bluuebunny/crossref_metadata_2025 huggingface dataset:
Pros and Cons of Clinical Pathway Software Management: A Qualitative Study
Authors: Aarnoutse M.F.  , Brinkkemper S.  , de Mul M.  , Askari M.
Published: February 2025

In this study we aimed to assess the perceived effectiveness of clinical pathway management software for healthcare professionals. A case study on the clinical pathway management software program Check-It was performed in three departments at an academic medical center. Four months after the implementation of the software, interviews were held with healthcare professionals who work with the system. The interview questions were posed in a semi-structured interview format and the participant were asked about the perceived positive or negative effects of Check-It, and whether they thought the software is effective for them. The interviews were recorded and transcribed based on grounded theory, using different coding techniques. Our results showed fewer overlooked tasks, pre-filled orders and letters, better overview, and increased protocol insight as positive aspects of using the software. Being not flexible enough was experienced as a negative aspect.
TASoMe: Validating a Framework to Generate Evidence About Health Outcomes from Social Media Use
Authors: Merolli Mark  , Gray Kathleen  , Martin-Sanchez Fernando
Published: February 2025

Research surrounding social media's impact on patient-reported health outcomes continues to emerge. However, an ongoing challenge for researchers is generating valid and reliable evidence that draws upon rigorous frameworks. This manuscript details the development and refinement of a framework that defines criteria and methods for generating and evaluating evidence about social media use in chronic disease management; the Therapeutic Affordances of Social Media (TASoMe) framework. TASoMe was built through the considered combination of mixed research methods and data collection instruments. It represents a systematic methodology for conducting research that brings together the key concepts of: therapeutic affordances, patient-reported outcomes, and evidence-based practice to generate evidence about health outcomes from social media use. Its key building blocks include: the key research concepts, research methods, and stakeholders standing to benefit from outcomes. TASoMe contributes to the field of participatory health informatics by offering a stringent and reliable model for advancing research and practice. It has begun to be independently validated across a range of health conditions, and has the potential to be applied to a range of participatory health informatics technologies.
Automatic Processing of Anatomic Pathology Reports in the Italian Language to Enhance the Reuse of Clinical Data
Authors: Viani Natalia  , Chiudinelli Lorenzo  , Tasca Cristina  , Zambelli Alberto  , Bucalo Mauro  , Ghirardi Arianna  , Barbarini Nicola  , Sfreddo Eleonora  , Sacchi Lucia  , Tondini Carlo  , Bellazzi Riccardo
Published: February 2025

Medical reports often contain a lot of relevant information in the form of free text. To reuse these unstructured texts for biomedical research, it is important to extract structured data from them. In this work, we adapted a previously developed information extraction system to the oncology domain, to process a set of anatomic pathology reports in the Italian language. The information extraction system relies on a domain ontology, which was adapted and refined in an iterative way. The final output was evaluated by a domain expert, with promising results.
User Profile Detection in Health Online Fora
Authors: Pertin Camille  , Deccache Carole  , Gagnayre Rémi  , Hamon Thierry
Published: February 2025

Exchanges between diabetic patients on discussion fora permit to study their understanding of their disorder, their behavior and needs when facing health problems. When analyzing these exchanges and behavior, it is necessary to collect information on user profile. We present an approach combining lexicon and super-vised classifiers for the identification of age and gender of contributors, their disorders and relation between contributor and patient. According to parameters of the method, precision is between 100% for gender and 53.48% for disorders.
Making the CARE Comprehensive Geriatric Assessment as the Core of a Total Mobile Long Term Care Support System in China
Authors: Cui Yanyan  , Gong Dongwei  , Yang Bo  , Chen Hua  , Tu Ming-Hsiang  , Zhang Chaonan  , Li Huan  , Liang Naiwen  , Jiang Liping  , Chang Polun
Published: February 2025

Comprehensive Geriatric Assessments (CGAs) have been recommended to be used for better monitoring the health status of elder residents and providing quality care. This study reported how our nurses perceived the usability of CGA component of a mobile integrated-care long term care support system developed in China. We used the Continuity Assessment Record and Evaluation (CARE), developed in the US, as the core CGA component of our Android-based support system, in which apps were designed for all key stakeholders for delivering quality long term care. A convenience sample of 18 subjects from local long term care facilities in Shanghai, China were invited to assess the CGA assessment component in terms of Technology Acceptance Model for Mobile based on real field trial assessment. All (100%) were satisfied with the mobile CGA component. 88.9% perceived the system was easy to learn and use. 99.4% showed their willingness to use for their work. We concluded it is technically feasible to implement a CGA-based mobile integrated care support system in China.
Representing the Aboutness of a Diagnosis
Authors: Hogan William
Published: February 2025

Clinical statements such as diagnoses are correct only if all the entities they reference exist and stand in the requisite relationships. Representing the aboutness of a diagnosis to this entire configuration of entities is not straightforward. Past approaches require extraneous entities like “situation” and cannot indicate specifically which relationships in a configuration are relevant for the diagnosis to be correct. I use the paradigm of referent tracking to represent the aboutness of a diagnosis in a manner that addresses these shortcomings.
A Decision Support Tool for Healthcare Professionals in the Management of Hyperphosphatemia in Hemodialysis
Authors: Laursen Sisse H.  , Buus Amanda A.  , Brandi Lisbet  , Vestergaard Peter  , Hejlesen Ole K.
Published: February 2025

Hyperphosphatemia is known as one of the more challenging conditions in end-stage renal disease patients. This study set out to present and evaluate a healthcare-oriented decision support tool in the management of hyperphosphatemia within hemodialysis therapy. A prototype module was designed to fit into the interface of a modern dialysis machine (Fresenius 5008). The prototype included three main functions: 1) immediate bedside blood sample access, 2) a model based prognosis tool with estimates of P-phosphate and 3) an overview of the user's phosphate related activities during dialysis treatments. The prototype was evaluated by a) heuristic evaluation with five human computer interaction experts and b) user testing with think-aloud by three users as (clinical) domain experts. The two evaluation procedures identified a total of 103 usability problems and led to some specific amendments to improve its practical potential. The overall results will guide further development of the decision support tool to ensure that the functions will support the user's needs. In conclusion, the prototype was evaluated to be relevant and potentially beneficial in the management of hyperphosphatemia in hemodialysis patients. Furthermore, it was found that some of the functions could be used for educational purposes or as decision support for some patient groups, e.g. for patient doing home-dialysis.
An Analytical Method for Multimorbidity Management Using Bayesian Networks
Authors: Deparis Stéphane  , Pascale Alessandra  , Tommasi Pierpaolo  , Kotoulas Spyros
Published: February 2025

This paper describes an application of Bayesian Networks to mo-del persons with multimorbidity using measurements of vital signs and lifestyle assessments. The model was developed as part of a project on the use of wearable and home sensors and tablet applications to help persons with multimorbidity and their carers manage their conditions in daily life. The training data was extracted from TILDA, an open dataset collected from a longitudinal health study of the older Irish population. A categorical BN structure was learnt using a score-based approach, with constraints on the ordering of variables. The prediction accuracy of the model is assessed using the Brier score in a cross-validation experiment. Finally, a user inter-face that allows to set some observed levels and query the resulting margi-nal probabilities from the BN is presented.
Use of System Dynamics Modeling in Medical Education and Research Projects
Authors: Bozikov Jadranka  , Relic Danko  , Dezelic Gjuro
Published: February 2025

The paper reviews experiences and accomplishments in application of system dynamics modeling in education, training and research projects at the Andrija Stampar School of Public Health, a branch of the Zagreb University School of Medicine, Croatia. A number of simulation models developed over the past 40 years are briefly described with regard to real problems concerned, objectives and modeling methods and techniques used. Many of them have been developed as the individual students' projects as a part of their graduation, MSc or PhD theses and subsequently published in journals or conference proceedings. Some of them were later used in teaching and simulation training. System dynamics modeling proved to be not only powerful method for research and decision making but also a useful tool in medical and nursing education enabling better understanding of dynamic systems' behavior.
Interoperable Localisation of Lesions on the Human Skin
Authors: Weinbacher Andreas  , Tschandl Philipp  , Kittler Harald  , Rinner Christoph
Published: February 2025

Medical terms of anatomical regions are not sufficient to unequivocally describe the locations of lesions on the skin. In order to get gender, age, height and weight independent localisations on the human skin we propose to use the base mesh of MakeHuman in combination with UV coordinates. As proof-of-concept we present a web application based on Three.js with three different MakeHuman 3D models (male, female, infant). Anatomical regions corresponding to UV coordinates are displayed and the UV coordinates of skin lesions can be marked. Marked regions are “transformed” to changed 3D models automatically allowing for tracking in spite of anatomic changes.
Data Modeling Challenges of Advanced Interoperability
Authors: Blobel Bernd  , Oemig Frank  , Ruotsalainen Pekka
Published: February 2025

Progressive health paradigms, involving many different disciplines and combining multiple policy domains, requires advanced interoperability solutions. This results in special challenges for modeling health systems. The paper discusses classification systems for data models and enterprise business architectures and compares them with the ISO Reference Architecture. On that basis, existing definitions, specifications and standards of data models for interoperability are evaluated and their limitations are discussed. Amendments to correctly use those models and to better meet the aforementioned challenges are offered.
Implementing Systems Medicine: A Medical Informatics Perspective
Authors: Ganzinger Matthias  , Gietzelt Matthias  , Karmen Christian  , Flores Blanca  , Knaup Petra
Published: February 2025

Systems medicine is a paradigm for translating in silico methods developed for modelling biological systems into the field of medicine. Such approaches rely on the integration of as many data sources as possible, both in the dimension of disease knowledge and patient data. This is a challenging task that can only be implemented in clinical routine with the help of suitable information technology from the field of Medical Informatics. For the research project “Clinically-applicable, omics-based assessment of survival, side effects, and targets in multiple myeloma” (CLIOMMICS) we developed a prototypical systems medicine application system. It is based on a three-level-architecture covering data representation, decision support, and user interface. The core decision support component is implemented as a case-based reasoning engine. However, the architecture follows a modular design that allows to replace individual components as needed.
Towards Pharmacogenomics-Driven Medication Risk Assessment in People with Polypharmacy
Authors: Liu Jiazhen  , Finkelstein Joseph
Published: February 2025

The main objective of this project was to introduce approaches for comprehensive medication risk assessment in people with polypharmacy that simultaneously account for multiple drug and gene effects. To achieve this goal, we developed an integrated knowledge repository of actionable pharmacogenes and a scoring algorithm that was pilot-tested using a data set containing pharmacogenomic information of people with polypharmacy. Metabolic phenotyping using resulting database demonstrated recall of 83.6% and precision of 87.1%. The final scoring algorithm yielded medication risk scores that allowed distinguish frequently hospitalized older adults with polypharmacy and older adults with polypharmacy with low hospitalization rate (average scores respectively: 75.89±15.45 and 10.51±1.82, p<0.05). The initial prototype assessment demonstrated feasibility of our approach and identified steps for improving risk scoring algorithms. Pharmacogenomics-driven medication risk assessment in patient with polypharmacy has potential in identifying inadequate drug regimens and preventing adverse drug events.
Improving Patient Experience in a Children's Hospital: New Digital Services for Children and Their Families
Authors: Karisalmi Nina  , Kaipio Johanna  , Lahdenne Pekka
Published: February 2025

Digital services are increasingly being developed for the healthcare sector. In Finland, the five university hospitals in 2016 launched a virtual hospital platform, Healthvillage.fi that includes several portals. The aim of this study is to explore the needs of children and their families related to digital services in the context of a children's hospital in Finland. Two methods were used to examine the needs and expectations of children and their families: a web-based survey for parents and video diaries for children. We identified nine categories of needs and noticed they were related to better communication between families, healthcare professionals, and peers. These observations were used to further analyze possible novel digital services for child patients' families to support and to complement the recently launched Healthvillage.fi platform.
Identifying and Validating Requirements of a Mobile-Based Self-Management System for People Living with HIV
Authors: Mehraeen Esmaeil  , Safdari Reza  , Seyedalinaghi Seyed Ahmad  , Mohammadzadeh Niloofar  , Arji Goli
Published: February 2025

Background: Due to the widespread use of mobile technology and the low cost of this technology, implementing a mobile-based self-management system can lead to adherence to the medication regimens and promotion of the health of people living with HIV (PLWH). We aimed to identify requirements of a mobile-based self-management system, and validate them from the perspective of infectious diseases specialists.
Development of a Computer-Aided Dosage and Telemonitoring System for Patients Under Oral Anticoagulation Therapy
Authors: Krumm Heiko  , Reiss Nils  , Burkert Malte  , Schmidt Thomas  , Biehs Steffen  , Bohr Christian  , Gürtler Fabian  , Horn Hendrik  , Kreutzer Philipp  , Mewes Philipp  , Miller Hendrik  , Riest Christian  , Römer Christian  , Seebold Albert  , Sprung Gertrude  , Ziegler Oliver
Published: February 2025

In this paper, we present a system that allows patients who require anticoagulation medicine an opportunity to independently manage their dosage concentration with the help of two machine learning algorithms. The basic idea is to predict the next dosage by using a neuronal network and the model predictive control approach, both based on the history of data already available from patients. This machine learning system is expanded by an smartphone application for the patients, and a website for the doctors to support their patients.
HEALTHeBIKES – Smart E-Bike Prototype for Controlled Exercise in Telerehabilitation Programs
Authors: Mayr Patrick  , Falgenhauer Markus  , Modre-Osprian Robert  , Hofmann Peter  , Traninger Heimo  , Rath Michael  , Schreier Günter
Published: February 2025

E-Bikes in telerehabilitation programs could be a new intervention for more sustainable rehabilitation results. The aim is to design and build a prototype of an E-Bike usable for rehabilitation – a HEALTHeBIKE. It should avoid over-exercising, work independently of the environment and it should enable cycling in a group despite different reference exercise intensities. To achieve these goals, requirements for this system architecture have been identified. A system architecture including an Arduino microcontroller, an Android smartphone and a telemonitoring platform was presented. A power output regulated proportional-integral controller to adjust the motor assistance has been implemented. A feasibility study with two subjects cycling in a group was performed. Seven test rides on varying terrain (flat, hilly, mountainous and uphill) with the same and different exercise intensities were completed. The mean power output was close to or below the target power output of the cyclist for all test rides with a maximal error of 6.7% above and 27.6% below the target. Although the exercise intensities of the two subjects were clearly different, cycling in a group was possible without over-exercising.
Modeling the Personal Health Ecosystem
Authors: Blobel Bernd  , Brochhausen Mathias  , Ruotsalainen Pekka
Published: February 2025

Complex ecosystems like the pHealth one combine different domains represented by a huge variety of different actors (human beings, organizations, devices, applications, components) belonging to different policy domains, coming from different disciplines, deploying different methodologies, terminologies, and ontologies, offering different levels of knowledge, skills, and experiences, acting in different scenarios and accommodating different business cases to meet the intended business objectives. For correctly modeling such systems, a system-oriented, architecture-centric, ontology-based, policy-driven approach is inevitable, thereby following established Good Modeling Best Practices. However, most of the existing standards, specifications and tools for describing, representing, implementing and managing health (information) systems reflect the advancement of information and communication technology (ICT) represented by different evolutionary levels of data modeling. The paper presents a methodology for integrating, adopting and advancing models, standards, specifications as well as implemented systems and components on the way towards the aforementioned ultimate approach, so meeting the challenge we face when transforming health systems towards ubiquitous, personalized, predictive, preventive, participative, and cognitive health and social care.
Human Activity Recognition Supported on Indoor Localization: A Systematic Review
Authors: Cerón Jesús  , López Diego M.
Published: February 2025

Problem: The number of older adults is growing worldwide. This has a social and economic impact in all countries because of the increased number of older adults affected by chronic diseases, health emergencies, and disabilities, representing at the end high cost for the health system. To face this problem, the Ambient Assisted Living (AAL) domain has emerged. Its main objective is to extend the time that older adults can live independently in their homes. AAL is supported by different fields and technologies, being Human Activity Recognition (HAR), control of vital signs and location tracking the three of most interest during the last years.
Climate Changes and Maritime Transportation: A State of the Art
Authors: Mocerino Luigia  , Quaranta Franco  , Rizzuto Enrico
Published: February 2025

In the next years, the worldwide fleet will be called to adopt drastic measures to reduce their emissions of pollutants. In order to comply with the Paris Agreement and keep the average increase in the earth's temperature below 2°C, anthropogenic emissions will have to drop significantly from 2020 onwards. Maritime transportation plays an important role in these policies. At the end of 2018, the United Nations Framework Convention on Climate Change (UNFCC) expects the IMO to communicate its intentions regarding the Paris Agreement. During the last session of MEPC71 guidelines have been set for the purpose. While waiting for regulatory updates in the maritime world, the study aims at interpreting the present position of IMO on the subject within the framework set by the IPCC's last Assessment Report, AR5. The Third IMO study on GHG (3° IMO-GHG's) is analyzed in details, covering the inventory for the period 2007 to 2012 of GHG and of non-GHG emissions in the world's fleet and the forecast scenario for years 2012 to 2050. A last part of the work will concern the effects of these pollutants, with reference to the impact on human health and on environment.
Environmental Monitoring System in a Cruise Ship Cabin
Authors: Baronti Paolo  , Barsocchi Paolo  , Ferro Erina  , La Rosa Davide  , Nerino Roberto  , Piotto Massimo  , Ravazzani Paolo  , Tognola Gabriella  , Celotti Daniel  , Guglia Paolo
Published: February 2025

Data collected in a cruise ship cabin from a monitoring system can be used for various scenarios, such as the energy waste reduction and the passenger wellness & comfort. Although the reference scenarios are out of the scope of this paper, we concentrate on presenting an effective and efficient monitoring system. In this context, we describe an environmental monitoring system for a closed environment, based on heterogeneous sensor networks, and a minimal invasiveness approach for a robust monitoring of sleep quality, which integrates signals from different types of sensors to estimate physiological parameters.
Assessment of Evaluation Frameworks for Design of a Sexual Risk Prevention Game for Black Adolescent Girls
Authors: Sockolow Paulina  , Joppa Meredith  , Zhu Jichen
Published: February 2025

Adolescent sexual risk behavior (SRB), a major public health problem affects urban Black adolescent girls increasing their health disparities and risks for sexually transmitted infections. Collaborating with these adolescents, we designed a game for smartphones that incorporates elements of trauma-informed care and social cognitive theory to reduce SRB. Game researchers promote use of a comprehensive, multipurpose framework for development and evaluation of games for health applications. Our first game development step was framework selection and measurable health outcomes identification. Literature search identified two health game frameworks, both incorporating pedagogical theory, learning theory, and gaming requirements. Arnab used the IM + LM-GM framework to develop and implement a game in a school intervention program. Yusoff's framework was developed for use during game design. We investigated concordance and discordance between our SRB game design characteristics and each framework's components. Findings indicated Arnab's framework was sufficiently comprehensive to guide development of our game and outcome measure selection.
Constructing an Interdepartmental Information Integration System for Discharge Planning Services
Authors: Feng Rung-Chuang  , Tsai Hui-Hua  , Li Yun-Pao
Published: February 2025

Discharge planning involves providing appropriate healthcare, assistive devices, and support systems through the collaborative discussion and planning among hospital staff and clients' family members. With seamless transition of patient care as the goal, an intelligent information platform, i.e. an interdepartmental information integration system for discharge planning services, was established. This system is connected with operating systems and clinical care workflows to connect the patient with long-term or home care medical resources. We aimed to provide an ideal healthcare model focusing on staff diligence, patient comfort, and family confidence throughout discharge, thereby achieving the healthcare targets of intelligent care and high-quality nursing.
Technologies to Combat Aedes Mosquitoes: A Model Based on Smart City
Authors: de Souza Silva Geovanna Cristine  , Peltonen Laura-Maria  , Pruinelli Lisiane  , Yoshikazu Shishido Henrique  , Jacklin Eler Gabrielle
Published: February 2025

Aedes aegypti and Aedes albopictus mosquitoes are responsible for the transmission of diseases such as dengue fever, yellow fever, chikungunya fever, zika virus fever, some of which can cause irreversible central nervous system problems and death. This study investigates what technologies are being used for combatting and monitoring the Aedes mosquitoes and to propose joining these technologies into a single and complete solution using the Smart Cities concept. A search for newscasts on Google and mobile apps in app stores were performed to identify technological solutions for combat to Aedes mosquitoes. Also, a model for joint technology was proposed. Results identified the following technologies: 170 software, two sensors, two drones, one electronic device, ten mosquito traps/lures, seven biological tools, six biotechnologies, and eight chemical formulations. Technological resources and adoption of preventive measures by the population could be a useful method for the mosquito control. Examples include a georeferenced model for identification and examination of larvae, application of chemical/biological products, real-time mapping, sending of educational materials via email or social media for the population, and alerts to health professionals in the zones of combat/risk. In combination, these technologies may indicate a better solution to the current problem.
Relevant Factors Affecting Nurse Use of a Pain Management System
Authors: Chen Li-Ya  , Chiou Shwu-Fen  , Sun Yu-Ching  , Pan Mei-Lien  , Liu Chieh-Yu
Published: February 2025

This study aimed to explore influencing factors and predictive capability for nursing staff use of a pain management system based on the information system success model. There were three key results: (a) Information quality is the most important influencing factor; (b) The correlations between these factors were all positively correlated; (c)Information quality and user satisfaction are the affect factors in predicting net benefits. These results elucidate the relevant factors affecting use of a pain management system by nurses, and can also predict system benefits.
The MOBile-Health and Implementation Leadership Evaluation (MOBILE) Nurse Study: Developing a Testable Conceptual Model
Authors: Ronquillo Charlene  , Dahinten Susan  , Bungay Vicky  , Currie Leanne
Published: February 2025

Leadership is consistently identified as an important factor that influences nurses' adoption of health information technologies, yet, the concept of leadership remains underdeveloped. Our study examines the influence of leadership on nurses' mHealth usage outcomes. Informed by diverse fields, we developed the MOBILE Nurse conceptual model as a way to empirically explore relationships between leadership and other factors commonly thought to influence mHealth usage in nursing.
Effectiveness of mHealth Interventions for Asthma Self-Management: A Systematic Review and Meta–Analysis
Authors: Xiao Qian  , Wang Jiani  , Chiang Vico  , Choi Thomas  , Wang Yanling  , Sun Liu  , Wu Ying
Published: February 2025

To assess the effectiveness of mHealth interventions for asthma self-management, we conducted a systematic review and meta-analysis of relevant studies identified by a search of English and Chinese databases. 18 studies were included in meta-analysis, and the results showed that mHealth interventions (vs routine care) improved the level of asthma control and adherence to treatment, and reduced exacerbation rate and admission rate. Evidence from this study shows that mobile health-based interventions may be useful tools for asthma self-management.
The Effectiveness of Taiwan TIGER Model in Assisting Nurses in Designing Customized Diabetics Medication Management System
Authors: Qiao Li  , Cao Yingjuan  , Yu Xiaofeng  , Liu Yan  , Chang Polun
Published: February 2025

Our hospital was still late in establisheding a nursing information system, including a component for blood glucose management. We tried to use the Taiwan TIGER model to train ourselves to see whether we could develop a working system on our own. The process is very educating and we did not only successfully designed a system based on our ideas, but also learn how to convert from traditional paper work to automation with ICT capability.
Can Staff Distinguish Falls: Experimental Hypothesis Verification Using Japanese Incident Reports and Natural Language Processing
Authors: Yokota Shinichiroh  , Shinohara Emiko  , Ohe Kazuhiko
Published: February 2025

Falls are generally classified into two groups in clinical settings in Japan: falls from the same level and falls from one level to another. We verified whether clinical staff could distinguish between these two types of falls by comparing 3,078 free-text incident reports about falls using a natural language processing technique and a machine learning technique. Common terms were used in reports for both types of falls, but the similarity score between the two types of reports was low, and the performance of identification based on the classification model constructed by support vector machine and deep learning was low. Although it is possible that adjustment of hyper parameters during construction of the classification model was required, we believe that clinical staff cannot distinguish between the two types of falls and do not record the distinction in incident reports.
Electronic Method for Measuring Nursing: Workload Action Measures Method (WAMM)
Authors: Saba Virginia  , Whittenburg Luann
Published: February 2025

The Workload Action Measures Method (WAMM) is a predictive model of care workload for individual patients.
Evaluation of Nurses' Acceptance of Screen Display Methods with Temporarily Non-Display for Privacy Protection
Authors: Niimi Yukari  , Ota Katsumasa  , Ikegami Chikako
Published: February 2025

The purpose of this study was to explore nurses' acceptance of a screen display method that temporarily hides patient information for privacy protection. Using a questionnaire, we asked nurses to evaluate the display method from the viewpoints of safety and efficiency with respect to 22 personal information items. The nurses were favorably interested in introducing the display method into their hospital system; however, their acceptance varied.
A Cloud Based Potentially Inappropriate Medication Management System Using Patient Owned Personal Health Records
Authors: Lee Hsiu-An  , Chao Louis R.  , Rau Hsiao-Hsien  , Yang Shang-Dong  , Hsu Chien-Yeh
Published: February 2025

Taiwan has been confronted with a serious problem of aging in recent years. The prevalence of the chronic diseases caused by aging is increased continuously, which has led to a high percentage of comorbidity and polypharmacy. The proportion of the elderly people with polypharmacy (over three to five kinds of drugs) is 81%. Under the situation of high comorbidity, the potentially inappropriate drug for the elderly have become a series problem. However, in order to promote personal health management, Taiwan's Ministry of Health and Welfare has released a service of “My Health Bank”, which contains all the personal medical information issued by the National Health Insurance Department and can be downloaded by any individual person. This study designs a cloud-based personal health management platform to parse and store the information of “My Health Bank”, establishes two databases, one for the health insurance drug table and one for the inappropriate medications. A warning of inappropriate personal medication will be generated based on a checking process. We expect that the application will enhance the safety of medication and improve the self-health management of the elderly.
Digitalized Discharge Planning Between Hospitals and Municipal Health Care
Authors: Hellesø Ragnhild  , Gautun Heidi
Published: February 2025

The use of digitalized collaboration between levels of care is expected to improve coordination in patients' transitions. The aim of this study was to investigate how safe and effective e-messages were regarding discharge planning between hospital nurses and the municipal level of administration. A nationwide survey was conducted among 2 431 Norwegian nurses working in inpatient wards in general hospitals. A majority (86%) of the nurses used e-messages as their main mode of communication with the administration when older patients were discharged. Most nurses (73%) found that e-messages were effective in their collaboration, and that e-messages ensured safe discharge for older patients (65%). More than half of the nurses reported being satisfied with the collaboration with the administration. E-messages supported hospital nurses in their discharge planning for older patients. However, they sometimes needed to use the telephone to exchange additional and more detailed information.
Digitalization of Patient Information Process from Hospital to Community (Home) Care Nurses: International Perspectives
Authors: Sockolow Paulina  , Hellesø Ragnhild  , Ekstedt Mirjam
Published: February 2025

For older people who transition from hospital to home, home care is an increasingly important and effective way of managing chronic illness with skilled nursing care in the home. Communication between clinicians across care settings is fundamental for continuity of care. Poor communication of patient information is acknowledged to be a root cause of sentinel events. In Scandinavia and the United States, researchers study the communication of patient information from hospital to home care. The health care systems of these two countries differ. Differences are reflected in the characteristics of patients transferred from hospital to home care, as well as the characteristics of health information systems (ICT). These differences help to elucidate key issues related to the transfer of patient information from hospital to home care.
Use of Distraction to Reduce Pain in Venipunture when a Venoclysis Is Placed
Authors: Juarez García Jessica  , Jordán Morales Adriana  , García Fernández Lizbeth  , Rosas Negrete Reyna  , Rendón Macias Mario Enrique  , Ramírez Sánchez Sylvia Claudine
Published: February 2025

The use of a venoclysis in hospitalized pediatric patients is a necessity, a procedure perceived by children as painful, so that distraction techniques have been suggested to attenuate this suffering. Evaluating the implementation of a distraction method with an uncontrolled trial with pre and post maneuver evaluation without control group.
Technology Informatics Guiding Education Reform (TIGER). The Future of Interprofessional Education Is Here!
Authors: Kuo Ming-Chuan  , Ball Marion  , Skiba Diane J.  , Marin Heimar  , Shaw Toria  , Chang Polun
Published: February 2025

This session will describe the TIGER Initiative journey, its evolution and accomplishments nationally and internationally. A powerful demonstration of the TIGER Virtual Learning Environment (VLE) will be highlighted along with case studies from around the world, with emphasis on global competencies and opportunities for engagement in all current TIGER activities and future plans.
Information Literacy in Nursing Students of Fes Zaragoza Unam
Authors: Sánchez G. Ana  , Carmona M. Beatriz  , Pérez O. Edgar  , del Socorro García V. Ma.
Published: February 2025

In an exploratory quantitative study,information literacy was analyzed in first-year students of the nursing program at the Facultad de Estudios superiores Zaragoza UNAM. A sample of 150 students completed, a validated scale that consisted of 8 categories and a total of 110 items. The average score obtained was 2.11, which places them in a ‘low knowledge’ category of information literacy.
Nurses' Experiences and Perceptions of Mobile Learning: A Survey in Beijing, China
Authors: Xiao Qian  , Sun Aihua  , Wang Yicong  , Zhang Yan  , Wu Ying
Published: February 2025

To explore nurses' experience and perceptions toward mobile learning, 397 nurses were investigated. All of them used mobile learning in the past one year through internet, e-books and WeChat. Smartphones were the most used mobile learning tools, followed by a tablet and laptop computer. The mean score of nurses' intention towards mobile learning was 12.1 (ranged from 7 to 15), and it related to nurses' gender, education background, expected effect, ease of operation, self-learning management and perceived interest. Nurses had positive perception toward mobile learning and enough conditions to promote nurses' mobile learning should be provided.
Towards Understanding the Impact of EHR-Related Information Overload on Provider Cognition
Authors: Rand Victoria  , Coleman Cam  , Park Rachel  , Karar Azza  , Khairat Saif
Published: February 2025

Information overload is a significant problem in the digital age of healthcare and plays key a role in diagnostic errors, near misses, and patient safety, especially in critical care settings. Because of this, we propose a new mixed-methods approach for evaluating EHR-related information overload on clinicians in the ICU. We describe a three-part approach to better understand ICU clinicians' information needs and workflow as they relate to the EHR, and to explore the effects of the EHR on provider workload, performance, and satisfaction. Based on discussions with ICU providers, key areas of information needs have been identified and a preliminary model of EHR workflow has been established.
Methods to Measure the Impact of mHealth Applications: Preliminary Results of a Scoping Review
Authors: Holl Felix  , Swoboda Walter
Published: February 2025

Important requirements for mHealth, the availability of devices and network connectivity have dramatically improved in the past years globally. mHealth applications are being developed at a rapid pace. But a thorough impact assessment is not routinely performed. We performed a scoping review to compile an overview of evaluation methods used to assess mHealth applications. Preliminary results are reported here, and a full scoping review is in preparation. Qualitative measurement of user experience is common. A number of studies measured the impact of the mHealth intervention on clinical outcomes. Few measured usability and end-user experience. Assessment of the impact on treatment process was rare and evaluations of cost and cost-effectiveness analyses are rarely ever done. An evaluation framework for mHealth interventions that includes disease-appropriate clinical outcome measures, use experience measure but also an economic component in form of cost comparison of the intervention with the standard of care should be developed.
Matching Ontologies to HL7 FHIR Towards Their Syntactic and Semantic Similarity
Authors: Kiourtis Athanasios  , Mavrogiorgou Argyro  , Kyriazis Dimosthenis
Published: February 2025

Current medical systems need to be able to communicate complex and detailed medical data securely and efficiently. However, the quantity of available healthcare data is rising rapidly, far exceeding the capacity to deliver personal or public health benefits from analyzing this data. Thus, a substantial overhaul of methodology is required to address the real complexity of health. This can be achieved by constructing medical domain ontologies for representing medical terminologies, considered to be a difficult task, requiring a profound analysis of the structure and the concepts of medical terminologies. In this paper, a mechanism is presented for constructing healthcare ontologies, while matching them to HL7 FHIR Resources ontologies both in terms of syntactic and semantic similarity, in order to understand their nature and translate them into a common standard to improve the quality of patient care, research, and health service management.
Clinical Data Warehouse Query and Learning Tool Using a Human-Centered Participatory Design Process
Authors: Mullin Sarah  , Zhao Jane  , Sinha Shyamashree  , Lee Robert  , Song Buer  , Elkin Peter L.
Published: February 2025

BMI Investigator (BMII) is an interactive web-based tool with a learning knowledge base, which provides a way for researchers to query structured, unstructured, genomic and image data contained in a data warehouse. We demonstrate how development of an efficient, usable, and learnable web interface for a diverse group of research stakeholders benefits from an iterative human-centered participatory design process utilizing a team of clinicians, students, programmers, and informatics experts.
Computer Virus Models – The Susceptible Infected Removed (SIR) Model
Authors: Zimeras Stelios  , Diomidous Marianna
Published: February 2025

The healthcare domain requires security against possible threats, such as viruses to defend the integrity of the health and patient records. During the system analysis, different parts of the sub systems are connected under a main system. Under these connections into the Internet, malicious programs are spread into the system network and damages to vital information have been appearing. For that reason, it is crucial to model the spreading of the computer virus using dynamic equation systems and the solution of these systems will be presented. In this work an epidemiological model SIR is presented, and the analysis of its performance is illustrated.
Quality Management of Patient Generated Health Data in Remote Patient Monitoring Using Medical Wearables – A Systematic Review
Authors: Abdolkhani Robab  , Borda Ann  , Gray Kathleen
Published: February 2025

To be considered fit for use in clinical care, health data should meet quality requirements, and data generated in remote patient monitoring settings are not exempt. Since patients take part of the responsibility in ensuring the quality of data during their flow from patient to the clinical setting, the quality management of these data is of great importance. This study aims to systematically review the literature to understand the current situation of quality management of patient generated data in remote patient monitoring particularly in use of wearable medical devices.
Adherence, Avatars and Where to From Here
Authors: Fang Kerry Y.  , Bjering Heidi  , Ginige Athula
Published: February 2025

Adherence to medication and treatment regimen continues to rank as one of the major clinical problems worldwide. Many of the currently available strategies lack the personalised interaction needed in order to effectively connect with the patients. Our solution is to develop an interactive avatar-based reminder application to simulate a human carer to provide customised conversations with the aim of improving adherence and satisfaction. The results of our initial trial showed that information and communication provided by the avatar were useful in reminding participants to take their health supplements. This paper discusses the importance of personalised communication and information in improving adherence and satisfaction, what we have learned from our initial trial with the avatar-based reminder application, and our proposed modifications for our next trial.
Novel Correction of Cardiac Rehabilitation Resting Physiologic Outcomes in Patients Without a History of Infarction
Authors: Hamdy Ehsan
Published: February 2025

Background: Large datasets of outcomes in cardiac rehabilitation (CR) are not often analysed using a combination of primary presentations and comorbidities, which has left important issues as yet unresolved. This study investigates the influence of history of infarction, measured pre-program resting blood pressure, and comorbidities including diagnosed hypertension, hypercholesterolemia, diabetes and obesity on CR outcomes in patients without a history of myocardial infarction (MI).
Designing a Chat-Bot for Non-Verbal Children on the Autism Spectrum
Authors: Cooper Anabelle  , Ireland David
Published: February 2025

There is a significant amount of anecdotal evidence of the benefits of individuals on the autism spectrum interacting with technology via natural language. Many of these individuals are non-verbal but still able to communicate via augmentative and alternative communication (AAC) aids. This paper presents the design of a AAC software program (app) with embedded artificial conversational agent, called Alex. Alex runs on a Android device and is able to engage with the user on a variety of topics using symbols and images. Alex may be programmed via speech and occupational therapists and other key stakeholders via speech and hence does not require any specialised computer skills. The importance of customisation, interoperability, personalisation and motor skill considerations is herein discussed.
Modeling Activity Tracker Data Using Deep Boltzmann Machines
Authors: Treppner Martin  , Lenz Stefan  , Binder Harald  , Zöller Daniela
Published: February 2025

Commercial activity trackers are set to become an essential tool in health research, due to increasing availability in the general population. The corresponding vast amounts of mostly unlabeled data pose a challenge to statistical modeling approaches. To investigate the feasibility of deep learning approaches for unsupervised learning with such data, we examine weekly usage patterns of Fitbit activity trackers with deep Boltzmann machines (DBMs). This method is particularly suitable for modeling complex joint distributions via latent variables. We also chose this specific procedure because it is a generative approach, i.e., artificial samples can be generated to explore the learned structure. We describe how the data can be preprocessed to be compatible with binary DBMs. The results reveal two distinct usage patterns in which one group frequently uses trackers on Mondays and Tuesdays, whereas the other uses trackers during the entire week. This exemplary result shows that DBMs are feasible and can be useful for modeling activity tracker data.
Prediction of Readmissions in the German DRG System Based on §21 Datasets
Authors: Eggerth Alphons  , Hayn Dieter  , Veeranki Sai  , Stieg Jörg  , Schreier Günter
Published: February 2025

Hospital readmissions receive increasing interest, since they are burdensome for patients and costly for healthcare providers. For the calculation of reimbursement fees, in Germany there is the German-Diagnosis Related Groups (G-DRG) system. For every hospital stay, data are collected as a so-called “case”, as the basis for the subsequent reimbursement calculations (“§21 dataset”). Merging rules lead to a loss of information in §21 datasets. We applied machine learning to §21 datasets and evaluated the influence of case merging for the resulting accuracy of readmission risk prediction. Data from 478,966 cases were analysed by applying a random forest. Many cases with readmissions within 30 days had been merged and thus their prediction required additional data. Using 10-fold cross validation, the prediction for readmissions within 31–60 days showed no notable difference in the area under the ROC curves comparing unedited §21 datasets with §21 datasets with restored original cases. The achieved AUC values of 0.69 lie in a similar range as the values of comparable state-of-the-art models. We conclude that dealing with merged cases, i.e. adding data, is required for 30-day-readmission prediction, whereas un-merging brings no improvement for the readmission prediction of period beyond 30 days.