Information Management System Research Articles

Design and Implementation of an SGX Based Electricity Information Collection and Management System

With the rapid growth of the number and scale of smart grid users, traditional data encryption transmission methods can no longer meet the performance requirements of data aggregation. In response, a power consumption information collection and management system based on SGX software protection extension is proposed. The system mainly consists of three parts: user electricity data acquisition terminal, SGX data security processing and distributed storage module on the chain, and data monitoring management display platform. The user electricity data collection terminal collects electricity data from various buildings, residences, rooms, and other smart meters, analyzes and uploads it. After calling the trusted function of SGX technology, it enters the security zone provided by SGX for data processing. Finally, the data security processing results and data are uploaded to the blockchain for storage. In order to visually display user electricity usage data, an intelligent monitoring platform for user electricity collection and management has been established. This system can reduce the workload of user electricity data collection, ensure the accuracy of data collection, and provide an efficient and highly reliable system platform for user electricity data management.

Methodology for Ensuring the Viability for a Complex Object Based on Managing its Structural Dynamics

   The article examines a conceptual model that forms the basis of the authors’ proposed approach to solving the problem of creating integrated information-management systems (IMS) for making managerial decisions, embedded within the structure of vertically integrated Business Entity (BE) to maintain their viability. Viability is understood as the ability of an BE to maintain key technological and business indicators within safe ranges throughout its life cycle (LC), while being subject to the influence of destructive internal and external factors. The problem of synthesizing a generalized structure of an IMS is proposed to solve using a system-cybernetic approach, which considers this problem as the managing its structural dynamics. Managing structural dynamics enables maintaining a regulated level of viability of the vertically integrated BE at all the key stages of its life cycle. The proposed structure of model-algorithmic support (MAS) implements the methods for complexity management. This methodology proposes the approach that justifies the evolutionary redistribution of roles between managerial teams of the vertically integrated BE and functionally equivalent information-management systems. The results of implementing the structure of an IMS, as an example are provided, which arises through the transformation of its original multi-structural state into a qualitatively different state. Multi-structural states are characterized by the use of various control methods, such as "Automatic Multi-Factor", "Automatic Optimal" "Manual on site" etc. In the synthesis of the IMS structure, the methods for system modeling technologies based on simulation-statistical and fuzzy-possibilistic approaches were used.

Research on Pathology Information Management of Educational Architectural Heritage Based on Digital Technology: The Case of James Jackson Gymnasium

Rapid advances in technology have led to an increasing demand for this type of information in the field of cultural heritage and architectural conservation. The article aims to use digital technology to obtain, record, store, and display accurate and intuitive information about architectural heritage for daily management and repair of that heritage. This article conducts a comprehensive and in-depth study of the pathology information from the James Jackson Gymnasium, a typical case of the modern educational architectural heritage of Wuhan. Research contents include obtaining point cloud data through 3D scanning, constructing Building Information Modeling (BIM) 3D models and pathological information models to visualize the affected parts, using the Monument Damage Diagnostic System (MDDS) to establish a pathological information map management system, using virtual simulation technology and digital repair technology to diagnose and repair the affected parts, and establishing a systematic architectural pathology information database to explore the causes of architectural pathology from a multidisciplinary perspective. The authors aim to gradually promote this method and build a systematic pathological information database of architectural heritage. This utilizes the sharing characteristics of information technology to transcend the barriers of time and space and provide important support for heritage protection and pathology management. The Architectural Pathology Information Management System is proposed as an innovative solution to promote the sustainable conservation of architectural heritage through digital technology.

Modelling spatiotemporal variation in under-five malaria risk in Ghana in 2016–2021

BackgroundGhana is among the top 10 highest malaria burden countries, with about 20,000 children dying annually, 25% of which were under five years. This study aimed to produce interactive web-based disease spatial maps and identify the high-burden malaria districts in Ghana.MethodsThe study used 2016–2021 data extracted from the routine health service nationally representative and comprehensive District Health Information Management System II (DHIMS2) implemented by the Ghana Health Service. Bayesian geospatial modelling and interactive web-based spatial disease mapping methods were employed to quantify spatial variations and clustering in malaria risk across 260 districts. For each district, the study simultaneously mapped the observed malaria counts, district name, standardized incidence rate, and predicted relative risk and their associated standard errors using interactive web-based visualization methods.ResultsA total of 32,659,240 malaria cases were reported among children < 5 years from 2016 to 2021. For every 10% increase in the number of children, malaria risk increased by 0.039 (log-mean 0.95, 95% credible interval = − 13.82–15.73) and for every 10% increase in the number of males, malaria risk decreased by 0.075, albeit not statistically significant (log-mean − 1.82, 95% credible interval = − 16.59–12.95). The study found substantial spatial and temporal differences in malaria risk across the 260 districts. The predicted national relative risk was 1.25 (95% credible interval = 1.23, 1.27). The malaria risk is relatively the same over the entire year. However, a slightly higher relative risk was recorded in 2019 while in 2021, residing in Keta, Abuakwa South, Jomoro, Ahafo Ano South East, Tain, Nanumba North, and Tatale Sanguli districts was associated with the highest malaria risk ranging from a relative risk of 3.00 to 4.83. The district-level spatial patterns of malaria risks changed over time.ConclusionThis study identified high malaria risk districts in Ghana where urgent and targeted control efforts are required. Noticeable changes were also observed in malaria risk for certain districts over some periods in the study. The findings provide an effective, actionable tool to arm policymakers and programme managers in their efforts to reduce malaria risk and its associated morbidity and mortality in line with the Sustainable Development Goals (SDG) 3.2 for limited public health resource settings, where universal intervention across all districts is practically impossible.

Analysis on time delay of tuberculosis among adolescents and young adults in Eastern China

BackgroundTuberculosis (TB) is recognized as a significant global public health concern. Still, there remains a dearth of comprehensive evaluation regarding the specific indicators and their influencing factors of delay for adolescents and young adults.MethodsAll notified pulmonary TB (PTB) patients in Jiaxing City were collected between 2005 and 2022 from China’s TB Information Management System. Logistic regression models were conducted to ascertain the factors that influenced patient and health system delays for PTB cases, respectively. Furthermore, the impact of the COVID-19 pandemic on local delays has been explored.ResultsFrom January 1, 2005 to December 31, 2022, a total of 5,282 PTB cases were notified in Jiaxing City, including 1,678 adolescents and 3,604 young adults. For patient delay, female (AOR: 1.18, 95%CI: 1.05–1.32), PTB complicated with extra-pulmonary TB (AOR: 1.70, 95% CI: 1.28–2.26), passive case finding (AOR: 1.46, 95% CI: 1.07–1.98) and retreatment (AOR: 1.52, 95% CI: 1.11–2.09) showed a higher risk of delay. For health system delay, minorities (AOR: 0.69, 95% CI: 0.53–0.90) and non-students (AOR: 0.83, 95% CI: 0.71–0.98) experienced a lower delay. Referral (AOR: 1.46, 95% CI: 1.29–1.65) had a higher health system delay compared with clinical consultation. Furthermore, county hospitals (AOR: 1.47, 95% CI: 1.32–1.65) and etiological positive results (AOR: 1.46, 95% CI: 1.30–1.63) were associated with comparatively high odds of patient delay. Contrarily, county hospitals (AOR: 0.88, 95% CI: 0.78–1.00) and etiological positive results (AOR: 0.67, 95% CI: 0.59–0.74) experienced a lower health system delay. Besides, the median of patient delay, health system delay, and total delay during the COVID-19 pandemic were significantly lower than that before.ConclusionIn general, there has been a noteworthy decline in the notification rate of PTB among adolescents and young adults in Jiaxing City while the declining trend was not obvious in patient delay, health system delay, and total delay, respectively. It also found factors such as gender, case-finding method, and the hospital level might influence the times of seeking health care and diagnosis in health agencies. These findings will provide valuable insights for refining preventive and treatment strategies for TB among adolescents and young adults.

The Red Cross Red Crescent Health Information System (RCHIS): an electronic medical records and health information management system for the red cross red crescent emergency response units

BackgroundThe Red Cross and Red Crescent Movement (RCRC) utilizes specialized Emergency Response Units (ERUs) for international disaster response. However, data collection and reporting within ERUs have been time-consuming and paper-based. The Red Cross Red Crescent Health Information System (RCHIS) was developed to improve clinical documentation and reporting, ensuring accuracy and ease of use while increasing compliance with reporting standards.Case presentationRCHIS is an Electronic Medical Record (EMR) and Health Information System (HIS) designed for RCRC ERUs. It can be accessed on Android tablets or Windows laptops, both online and offline. The system securely stores data on Microsoft Azure cloud, with synchronization facilitated through a local ERU server. The functional architecture covers all clinical functions of ERU clinics and hospitals, incorporating user-friendly features. A pilot study was conducted with the Portuguese Red Cross (PRC) during a large-scale event. Thirteen super users were trained and subsequently trained the staff. During the four-day pilot, 77 user accounts were created, and 243 patient files were documented. Feedback indicated that RCHIS was easy to use, requiring minimal training time, and had sufficient training for full utilization. Real-time reporting facilitated coordination with the civil defense authority.ConclusionsThe development and pilot use of RCHIS demonstrated its feasibility and efficacy within RCRC ERUs. The system addressed the need for an EMR and HIS solution, enabling comprehensive clinical documentation and supporting administrative reporting functions. The pilot study validated the training of trainers’ approach and paved the way for further domestic use of RCHIS. RCHIS has the potential to improve patient safety, quality of care, and reporting efficiency within ERUs. Automated reporting reduces the burden on ERU leadership, while electronic compilation enhances record completeness and correctness. Ongoing feedback collection and feature development continue to enhance RCHIS’s functionality. Further trainings took place in 2023 and preparations for international deployments are under way. RCHIS represents a significant step toward improved emergency medical care and coordination within the RCRC and has implications for similar systems in other Emergency Medical Teams.

Empowering Innovation in Banking Insurance: Expert System for Information Management

Background Nowadays, financial institutions face and solve challenges to optimise Information Management (IM), so the use of new technologies such as Expert Systems (ES) is indispensable. Therefore, the objective of this research is to implement an ES to improve IM in insurance companies. Method In terms of approach, the agile methodology SCRUM was chosen, which consists of five phases: initiation, planning and estimation, implementation, review and retrospective, launch, and thus decision making and optimisation of the IM process. In addition, the following technologies were chosen: ASP.NET as programming language, HTML as markup language, SQL Server as database management and CSS for design and visual styling. Results The results also showed a significant increase of 35% in user service, accompanied by a significant improvement of 44% in report delivery. Finally, a significant improvement of 24% was observed following the implementation of the expert system. This streamlines processes, reduces waiting times, improves the user experience in real time and optimises the management of large volumes of data in the insurance company. Conclusions The system demonstrated that this tool improves decision making, reduces errors in the issuing area and provides a user-friendly interface for information management.

Role of Artificial Intelligence in Developing Hospital Information Management Systems

Hospital information management systems (HIMS) play significant roles in improving clients' health by applying developed technologies, one of which is artificial intelligence (AI). This study aims to explore the roles of AI in order to support the development of HIMS. We conducted a literature review by extracting the articles from PubMed, ProQuest, and Google Scholar in the past 5 years (January 2019-August 2023) using specific keywords. The full text of relevant articles then thematically synthesized and to be presented. Our findings revealed eight themes that represent the role of AI in supporting the hospital information management system and its implementation in healthcare settings. The themes identified include Diagnosis and Medical Imaging, Health Data Management, Risks Prediction and Disease Progression, Inventory and Procurement Management, Telemedicine and Remote Consultation, Patient Care Management, Drug Development and Clinical Research, and Hospital Data Security System. The AI implementation brings the potential to improve efficiency, accuracy, and quality of care in hospitals. However, it should be noted that the development and implementation of AI need to consider the ethical aspects and proper integration through existing health systems.

Mortality in patients admitted to hospital with heart failure in China: a nationwide Cardiovascular Association Database-Heart Failure Centre Registry cohort study

China has the largest burden of heart failure worldwide. However, large-scale studies on heart failure mortality are scarce. We aimed to investigate mortality and identify risk factors for mortality among patients with heart failure in China. This prospective cohort study used data from the China Cardiovascular Association (CCA) Database-Heart Failure Centre Registry, which were linked to the National Mortality Registration Information Management System by the Chinese Centre for Disease Control and Prevention. We included patients enrolled from Jan 1, 2017, to Dec 31, 2021, across 572 CCA Database-Heart Failure Centre certified hospitals in 31 provinces of mainland China. Eligible patients were aged 18 years or older (younger than 100 years) with a principal discharge diagnosis of heart failure based on Chinese heart failure guidelines. All-cause mortality at 30 days, 1 year, and 3 years for patients with heart failure were calculated and the causes of death were recorded. Multivariable analysis was used to analyse factors associated with all-cause mortality and cardiovascular mortality. This study was registered with the Chinese Clinical Trial Registry, ChiCTR2200066305. Of the 327 477 patients in the registry, 230 637 eligible adults with heart failure were included in our analyses. Participant mean age was 69·3 years (SD 13·2), 94 693 (41·1%) participants were female, and 135 944 (58·9%) were male. The median follow-up time was 531 days (IQR 251-883). Post-discharge all-cause mortality of patients with heart failure at 30 days was 2·4% (95% CI 2·3-2·5), at 1 year was 13·7% (13·5-13·9), and at 3 years was 28·2% (27·7-28·6). Cardiovascular death accounted for 32 906 (71·5%) of 46 006 all-cause deaths. Patients with heart failure with reduced ejection fraction had the highest all-cause mortality. A lower guideline adherence score was independently associated with the increase of all-cause and cardiovascular mortality. In China, mortality for patients with heart failure is still high, especially in patients with reduced ejection fraction. Our findings suggest that guideline-directed medical therapy needs to be improved. National High Level Hospital Clinical Research Funding, the Capital's Funds for Health Improvement and Research, and the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences. For the Chinese translation of the abstract see Supplementary Materials section.

Cybersecurity on a budget: Evaluating security and performance of open-source SIEM solutions for SMEs.

The proliferation of cyber threats necessitates robust security measures to safeguard critical assets and data in today's evolving digital landscape. Small and Medium Enterprises (SMEs), which are the backbone of the global economy are particularly vulnerable to these threats due to inadequate protection for critical and sensitive information, budgetary constraints, and lack of cybersecurity expertise and personnel. Security Information and Event Management (SIEM) systems have emerged as pivotal tools for monitoring, detecting, and responding to security incidents. While proprietary SIEM solutions have historically dominated the market, open-source SIEM systems have gained prominence for their accessibility and cost-effectiveness for SMEs. This article presents a comprehensive study focusing on the evaluation of open-source SIEM systems. The research investigates the capabilities of these open-source solutions in addressing modern security challenges and compliance with regulatory requirements. Performance aspects are explored through empirical testing in simulated enterprise-grade SME network environments to assess resource utilization, and real-time data processing capabilities. By providing a rigorous assessment of the security and performance features of open-source SIEM systems, this research offers valuable insights to cybersecurity practitioners, organizations seeking cost-effective security solutions, and the broader academic community. The findings shed light on the strengths and limitations of these systems, aiding decision-makers in selecting the most suitable SIEM solution for their specific requirements while enhancing the cybersecurity posture of SMEs.

Surveillance for adverse events following immunization with DTaP-containing combination vaccines in Linping, China, 2019-2022.

The DTaP-Hib and DTaP-IPV/Hib combination vaccine can be used as a substitute for the diphtheria, tetanus, and acellular pertussis combined vaccine (DTaP). We aimed to evaluate the safety of multi-component vaccines containing DTaP by analyzing the reporting rates and characteristics of adverse events following immunization (AEFIs) in Linping District during the years 2019 to 2022. We obtained data of AEFI and vaccination from the National AEFI Surveillance System of China and Zhejiang Municipal Immunization Information Management System, respectively, during 2019-2022 for a descriptive, epidemiological analysis. The total number of AEFI reported following vaccinations with DTaP-containing combination vaccines was 802 in Linping District from 2019 to 2022. The overall reporting rates of AEFIs following DTaP, DTaP-Hib, and DTaP-IPV/Hib vaccinations were 445.72 (537 cases), 536.29 (45 cases), and 306.13 (220 cases) per 100,000 doses in Linping District from 2019 to 2022, respectively. Only one case of a serious AEFI following DTaP vaccination, with a reporting rate of 0.83 per 100,000 doses. The composition ratio of vaccine product-related reactions for DTaP, DTaP-Hib, and DTaP-IPV/Hib were 99.81, 97.78, and 100.00%, respectively. The composition ratio of coincidental events for DTaP and DTaP-Hib were 0.19 and 2.22%, respectively. The reporting rates of total AEFIs for DTaP-IPV/Hib were lower than for DTaP. The reporting rate of local induration for DTaP-Hib was lower than for DTaP, and the reporting rates of local redness & swelling and local induration for DTaP-IPV/Hib were both lower than for DTaP. DTaP-IPV/Hib had a higher proportion of AEFIs in first quarter compared to DTaP. The reporting rate after the second dose of DTaP-Hib was higher than that of DTaP, and the reporting rates of AEFIs after the first dose and third dose of DTaP-IPV/Hib were lower than DTaP. The reported AEFIs to multi-component vaccines containing DTaP components during 2019-2022 in Linping District were mainly mild vaccine reactions. DTaP-containing combination vaccines demonstrated a good safety profile.

Application of artificial intelligence technology in hospital management systems

This article explores the application of artificial intelligence technology in hospital management systems, specifically using the innovative work order project as an example. The system can interact with users through intelligent AI interaction through text and voice, enabling intelligent work order repair and query processing. The project includes multiple functions such as work order form generation, attachment uploading, voice file uploading, work order query, and interface docking. In addition, this article also introduces the requirements for integrating hospital logistics business with Turing CHATGPT application scenarios, including equipment failure repair, patient satisfaction surveys, patient follow-ups, and medical staff training and learning. Through detailed descriptions of interface docking, data flow, and functions, this article highlights the potential of AI technology to enhance work efficiency and user experience in hospital management systems. Finally, this article discusses the current achievements and future development directions and calls for further innovation and progress in medical information management systems.

Retraction Note: Optimization design and implementation of shared information management system for industrial design network platform

Retraction Note: Optimization design and implementation of shared information management system for industrial design network platform

Electronic Health Record Adoption in Oral and Dental Health Centres in Turkey

The digitalisation studies in public hospitals in Turkey started with the Health Transformation Program in 2003. The Ministry of Health has been measuring the dissemination of meaningful usage and adoption of electronic health record (EHR) using Electronic Medical Record Adoption Model (EMRAM) and Outpatient Electronic Medical Record Adoption Model (O-EMRAM). Using a comprehensive survey, our study intends to measure the stage of EHR adoption in oral and dental health centres (ODHCs) providing primary healthcare services in Turkey. The results obtained were classified by basic and comprehensive EHR functions and benchmarked against the studies addressing EHR adoption in primary healthcare institutions of other countries. In 2021, 167 ODHCs/oral and dental health hospitals (ODHHs) actively operating in Turkey completed the O-EMRAM survey. The data obtained from the survey results were analysed with QlikView Personal Edition. The availability and prevalence of medical information systems and EHR functions and their use were measured. It is observed that 59 (40.7%) of ODHCs/ODHHs have comprehensive EHR functions, while the remaining 86 (59.3%) have basic EHR functions. Under these circumstances, it can be stated that all ODHCs/ODHHs in Turkey use at least basic EHR functions. All ODHCs/ODHHs in Turkey have at least basic EHR functions. The integration of e-prescription, electronic authorisation system and e-Pulse used throughout Turkey and Health Information Management System Society (HIMSS) used in ODHCs/ODHHs can be listed as one of the decisive factors in this result. ODHCs/ODHHs still have a long way to go in adopting EHR, but the current circumstances are also promising. It is considered that this study will serve as a baseline for future measurements and produce a notable result for decision-makers.

Abstract 4427: Do changes in lipid metabolism link obesity to pancreatic cancer

Abstract The near equal incidence and mortality rates of pancreatic cancer, combined with projections that pancreatic cancer will become the second-most common cancer-related deaths by 2050, underscore the need to identify patients with early disease and interrupt this trajectory. Obesity, weight gain and waistline have been implicated in increasing the risk of pancreatic cancer. Although metabolomic analyses of pancreatic cancer patients have established correlations between phospholipids, lysophospholipids with treatment outcomes, the association between metabolites, obesity, and pancreatic cancer remains largely understudied. The objective of this pilot study was to determine differences in serum metabolites in obese and overweight pancreatic cancer patients compared with healthy non-obese subjects. Our long-term goal is to develop serum marker(s) that may be used to prevent advanced pancreatic cancer and thus improve outcomes for these patients. Serum was obtained from healthy subjects (n=11; BMI range from 18-25), overweight (n=9; 25-30) and obese (n=7; &amp;gt;30) pancreatic cancer patients from an IRB approved study. Males (n=12) and females (n=15) were represented in the study. Global metabolic profiles were determined using Ultrahigh performance liquid chromatography-tandem mass spectroscopy. Raw data was extracted, peaks were identified and processed at Metabolon using the Laboratory Information Management System. Comparison between overweight pancreatic cancer patients and healthy controls identified 403 biochemicals (111 upregulated and 292 downregulated; p &amp;lt;0.05) and 93 biochemicals (40 upregulated and 53 downregulated; 0.05&amp;lt;p&amp;lt;0.10). Comparison of the differences in biochemicals between obese pancreatic cancer patients and healthy controls showed changes in 293 biochemicals (71 upregulated and 222 downregulated; p &amp;lt;0.05) and 123 biochemical changes at 0.05&amp;lt;p&amp;lt;0.10 (42 increased and 81 decreased). 38 (p &amp;lt;0.05) and 47 (0.05&amp;lt;p&amp;lt;0.10) differential levels of biochemicals were identified when obese and overweight pancreatic cancer patients were compared. Random forest analysis showed that the 30 top ranking biochemicals were involved in lipid metabolism, amino acid metabolism, nucleotide metabolism, peptide, xenobiotics, and carbohydrate metabolism. These data suggest an association between changes in lipid metabolism may be another link between obesity and pancreatic cancer. This project was funded in part by VA-Merit Award (I01 BX003876). Citation Format: Rita Ghosh, Deepa Ajit, Jillian Woodworth, Danielle Fritze, Francisco G. Cigarroa, Glenn A. Halff, Addanki Pratap Kumar. Do changes in lipid metabolism link obesity to pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4427.

Abstract 6104: EDRN Lung Team Project 2 validation of molecular biomarkers for the early detection of lung cancer in the setting of indeterminate pulmonary nodules

Abstract Background: The goal of the Early Detection Research Network (EDRN) Lung Team Project #2 (LTP-2) is to establish a cohort (n= 300) of high-risk people with indeterminate pulmonary nodules (6mm-30mm) to clinically validate the diagnostic accuracy of existing molecular and imaging biomarkers discovered and analytically validated through the EDRN program. These biomarkers comprise signals measured in serum (glycan or cytokine), plasma (protein, miRNA, RNA, or methylated circulating tumor DNA), airway epithelial cells (RNA or DNA), nasal brush cells (RNA or DNA), and/or chest CT images. Methods: Eligible participants had an indeterminate nodule discovered incidentally or through low-dose CT screening within 14 months prior to enrollment and were aged 45-90 years, with 20 pack-years or more cigarette smoking history, free of lung cancer, and willing to provide blood, nasal brushing, and optionally bronchoscopic brush biopsy specimens. Baseline medical and demographic data were collected from each subject. Baseline and years 1 and 2 follow-up CT images were obtained. Each specimen at each respective site was labeled with a 2-D barcode provided by the DMCC and specimen information was entered into the Validation Study Information Management System (VSIMS) developed by the EDRN Data Management and Coordinating Center (DMCC). Aliquots of blinded specimens from selected cases and controls will be dispensed to each EDRN site for biomarker analysis. Analysis plan: Primary endpoint: The positive diagnostic likelihood ratio (DLR+) will be used to measure biomarker performance within values of DLR+ &amp;gt;= 2 or DLR- &amp;lt;= 0.5, a range considered clinically useful for any patients with indeterminate lung nodules. The sample size calculation targeted &amp;gt;80% power to test the null hypotheses that a) a positive biomarker does not alter risk across a range of specificities, and b) a negative biomarker does not alter risk across a range of sensitivities. The EDRN Data Management and Coordinating Center (DMCC) will unblind and complete analysis and report results. Exploratory endpoint: The diagnostic accuracy of combined biomarkers will be calculated using a logistic regression model with flexible functional forms. Results and Discussion: More than 300 subjects were enrolled into the LTP2 cohort including a sufficient number of cases and controls (cohort size n&amp;gt;300) to reach power according to calculated estimates. Chest CT images were collected and are in the process of transfer to a central database. Plasma specimens have been distributed to test sites. RNA and DNA extraction from NBC and AEC is in process and based on results thus far the specimen quality and quantity is more than sufficient from the number of subjects needed to reach power for the primary endpoint and to conduct the planned exploratory analyses. Citation Format: James C. Willey, Eric L. Grogan, Stephen A. Deppen, James G. Herman, Michael N. Kammer, Matthew B. Schabath, Lynn Sorbara, Harvey I. Pass, Jun-Chieh J. Tsay, Ziding Feng, Avrum Spira, Erin L. Crawford, Jackie Dahlgren, Steven M. Dubinett, Kimberly R. Rieger-Christ, Marc E. Lenburg. EDRN Lung Team Project 2 validation of molecular biomarkers for the early detection of lung cancer in the setting of indeterminate pulmonary nodules [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6104.

Organizational And Social Technologies For Early Cancer Detection Among General Population

In this review, organizational technologies for early cancer detection including screening programs and patient information management systems are discussed. An analysis of social technologies applied to early cancer detection is carried out, and the role of modern information technologies in cancer control management is discussed. The purpose of the study was to review and analyze existing organizational and social technologies used for early cancer detection, as well as for effectiveness evaluation.

Commercialisation dynamics system principles and support units of entrepreneurial universities

Background: The Fourth Industrial Revolution has given rise to the demand for universities to produce knowledge and innovation. Universities play a significant role in equipping students with skills and knowledge conducive for commercialisation of innovation (CoI). This investigation addressed the commercialisation dynamics research gap of entrepreneurial universities.Objectives: To investigate commercialisation dynamics of a strategic information management (SIM) system to facilitate the CoI process of an entrepreneurial university.Method: This paper presents the qualitative component of a larger mixed method complex action research strategy. Data were collected through an in-depth face-to-face interview and analysed through descriptive content analysis.Results: The results highlight successful CoI practices fulfilled through the signification framework for the SIM system for commercialisation dynamics of entrepreneurial universities. The system is based on various components deemed suitable for commercialisation.Conclusion: This study has the potential to guide the University of Johannesburg (UJ), as well as other higher education institutions (HEIs) and institutions involved in entrepreneurship, innovation, and commercialisation, in creating an entrepreneurial environment for their innovators. Furthermore, this study can guide students, entrepreneurs, inventors, and innovators in terms of the process to follow to commercialise their business ideas, inventions, and innovation.Contribution: The SIM system incorporates dynamic system principles with intervention benchmarks and has intervention keys that will provide innovators with the safety net that will assist them in converting their ideas into commercialised products and services.

The Regulatory Affairs Automation tools used in the Pharmaceutical Industry: An overview

Automation is becoming increasingly prevalent in various industries, including healthcare and pharmaceuticals. The pharmaceutical business is influenced by a variety of worldwide trends, with one of the most significant being the use of automation technologies, which will have a transformative effect on the research and development of new pharmaceutical products as well as the speed and efficiency with which products reach patients in need. Regulatory automation is enabled by a variety of technology tools, such as Electronic Document Management Systems, Regulatory Information Management (RIM) Systems, Artificial Intelligence (AI) Analytics Tools, Natural Language Processing (NLP) Tools, and Submission Publishing Tools. Automation tools can be used to automate regulatory activities such as administrative work, dossier completion, data extraction, auditing, regulatory implementation as well as quality management. Automation tools establish process links and minimize complexity, resulting in a more efficient management system. Human-AI interaction creates new prospects in regulatory concerns. This article investigates the potential use of automation techniques in pharmaceutical regulatory concerns.

Infectious causes and outcomes of patients with high fever in the emergency department

Aims: The aim of this study is to investigate the reasons for presentation, diagnoses, and outcomes of patients with high fever in the emergency department. Methods: This research is a retrospective study planned by examining the files and data of patients who presented to the emergency department between 01.03.2021 and 01.03.2023, and whose body temperature was above 38 degrees Celsius. Patient data was analyzed from patient files and the Hospital Information Management System (HIMS). The demographic characteristics, vital signs at admission, reasons for presentation, diagnoses, and outcomes of patients with complete data from patient files and HIMS were investigated. Results: Of the 288 patients included in the study, 151 (52.4%) were male, and the mean age was 47.04 ± 18.75. When examining the reasons for patients' presentation to the emergency department, 79 (27.4%) patients presented with sore throat, and 44 (15.3%) patients presented with fever. When examining the final diagnoses of patients, acute tonsillopharyngitis was the most common diagnosis with 99 (34.4%) patients, followed by 30 (10.4%) patients with Covid-19. Regarding the outcomes of patients, 190 (66%) patients were discharged from the emergency department, 63 (21.9%) were admitted to the ward, and 26 (9%) were admitted to the intensive care unit. Conclusion: Cases with high fever in the emergency department encompass a wide range of conditions, ranging from mild viral upper respiratory tract infections to potentially fatal infections such as meningoencephalitis and myocarditis. Therefore, in febrile cases in the emergency department, serious infectious causes should be considered in terms of the focus of fever. Additionally, non-infectious causes should also be kept in mind as they can cause high fever.