. TRIAL REGISTRATION: German Clinical Trials Register - trial registration number: DRKS00030598.

Quality, Usability, and Trust Challenges to Effective Data Use in the Deployment and Use of the Bangladesh Nutrition Information System Dashboard: Qualitative Study.

BACKGROUND: Evidence-based decision-making is essential to improve public health benefits and resources, especially in low- and middle-income countries (LMICs), but the mechanisms of its implementation remain less straightforward. The availability of high-quality, reliable, and sufficient data in LMICs can be challenging due to issues such as a lack of human resource capacity and weak digital infrastructure, among others. Health information systems (HISs) have been critical for aggregating and integrating health-related data from different sources to support evidence-based decision-making. Nutrition information systems (NISs), which are nutrition-focused HISs, collect and report on nutrition-related indicators to improve issues related to malnutrition and food security-and can assist in improving populations' nutritional statuses and the integration of nutrition programming into routine health services. Data visualization tools (DVTs) such as dashboards have been recommended to support evidence-based decision-making, leveraging data from HISs or NISs. The use of such DVTs to support decision-making has largely been unexplored within LMIC contexts. In Bangladesh, the Mukto dashboard was developed to display and visualize nutrition-related performance indicators at the national and subnational levels. However, despite this effort, the current use of nutrition data to guide priorities and decisions remains relatively nascent and underused. OBJECTIVE: The goal of this study is to better understand how Bangladesh's NIS, including the Mukto dashboard, has been used and areas for improvement to facilitate its use for evidence-based decision-making toward ameliorating nutrition-related service delivery and the health status of communities in Bangladesh. METHODS: Primary data collection was conducted through qualitative semistructured interviews with key policy-level stakeholders (n=24). Key informants were identified through purposive sampling and were asked questions about the experiences and challenges with the NIS and related nutrition dashboards. RESULTS: Main themes such as trust, data usability, personal power, and data use for decision-making emerged from the data. Trust in both data collection and quality was lacking among many stakeholders. Poor data usability stemmed from unstandardized indicators, irregular data collection, and differences between rural and urban data. Insufficient personal power and staff training coupled with infrastructural challenges can negatively affect data at the input stage. While stakeholders understood and expressed the importance of evidence-based decision-making, ultimately, they noted that the data were not being used to their maximum potential. CONCLUSIONS: Leveraging DVTs can improve the use of data for evidence-based decision-making, but decision makers must trust that the data are believable, credible, timely, and responsive. The results support the significance of a tailored data ecosystem, which has not reached its full potential in Bangladesh. Recommendations to reach this potential include ensuring a clear intended user base and accountable stakeholders are present. Systems should also have the capacity to ensure data credibility and support ongoing personal power requirements.

Design, develop, and implement the strategic information system on health, dependence, and healthy aging: an analysis of the Mexican experience.

BACKGROUND: The Decade of Healthy Aging (2021-2030) emerges as a 10 years strategy to improve the lives of older adults, their families, and the communities in which they live. One of the actions defined in this framework is related to improving the measurement, monitoring, and understanding of characteristics, factors, and needs related to aging and health. The aim was to analyze and assess the process of construction and development of the Strategic Information System on Health, Funcional Dependence and Aging (SIESDE, for its acronym in Spanish). SIESDE will provide strategic information in Mexico at the municipal, state, and national levels that support the public policies on healthy aging. METHODS: The system processes and analyzes the data sources of the Health Information Systems and the National System of Statistical and Geographical Information. SIESDE comprises three components: (1) Design, construction, and evaluation of the indicators; (2) storage, management, and visualization, and (3) diffusion and translation of information. RESULTS: A total of 135 indicators were built on seven themes: (1) demographic, socioeconomic, and aging conditions, (2) health, (3) functional dependence, (4) healthy aging, (5) health services, (6) social and physical environments, and (7) complex indicators. CONCLUSIONS: SIESDE is an effective system for providing an overall view of health, aging, and functional dependence.

A Pipeline for the Usage of the Core Data Set of the Medical Informatics Initiative for Process Mining - A Technical Case Report.

INTRODUCTION: Process Mining (PM) has emerged as a transformative tool in healthcare, facilitating the enhancement of process models and predicting potential anomalies. However, the widespread application of PM in healthcare is hindered by the lack of structured event logs and specific data privacy regulations. CONCEPT: This paper introduces a pipeline that converts routine healthcare data into PM-compatible event logs, leveraging the newly available permissions under the Health Data Utilization Act to use healthcare data. IMPLEMENTATION: Our system exploits the Core Data Sets (CDS) provided by Data Integration Centers (DICs). It involves converting routine data into Fast Healthcare Interoperable Resources (FHIR), storing it locally, and subsequently transforming it into standardized PM event logs through FHIR queries applicable on any DIC. This facilitates the extraction of detailed, actionable insights across various healthcare settings without altering existing DIC infrastructures. LESSONS LEARNED: Challenges encountered include handling the variability and quality of data, and overcoming network and computational constraints. Our pipeline demonstrates how PM can be applied even in complex systems like healthcare, by allowing for a standardized yet flexible analysis pipeline which is widely applicable.The successful application emphasize the critical role of tailored event log generation and data querying capabilities in enabling effective PM applications, thus enabling evidence-based improvements in healthcare processes.

Development of a SNOMED CT Mapping Process and Tool at a Data Integration Centre - Lessons Learned.

INTRODUCTION: 16 million German-language free-text laboratory test results are the basis of the daily diagnostic routine of 17 laboratories within the University Hospital Erlangen. As part of the Medical Informatics Initiative, the local data integration centre is responsible for the accessibility of routine care data for medical research. Following the core data set, international interoperability standards such as FHIR and the English-language medical terminology SNOMED CT are used to create harmonised data. To represent each non-numeric laboratory test result within the base module profile ObservationLab, the need for a map and supporting tooling arose. STATE OF THE ART: Due to the requirement of a n:n map and a data safety-compliant local instance, publicly available tools (e.g., SNAP2SNOMED) were insufficient. Concept and Implementation: Therefore, we developed (1) an incremental mapping-validation process with different iteration cycles and (2) a customised mapping tool via Microsoft Access. Time, labour, and cost efficiency played a decisive role. First iterations were used to define requirements (e.g., multiple user access). LESSONS LEARNED: The successful process and tool implementation and the described lessons learned (e.g., cheat sheet) will assist other German hospitals in creating local maps for inter-consortia data exchange and research. In the future, qualitative and quantitative analysis results will be published.

Nurses' acceptance of nursing information systems: A multi-center cross-sectional study in China.

BACKGROUND: In China, nursing information systems (NIS) implementation can face numerous barriers to acceptance, including the attitudes of potential users. However, few studies have evaluated this acceptance. OBJECTIVE: The aim of this study was to explain the acceptance of NIS utilizing a survey based on unified theory of acceptance and use of technology. METHODS: A multi-center cross-sectional study utilizing an online survey was conducted. SPSS AMOS was used to conduct a structural equation modelling analysis. This research followed the STROBE Checklist. RESULTS: A total of 3973 Nurses participated in the study between January 2023 and March 2023. The acceptance of NIS among nurses was overall moderate to high. The proposed model has been rigorously tested and validated using empirical data, ensuring its credibility and dependability. Performance expectancy (PE), social influence (SI), and attitude significantly and positively affected intentions to use NIS. Effort expectancy (EE) did not show any significant effects in the sample. Facilitating conditions (FCs) was found to have a negative relationship with the intention to use NIS. There was a statistically significant difference BI between the different age groups, working years, and computer training experience. The model demonstrates a good fit with the observed data. CONCLUSIONS: This study identified PE, SI, and attitude as facilitators of nurses' intentions to use NIS. The findings about EE indicates that the ease of using NIS does not seem to be a concern among nurses. Moreover, high FC might be perceived as indicative of a complex system or extensive usage, that can lead to increased workload and reduced behavioural intention (BI). The significant differences in BI among various demographic groups highlight the need for more studies understanding the preferences and barriers faced by different, levels of experience and training backgrounds. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

Spatiotemporal relationship between agriculture, livestock, deforestation, and visceral leishmaniasis in Brazilian legal Amazon.

Visceral leishmaniasis (VL) is an urgent public health concern in Brazil. We evaluated the spatiotemporal distribution of VL to better understand the effects of economic activities related to agriculture, livestock, and deforestation on its incidence in the Brazilian Legal Amazon (BLA). The data on newly confirmed cases of VL in Brazilian municipalities from 2007 to 2020 were extracted from the Brazilian Notifiable Diseases Information System (SINAN) and analyzed. The data on agricultural production (planted area in hectares) and livestock (total number of cattle) were obtained from the Brazilian Institute of Geography and Statistics (IBGE), whereas deforestation data (in hectares) were obtained from the Amazon Deforestation Estimation Project (PRODES). SatScan and the local indicators of spatial association (LISA) were used to identify the spatial and temporal patterns of VL and its relationships with economic and environmental variables. The cumulative incidence rate was found to be 4.5 cases per 100,000 inhabitants. Based on the LISA results, areas with a high incidence of VL and deforestation were identified in the states of Roraima, Pará, and Maranhão. Strengthening deforestation monitoring programs and environmental enforcement actions can help implement public policies to control illegal deforestation and mitigate the socio-environmental vulnerability in the BLA. Therefore, areas identified in this study should be prioritized for controlling VL.

Mapping eating disorders in adolescents and young adults: an investigation of geographic distribution and access to care in Ontario, Canada.

BACKGROUND: There is limited research on the spatial distribution of eating disorders and the proximity to available eating disorder services. Therefore, this study investigates the distribution of eating disorders among adolescents and young adults in Ontario, Canada, with a specific focus on geographic disparities and access to publicly-funded specialized eating disorder services. METHODS: A community sample of 1,377 adolescents and young adults ages 16-30 across Ontario between November and December 2021 participated in this study and completed the Eating Disorder Examination Questionnaire. Utilizing Geographic Information System (GIS) technology, we mapped the geographic prevalence of eating disorders and examined proximity to specialized eating disorder services. Multiple linear and logistic regression analyses were utilized to determine the association between geographic region and eating disorder symptomatology. Additionally, t-tests were utilized to examine differences between time/distance to specialized services and clinical risk for eating disorders. RESULTS: Applying geospatial analysis techniques, we detected significant spatial clusters denoting higher eating disorder scores in rural areas and areas with fewer specialized services. Likewise, our findings report disparities between rural and urban areas, suggesting that rural regions exhibit elevated rates of eating disorders. There were no associations between distance/time to services and eating disorder symptomology. CONCLUSIONS: The discrepancies in eating disorder symptomology between urban/rural may stem from stigma and unique socio-cultural contexts in rural communities. The study underscores the need for targeted intervention, including telehealth, in addressing the eating disorder challenges faced by adolescents and young adults in rural regions.

This study explores how common eating disorders are among adolescents and young adults in Ontario, Canada, with a specific focus on the geographic disparities of eating disorders. This study uses mapping technology to assess where eating disorders were more common and how close these areas were to specialized eating disorder treatment services. The findings showed that places with fewer services, especially rural areas, had higher rates of eating disorders. However, there wasn't a clear link between how far people lived from these services and the severity of their eating disorders. This may suggest that those in rural areas might struggle more with eating disorders due to greater stigma and different social and cultural factors compared to urban areas. This study emphasizes the need for targeted interventions, like telehealth, to address these disparities. This research is pivotal in guiding equitable healthcare solutions for eating disorders, particularly in underserved rural communities.

Geospatial Analysis of Parental Healthcare-Seeking Behavior in the Vicinity of Multispecialty Hospital in India.

Background and Objective: The healthcare-seeking behavior of vulnerable groups, such as children under five, depends on a multitude of factors, including the caregiver's decision making. Approximately 60% of Indians seek care from private hospitals. Recent health policy in India has favored the establishment of multispecialty hospitals. However, it remains unclear to what extent this policy has changed the number of Indians seeking healthcare from these government-established multispecialty hospitals. The study aims to assess the health-seeking behavior of parents of children under five in the vicinity of a public multispecialty tertiary care hospital. Methods: This was a community-based cross-sectional survey with geospatial mapping conducted among the parents of children under five using a semi-structured questionnaire in Epi-collect mobile app. The study site was an urban slum in a catchment area [within five kilometers (km)] of a multispecialty tertiary care public hospital in the central Indian state of Chhattisgarh. The study was conducted for one year duration from February 2019 to January 2020. A questionnaire was administered to the parents of the children under five (N = 353) after their household confirmation from the nearby Anganwadi center, the community level service providing center under the Integrated Child Development Scheme by the Ministry of Women and Child Development (WCD). The questionnaire included sections for demographic characteristics, the illness pattern among their children, health-seeking decision-making, and more. Descriptive analysis was presented with numbers and percentages. Univariate analysis was used to assess the association between sociodemographic variables and health-seeking characteristics. Statistical significance was considered at p value less than 0.05. We used geospatial mapping using coordinates collected and compiled using the Microsoft Excel version 2021 and analyzed using QGIS (Quantum Geographic Information System) software. Results: Among the parents interviewed patients (N = 353), maternal literacy rates were over 85%. Approximately 54% of the families were below poverty line. Among 95.2% of the families, mothers were part of decision-making regarding their children's health-seeking. Over 92% of the families opted for consultation in a nearby private hospital or dispensary. Geospatial mapping of private hospitals was a favored place for healthcare-seeking by mothers, irrespective of their socioeconomic status or education rather than multispecialty hospital. Conclusion and Global Health Implications: The majority of the parents in the vicinity of public multispecialty hospitals seek care from private clinics for ailments for children under five. The establishment of public multispecialty tertiary care hospitals, which are mandated for tertiary level of care and research, cannot replace primary-level healthcare institutions, showed that private hospitals were the favored places healthcare seeking by mothers. These primary-level institutions are critical for the management of common ailments for children under five near home and reducing the financial burden on the family, even in the vicinity of a multispecialty hospital.

Search for medical information for chronic rhinosinusitis through an artificial intelligence ChatBot.

Objectives: Artificial intelligence is evolving and significantly impacting health care, promising to transform access to medical information. With the rise of medical misinformation and frequent internet searches for health-related advice, there is a growing demand for reliable patient information. This study assesses the effectiveness of ChatGPT in providing information and treatment options for chronic rhinosinusitis (CRS). Methods: Six inputs were entered into ChatGPT regarding the definition, prevalence, causes, symptoms, treatment options, and postoperative complications of CRS. International Consensus Statement on Allergy and Rhinology guidelines for Rhinosinusitis was the gold standard for evaluating the answers. The inputs were categorized into three categories and Flesch-Kincaid readability, ANOVA and trend analysis tests were used to assess them. Results: Although some discrepancies were found regarding CRS, ChatGPT's answers were largely in line with existing literature. Mean Flesch Reading Ease, Flesch-Kincaid Grade Level and passive voice percentage were (40.7%, 12.15%, 22.5%) for basic information and prevalence category, (47.5%, 11.2%, 11.1%) for causes and symptoms category, (33.05%, 13.05%, 22.25%) for treatment and complications, and (40.42%, 12.13%, 18.62%) across all categories. ANOVA indicated no statistically significant differences in readability across the categories (p-values: Flesch Reading Ease = 0.385, Flesch-Kincaid Grade Level = 0.555, Passive Sentences = 0.601). Trend analysis revealed readability varied slightly, with a general increase in complexity. Conclusion: ChatGPT is a developing tool potentially useful for patients and medical professionals to access medical information. However, caution is advised as its answers may not be fully accurate compared to clinical guidelines or suitable for patients with varying educational backgrounds.Level of evidence: 4.

You cannot spell risk without "I-S": The disclosure of information systems risks by Fortune 1000 firms.

Cybersecurity events can cause business disruptions, health and safety repercussions, financial costs, and negative publicity for large firms, and executives rank cybersecurity as a top operational concern. Although cybersecurity may be the most publicized information systems (IS) risk, large firms face a range of IS risks. Over the past three decades, researchers developed frameworks to categorize and evaluate IS risks. However, there have been few updates to these frameworks despite numerous technological advances, and we are not aware of any research that uses empirical data to map actual IS risks cited by large firms to these frameworks. To address this gap, we coded and analyzed text data from Item 1A (Risk Factors) of the fiscal year 2020 Securities and Exchange Commission Forms 10-K for all Fortune 1000 firms. We build on prior research to develop a framework that places 25 IS risks into four quadrants and 10 categories, and we record the number and type of IS risks cited by each firm. The risk of cyberattack is cited by virtually all Fortune 1000 firms, and the risk of software/hardware failure is cited by 90% of Fortune 1000 firms. Risks associated with data privacy law compliance are cited by 70% of Fortune 1000 firms, and risks associated with internet/telecommunications/power outage, human error, and natural disasters/terrorism are cited by 60% of Fortune 1000 firms. We perform additional analysis to identify differences in risk citation based on industry and financial measures.

Mapping the evaluation of the electronic health system PEC e-SUS APS in Brazil: a scoping review protocol.

BACKGROUND: The Brazilian Ministry of Health has developed and provided the Citizen's Electronic Health Record (PEC e-SUS APS), a health information system freely available for utilization by all municipalities. Given the substantial financial investment being made to enhance the quality of health services in the country, it is crucial to understand how users evaluate this product. Consequently, this scoping review aims to map studies that have evaluated the PEC e-SUS APS. METHODS: This scoping review is guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) framework, as well as by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Checklist extension for scoping reviews (PRISMA-ScR). The research question was framed based on the "CoCoPop" mnemonic (Condition, Context, Population). The final question posed is, "How has the Citizen's Electronic Health Record (PEC e-SUS APS) been evaluated?" The search strategy will be executed across various databases (LILACS, PubMed/MEDLINE, Scopus, Web of Science, ACM Digital Library, and IEEE Digital Library), along with gray literature from ProQuest Dissertation and Theses Global and Google Scholar, with assistance from a professional healthcare librarian skilled in supporting systematic reviews. The database search will encompass the period from 2013 to 2024. Articles included will be selected by three independent reviewers in two stages, and the findings will undergo a descriptive analysis and synthesis following a "narrative review" approach. Independent reviewers will chart the data as outlined in the literature. DISCUSSION: The implementation process for the PEC e-SUS APS can be influenced by the varying characteristics of the over 5500 Brazilian municipalities. These factors and other challenges encountered by health professionals and managers may prove pivotal for a municipality's adoption of the PEC e-SUS APS system. With the literature mapping to be obtained from this review, vital insights into how users have evaluated the PEC will be obtained. SYSTEMATIC REVIEW REGISTRATION: The protocol has been registered prospectively at the Open Science Framework platform under the number 10.17605/OSF.IO/NPKRU.

Towards digital readiness of evidence-based practice in a regional cancer center using role-based business process and data modeling.

Introduction: Evidence-based practice is a problem-based solving approach to clinical practice that encourages nurses providing personalized patient care while utilizing the necessary scientific evidence for a better understanding of risks and benefits of diagnostic tests and treatments. Digital transformation of an organization begins with attaining an acceptable digital readiness level. One approach entails specifying and modeling their processes and the respective data models. Objectives: In Jordan, at King Hussein Cancer Center-an international and regional accredited cancer care hospital-their nursing practice requires obtaining a standardized specification of evidence-based practice processes and their respective conceptual data model that is currently not specified for digital readiness. Methods: The design science research methodology was adopted to deliver two increments. The first was concerned with the design, development, and demonstration of eight evidence-based practice processes specified using BPMN. The second was related to the design and development, demonstration, and evaluation of a respective derived data model of the case study. Both increments involved interviews with domain experts for elicitation and validation. Results: Eight evidence-based practice process models were identified and specified using BPMN along with their associated data models, where one representative process model was utilized in this research to demonstrate the effectiveness of process and data modeling towards digital readiness of evidence-based practice in regional cancer center. Conclusions: Both deliverables enabled the evidence-based practice management to attain common understanding to identify inefficiencies, redundancies, and areas for improvement that can be addressed through digital solutions. Evidence -based practice BPMN process models were considered as a road map to follow up a project implementation and a rich visualization to perform data analytics to identify evidence-based practice trends, patterns, and insights that can inform strategic data-driven decisions. Both deliverables were concluded necessary for developing respective information systems in the journey towards digital transformation.

System interoperability and data linkage in the era of health information management: A bibliometric analysis.

Background: Across the world, health data generation is growing exponentially. The continuous rise of new and diversified technology to obtain and handle health data places health information management and governance under pressure. Lack of data linkage and interoperability between systems undermines best efforts to optimise integrated health information technology solutions. Objective: This research aimed to provide a bibliometric overview of the role of interoperability and linkage in health data management and governance. Method: Data were acquired by entering selected search queries into Google Scholar, PubMed, and Web of Science databases and bibliometric data obtained were then imported to Endnote and checked for duplicates. The refined data were exported to Excel, where several levels of filtration were applied to obtain the final sample. These sample data were analysed using Microsoft Excel (Microsoft Corporation, Washington, USA), WORDSTAT (Provalis Research, Montreal, Canada) and VOSviewer software (Leiden University, Leiden, Netherlands). Results: The literature sample was retrieved from 3799 unique results and consisted of 63 articles, present in 45 different publications, both evaluated by two specific in-house global impact rankings. Through VOSviewer, three main clusters were identified: (i) e-health information stakeholder needs; (ii) e-health information quality assessment; and (iii) e-health information technological governance trends. A residual correlation between interoperability and linkage studies in the sample was also found. Conclusion: Assessing stakeholders' needs is crucial for establishing an efficient and effective health information system. Further and diversified research is needed to assess the integrated placement of interoperability and linkage in health information management and governance. Implications: This research has provided valuable managerial and theoretical contributions to optimise system interoperability and data linkage within health information research and information technology solutions.

[Geriatric assessment goes digital-Possible applications in the emergency department setting]. / Geriatrisches Assessment goes digital ­ Einsatzmöglichkeiten im Setting der Notaufnahme.

The geriatric assessment is a basic requirement and a key quality parameter in geriatric care. An increasing number of older patients are presenting to emergency or central admission departments and discharge units in hospitals. For this reason, and in view of the time-critical decision-making requirements in this setting, digital applications of basic geriatric assessment data are becoming increasingly more important for the high-quality follow-up care of geriatric patients.