bluuebunny/crossref_metadata_2025 huggingface dataset:
Adaptive Sampling Technique Using Regression Modelling and Fuzzy Inference System for Network Traffic
Authors: Salama Abdussalam  , Saatchi Reza  , Burke Derek
Published: February 2025

Electronic-health relies on extensive computer networks to facilitate access and to communicate various types of information in the form of data packets. To examine the effectiveness of these networks, the traffic parameters need to be analysed. Due to quantity of packets, examining their transmission parameters individually is not practical, especially when performed in real time. Sampling allows a subset of packets that accurately represents the original traffic to be chosen. In this study an adaptive sampling method based on regression and fuzzy inference system was developed. It dynamically updates the sampling by responding to the traffic changes. Its performance was found to be superior to the conventional non-adaptive sampling methods.
Lived Experience, Stakeholder Evaluation and the Participatory Design of Assisted Living Technology
Authors: Cahill Joan  , McLoughlin Sean  , Wetherall Sean
Published: February 2025

This paper presents the theoretical and methodological framework underpinning the advancement of new technology enabling seniors domicile in residential homes to live with independence, quality of life and dignity. In addition, it presents the preliminary findings of this research including the emerging user interface design solution.
Attenuating Tremor Using Passive Devices
Authors: Katz Reuven  , Buki Eran  , Zacksenhouse Miriam
Published: February 2025

Limb tremor is treated with either medication or surgery, both of which may have adverse effects. This paper presents two passive devices for tremor attenuation: One for attenuating pronation/supination tremor of the forearm using a dynamic vibration absorber, and the other for attenuating flexion/extension tremor of the hand using a rotational damper.
Efficiency and Rolling Resistance in Manual Wheelchair Propulsion
Authors: Hashizume Tsutomu  , Kitagawa Hiroshi  , Ueda Hisatoshi  , Yoneda Ikuo  , Booka Masayuki
Published: February 2025

The efficiency and the rolling resistance in wheelchair propulsion play an important role in the comfort and the health of wheelchair users in daily life. Here we identify these fundamental interactions of wheelchair-user system on treadmill and on track. We measured the oxygen uptake (input) and the propelling torque (output) as the parameters with velocity and tire pressure. The efficiency increased about 9–13% as the velocity increased on treadmill and it increased around 11–12% as the tire pressure reduced on track. The mean coefficient of rolling resistance was 0.012 on treadmill and that were 0.016 (200 kPa) and 0.026 (30 kPa) on track. Our experimental results indicated that the efficiency and the rolling resistance were strongly dependent on the velocity and tire pressure.
Effects of Optimizing the Scan-Path on Scanning Keyboards with QWERTY-Layout for English Text
Authors: Sandnes Frode Eika  , Medola Fausto Orsi
Published: February 2025

Scanning keyboards can be essential tools for individuals with reduced motor function. However, most research addresses layout optimization. Learning new layouts is time-consuming. This study explores the familiar QWERTY layout with alternative scanning paths intended for English text. The results show that carefully designed scan-paths can help QWERTY nearly match optimized layouts in performance.
Proof-of-Concept Integration of Heterogeneous Biobank IT Infrastructures into a Hybrid Biobanking Network
Authors: Mate Sebastian  , Kadioglu Dennis  , Majeed Raphael W.  , Stöhr Mark R.  , Folz Michael  , Vormstein Patric  , Storf Holger  , Brucker Daniel P.  , Keune Dietmar  , Zerbe Norman  , Hummel Michael  , Senghas Karsten  , Prokosch Hans-Ulrich  , Lablans Martin
Published: February 2025

Cross-institutional biobank networks hold the promise of supporting medicine by enabling the exchange of associated samples for research purposes. Various initiatives, such as BBMRI-ERIC and German Biobank Node (GBN), aim to interconnect biobanks for enabling the compilation of joint biomaterial collections. However, building software platforms to facilitate such collaboration is challenging due to the heterogeneity of existing biobank IT infrastructures and the necessary efforts for installing and maintaining additional software components. As a remedy, this paper presents the concept of a hybrid network for interconnecting already existing software components commonly found in biobanks and a proof-of-concept implementation of two prototypes involving four biobanks of the German Biobank Node. Here we demonstrate the successful bridging of two IT systems found in many German biobanks – Samply and i2b2.
Factors Influencing the Implementation and Distribution of Clinical Decision Support Systems (CDSS)
Authors: Kux Benjamin R.  , Majeed Raphael W.  , Ahlbrandt Janko  , Röhrig Rainer
Published: February 2025

Clinical Decision Support Systems (CDSS) can have positive effects on quality of care measures, yet have not gained widespread traction in healthcare. This study sought to determine and evaluate barriers and facilitators to CDSS implementation and distribution. Based on 768 systems identified in a literature review we conducted semi-structured telephone interviews with 54 system developers in 16 countries. Qualitative analysis led to the identification of 66 key factors influencing implementation. Central issues evolved around CDSS properties, quality and integration, as well as usability, user related factors, internal marketing, resource issues and collaborations with emphasis partly on topics differing from existing research. Additionally, evidence pointed to regional differences regarding implementation hurdles. Recent regulatory requirements were deemed less of a barrier to system adoption than expected, even though lacking expertise in this area was surprisingly common among interview partners.
Processual Reasoning over Sequences of Situations in Endoscopic Surgery
Authors: Siemoleit Sebastian  , Uciteli Alexandr  , Bieck Richard  , Herre Heinrich
Published: February 2025

Minimally invasive surgery is a highly complex and technically demanding alternative to open surgery. Surgical procedures based on this method are characterized by small incisions and allow for a fast recovery of the patient. Such techniques are challenging for surgeons since they do not have a direct view of the surgical area. Systems that provide surgical navigation are well established in clinical practice but depend on external markers allowing a mapping between a surgeon's tools and a patient's medical images. As of today, these systems are prone to inaccuracies, the reasons of which lie in their extensive technical requirements. The BIOPASS project aims to develop an alternative that works without external markers and indirect computation of locations. An ontology has been used to provide an adequate vocabulary describing situations and their temporal relationship. This ontology is expected to relate real time multimodal sensor data and static surgical process models in order to infer movement directions, subsequent actions and hidden anatomical structures that inhere risk for surgical interventions. However, the Web Ontology Language is not capable of modelling temporal conditions, which are necessary to provide such exhaustive situational descriptions as expected by a surgeon. This paper concerns an ontology design pattern developed to overcome this issue by the integration of dynamic ontological classes that are assigned according to the temporal relations between situations.
The Value of Data and the Value of Questions: Achieving Improvement in Hospital Pharmacy and Medication Safety
Authors: Lichtner Valentina  , Cornford Tony
Published: February 2025

Medication safety incidents are one of the major patient safety issue faced across all healthcare services and one that is very challenging to tackle. To make progress, data about the supply and use of medicines that is generated and made available in clinical systems can serve both the purposes of patient safety and service quality improvement. This paper shows how the value of data for these purposes can be framed in terms of the value of questions. This theme is developed based on an interview with a quality and safety pharmacist working in a large hospital pharmacy unit.
How to Use TCM Informatics to Study Traditional Chinese Medicine in Big Data Age
Authors: Shi Cheng  , Gong Qing-yue  , Zhou Jinhai
Published: February 2025

This paper introduces the characteristics and complexity of traditional Chinese medicine (TCM) data, considers that modern big data processing technology has brought new opportunities for the research of TCM, and gives some ideas and methods to apply big data technology in TCM.
Identifying Use Cases for Electronic Nursing Record Systems Using Clinical Workflow Observations and a Delphi Survey
Authors: Cho Insook  , Chung Joohyun
Published: February 2025

This study describes the process of identifying use cases for next generation electronic nursing records in a high-level view. Literature review, clinical observation, and a Delphi survey were employed. Eight use cases were identified with importance and convergence scores.
A Study on Data-Driven Novel Cancer Staging Methods
Authors: Gao Yuan  , Tian Yu  , Chi Shengqiang  , Lu Yao  , Li Xinhang  , Zhou Tianshu  , Li Jing-song
Published: February 2025

This paper presents a data-driven method to study the relationship of survival and clinical information of patients. The machine learning models were established to study the survival situation at the time of interest based on survival analysis. The way to determine the time of interest is an innovation of this paper. The distribution of survival time is considered, namely the three quartiles, as well as the traditional analysis experience is taken into consideration.
Nursing Informatics Pioneers Embrace Social Media
Authors: Brixey Juliana J.  , Newbold Susan K.
Published: February 2025

The American Medical Informatics Association (AMIA) established the Nursing Informatics History Project to recognize the pioneers of nursing informatics. Fundamental to the pioneers was dissemination of knowledge. The purpose of this review was to identify pioneers who have embraced social media as of 2016. It is suggested that the pioneers participate in the advancement of nursing informatics via social media.
Dynamic Creation of Patient Summaries: A CDA and IHE XDS Based Approach for Regional EHRs
Authors: Mangesius Patrick  , Saboor Samrend  , Healy Thomas  , Schabetsberger Thomas
Published: February 2025

Cooperative healthcare is regarded as one of the major goals for providing adequate health related information to physicians. To achieve this goal, national authorities and large hospital organizations are introducing large scale, standard based transactional EHR systems. Those systems record and distribute a significant amount of medical related data. This raises the concern of information overload for the intended users. The objective is to elaborate on an architecture and consequently a workflow that allows the generation of an automatic patient summary in a standard based IHE XDS environment. A literature review evaluating the current state of research is conducted. Current eHealth projects, laws and technical background are analyzed. An architecture is suggested, prototyped and compared using SAAM (Software Architecture Analysis Method) against alternative approaches. A technical workflow built on IHE XDR and HL7 FHIR observations is suggested introducing two new services within an IHE XDS product for extracting observations from CDA documents and storing the data on domain level scope. The information is published as an OnDemand Document in the IHE XDS infrastructure.
iT2DM Project: A Framework for Secondary Use of EHR Data for High-Throughput Phenotyping in Diabetes
Authors: Wei Yufang  , Shang Yujuan  , Wang Jie  , He Defu  , Zhou Shengrong  , Zhang Weixun  , Shi Lili  , Chen Yalan  , Jiang Kui  , Wu Huiqun  , Dong Jiancheng
Published: February 2025

Diabetes is one of the major burdens in health care, but could be controlled if the relevant data are well-managed. Referring to current successful cases, we designed a framework for the interoperability and integration of medical data in compliance with both archetype and reference information model specification. The clinical data model (CDM) was designed on the basis of OpenEHR archetypes and self-made patient generated health data (PGHD). Integrating healthcare enterprise (IHE) protocol was taken into integrating different modality data. After terminology mapping, the personal health record could be transferred and shared in different clinical information vendors complying with HL7 standards. Many fragment data such as blood glucose and gene data were also integrated to system. Those patients suspected of higher risk of diabetic retinopathy (DR) were grouped as case and other patients could be filtered as control cohort. Furthermore, the framework could be further developed for precision medicine.
Mining Adverse Drug Reactions in Social Media with Named Entity Recognition and Semantic Methods
Authors: Chen Xiaoyi  , Deldossi Myrtille  , Aboukhamis Rim  , Faviez Carole  , Dahamna Badisse  , Karapetiantz Pierre  , Guenegou-Arnoux Armelle  , Girardeau Yannick  , Guillemin-Lanne Sylvie  , Lillo-Le-Louët Agnès  , Texier Nathalie  , Burgun Anita  , Katsahian Sandrine
Published: February 2025

Suspected adverse drug reactions (ADR) reported by patients through social media can be a complementary source to current pharmacovigilance systems. However, the performance of text mining tools applied to social media text data to discover ADRs needs to be evaluated. In this paper, we introduce the approach developed to mine ADR from French social media. A protocol of evaluation is highlighted, which includes a detailed sample size determination and evaluation corpus constitution. Our text mining approach provided very encouraging preliminary results with F-measures of 0.94 and 0.81 for recognition of drugs and symptoms respectively, and with F-measure of 0.70 for ADR detection. Therefore, this approach is promising for downstream pharmacovigilance analysis.
Automatically Identifying Topics of Consumer Health Questions in Chinese
Authors: Guo Haihong  , Na Xu  , Li Jiao
Published: February 2025

In health question answering (QA) system development, question topic identification is crucial to understand users' information needs and further facilitate answer extraction. This paper presented a machine-learning method to automatically identify topics of health related questions in Chinese asked by the general public. We collected 2000 questions from Chinese consumer health website, and characterized them using 17 types of features such as lexical, grammatical, statistical, and semantic features. This method were applied to identify 6 health question topics of Condition Management, Healthy Lifestyle, Diagnosis, Health Provider Choosing, Treatment, and Epidemiology. The results showed the average F1-scores of the above 6 topic identification were 99.63%, 99.13%, 98.55%, 96.35%, 76.02%, and 71.77%, respectively.
Diagnostic Machine Learning Models for Acute Abdominal Pain: Towards an e-Learning Tool for Medical Students
Authors: Khumrin Piyapong  , Ryan Anna  , Judd Terry  , Verspoor Karin
Published: February 2025

Computer-aided learning systems (e-learning systems) can help medical students gain more experience with diagnostic reasoning and decision making. Within this context, providing feedback that matches students' needs (i.e. personalised feedback) is both critical and challenging. In this paper, we describe the development of a machine learning model to support medical students' diagnostic decisions. Machine learning models were trained on 208 clinical cases presenting with abdominal pain, to predict five diagnoses. We assessed which of these models are likely to be most effective for use in an e-learning tool that allows students to interact with a virtual patient. The broader goal is to utilise these models to generate personalised feedback based on the specific patient information requested by students and their active diagnostic hypotheses.
Uncovering Hidden Topics in Hong Kong Clinical Research Through Hospital Authority Convention Publications
Authors: Wong Zoie Shui-Yee  , Chan Wai-Man  , Wong Eliza Lai-Yi  , Chau Patsy Yuen-Kwan  , Tsui Kwok-Leung  , Fung Hong
Published: February 2025

Uncovering clinical research trends allows us to understand the direction of healthcare services and is essential for longer-term healthcare planning. The Hospital Authority Convention is a mainstream annual healthcare conference that gathers up-to-date Hong Kong medical research. We propose to use state-of-the-art medical document mining and topic modelling methods to uncover latent themes and structures in the publications. We collected 742 articles from HA Convention from the year 2013 to 2016 and selected 56 publications from the category of “Clinical Safety and Quality Service” for further analysis. Applying natural language processing and Latent Dirichlet Allocation (LDA) methods, we identified 7 potential topics, namely: surgical operation, hospital discharge, medical error, nursing procedure, service performance assessment, patient and staff engagement, and admission algorithm and standardisation. This exploratory study demonstrates that key themes exist in the annual HA Convention and we observe potential changes in healthcare services focus over the years in the selected category.
Assessing Provider-Generated Free-Text Quality in EHR-Integrated Handoff Notes
Authors: Arsoniadis Elliot G.  , Skube Steven J.  , Bjerke Treva M.  , Jarabek Bryan  , Melton Genevieve B.
Published: February 2025

Handoff notes are increasingly integrated within electronic health record (EHR) systems and often contain data automatically generated from the EHR and free-text narratives. We examined the quality of data entered by providers in the free-text portion of our institutional EHR handoff tool. Overall, 65% of handoff notes contained at least one error (average 1.7 errors per note). Most errors were omissions in information around patient plan/management or assessment/diagnosis rather than entry of false data. Factors associated with increased error rate were increasing hospital day number; weekend note; medical (vs. surgical) service team; and authorship by a medical student, first or fourth year resident physician, or attending physician. Our findings suggest that errors are common in handoff notes, and while these errors are not completely false data, they may provide individuals caring for patients an inaccurate understanding of patient status.
Two Years of ePrescription in Slovenia – Applications and Potentials
Authors: Stanimirovic Dalibor  , Savic Dusan
Published: February 2025

ePrescription is one of the most successful eHealth solutions in Slovenia. Since its national roll-out in early 2016, the quality of its operations has been constantly improving, and the number of users has been growing ever since to reach today's 90% of all healthcare providers. ePrescription facilitates more transparent and safer prescribing of medications, an overview of possible medication interactions, and reduction of administrative and opportunity costs. This paper initially explores the current state of ePrescription in Slovenia and different aspects of its application. Based on the research findings, the paper finally outlines potentials of ePrescription, which could be transformed into tangible benefits with particular implications for healthcare system. The research is based on focus group methodology. Structured discussions were conducted with eminent experts currently in charge of ePrescription (and other eHealth solutions) development and implementation in Slovenia. Research results imply that certain application aspects are relatively easy to define and evaluate, while the overall potentials of ePrescription are difficult to determine in many cases, and relatively unexplored in terms of their implications and operational feasibility.
Improving Hospital Services Based on Patient Experience Data: Current Feedback Practices and Future Opportunities
Authors: Kaipio Johanna  , Stenhammar Hanna  , Immonen Susanna  , Litovuo Lauri  , Axelsson Minja  , Lantto Minna  , Lahdenne Pekka
Published: February 2025

Patient feedback is considered important for healthcare organizations. However, measurement and analysis of patient reported data is useful only if gathered insights are transformed into actions. This article focuses on gathering and utilization of patient experience data at hospitals with the aim of supporting the development of patient-centered services. The study was designed to explore both current practices of collecting and utilizing patient feedback at hospitals as well as future feedback-related opportunities. Nine people working at different hierarchical levels of three university hospitals in Finland participated in in-depth interviews. Findings indicate that current feedback processes are poorly planned and inflexible. Some feedback data are gathered, but not systematically utilized. Currently, it is difficult to obtain a comprehensive picture of the situation. One future hope was to increase the amount of patient feedback to be able to better generalize and utilize the data. Based on the findings the following recommendations are given: attention to both patients' and healthcare staff's perspectives when collecting feedback, employing a coordinated approach for collecting and utilizing patient feedback, and organizational transformation towards a patient-centric culture.
Reducing Nosocomial Infections in Surgical ICUs in Sri Lanka: Co-Creating a Safety Culture Using an eHealth Intervention
Authors: Kariyawasam Nadish  , Wong Ming Chao  , Turner Paul
Published: February 2025

Nosocomial infections are a major public health risk more prevalent among vulnerable patients in intensive care units of lower and lower-middle income countries. Despite advances in health care, the prevalence of nosocomial infections is alarming. The reasons for these infections are multifactorial and include organisational, cultural and individual factors. This paper discusses the findings associated with research undertaken in six surgical intensive care units in Sri Lanka to evaluate the impact of an eHealth system prototype in contributing to the improvement of hand hygiene compliance and thereby reduction of nosocomial infections. Key findings include the necessity of reconsidering the way of calculating nosocomial infection rates, the importance of coupling interventions to feedbacks on outcomes and the role of the leaders as role models in inculcating positive behaviours.
Clinical Similarity Based Framework for Hospital Medical Supplies Utilization Anomaly Detection: A Case Study
Authors: Sun Ning  , Xu Meilin  , Cai Mingzhi  , Ma Xudong  , Qin Yong
Published: February 2025

Healthcare systems are costly in many countries, and hospitals have always been one of the major cornerstones of the healthcare industry. Medical supplies expense is an increasingly substantial category of hospital costs. In China, the expense of medical supplies is being controlled at the hospital level. Different from drug prescription, medical supplies utilization is not being standardized or guided by clinical guidelines. In order to achieve the goal, many hospitals directly disable the use of the most expensive medical supplies. One missing piece in consideration is the patient heterogeneity, which decides the medical necessity for a specific surgery/procedure and the associated medical supplies requirement. The other challenge is to justify the substitutability of the medical supplies being replaced. In this study, we explore a clinical similarity based framework to analyze the inpatient medical supplies use records and detect unnecessary utilization. More specifically, the inpatient stays are clustered based on patients' clinical conditions. After clustering, inpatient cases within each sub-group should have similar clinical necessities and therefore similar medical supplies utilization patterns. Thus the unnecessary medical utilization can be identified and the cost reduction suggestions can be provided accordingly. This framework will be illustrated though a case study of 3-year inpatient records from a Chinese hospital.
Architecture and Initial Development of a Knowledge-as-a-Service Activator for Computable Knowledge Objects for Health
Authors: Flynn Allen J.  , Boisvert Peter  , Gittlen Nate  , Gross Colin  , Iott Brad  , Lagoze Carl  , Meng George  , Friedman Charles P.
Published: February 2025

The Knowledge Grid (KGrid) is a research and development program toward infrastructure capable of greatly decreasing latency between the publication of new biomedical knowledge and its widespread uptake into practice. KGrid comprises digital knowledge objects, an online Library to store them, and an Activator that uses them to provide Knowledge-as-a-Service (KaaS). KGrid's Activator enables computable biomedical knowledge, held in knowledge objects, to be rapidly deployed at Internet-scale in cloud computing environments for improved health. Here we present the Activator, its system architecture and primary functions.
Evaluation of the Technology Acceptance of a Collaborative Documentation System for Addiction Therapists and Clients
Authors: Perlich Anja  , Meinel Christoph  , Zeis Daniel
Published: February 2025

Addiction treatment outcomes are strongly determined by relational factors. We present the interactive documentation system Tele-Board MED (TBM) developed as an adjunct to therapy sessions aimed at enhancing the therapeutic alliance and patient empowerment. The objective of this work is to find factors that predict the acceptance of TBM in face-to-face addiction treatment sessions. We combined the methodologies of survey and focus group and based the data collection and analysis on the Unified Theory of Acceptance and Use of Technology. The studies, which involved therapists (n=13) and clients (n=33), were conducted in an addiction counselling center in Germany. Therapists see a flexible, context-dependent usage as a basic condition for TBM acceptance and its greatest benefit in providing a discussion framework and quick access to worksheets—in both individual and group sessions. Clients are inclined to use the system with the expectation of improved communication and better recall of the discussed topics based on a personal copy of the session notes.
Addressing the Socio-Technical Challenges of Health Information Exchange Adoption: DataWell in Greater Manchester
Authors: Thew Sarah  , Leeming Gary  , Ainsworth John
Published: February 2025

Several high profile, problematic UK health data-sharing projects have shaped NHS professionals' and the public's opinion about NHS data-sharing projects, and there is a substantial body of evidence identifying barriers to Health Information Exchange (HIE) adoption. Socio-technical factors are a significant consideration and this paper describes the approach taken to address these concerns in the design and implementation of a HIE for Greater Manchester.
A Predictive Model for Acute Admission in Aged Population
Authors: Mansourvar Marjan  , Andersen-Ranberg Karen  , Nøhr Christian  , Kock Wiil Uffe
Published: February 2025

Acute hospital admission among the elderly population is very common and have a high impact on the health services and the community, as well as on the individuals. Several studies have focused on the possible risk factors, however, predicting who is at risk for acute hospitalization associated with disease and symptoms is still an open research question. In this study, we investigate the use of machine learning algorithms for predicting acute admission in older people based on admission data from individual citizens 70 years and older who were hospitalized in the acute medical unit of Svendborg Hospital in Denmark.
An Information System Design for Emergency Department Overcrowding Assessment
Authors: Zhuang Yiqing  , Chen Xu  , Ge Xiaohua
Published: February 2025

This poster proposes an informatics report system designed to estimate the readiness of Emergency Departments (ED) to overcrowing and readiness of a real-time usage of medical response. This system can be installed with the applications on all kinds of electronic devices approved by the hospital. A automatically system generated electronic report can clearly and organized demonstrate the condition of ED, and offer the data to inform healthcare managers on decision making, and more importantly, improve the patient outcomes.
Development of MyPEEPS Mobile: A Behavioral Health Intervention for Young Men
Authors: Schnall Rebecca  , Kuhns Lisa  , Hidalgo Marco  , Hirshfield Sabina  , Pearson Cynthia  , Radix Asa  , Belkind Uri  , Bruce Joshua  , Batey D. Scott  , Garofalo Robert
Published: February 2025

The MyPEEPS Mobile intervention is a novel evidence-driven intervention using mobile technology to deliver HIV prevention information. This is the first study to test the efficacy of a scaled-up, mobile version of an existing HIV prevention intervention originally developed, designed, and piloted for, a diverse group of YMSM. We used an iterative design process incorporating feedback from experts and end-users to update the user-interface and content of the MyPEEPS Mobile Intervention.
Internet Well-Being in Adolescents: A Concept Analysis
Authors: Jo Soojung  , Chen Angela Chia-Chen
Published: February 2025

This paper aimed to analyze the concept “internet well-being in adolescents” using Walker and Avant's method. We analyzed concept use, it's attributes, antecedents, and consequences. We identified three attributes (e.g., self-help), three antecedents (e.g., internet access), and four consequences (e.g., feeling safe on the internet). This concept analysis will help guide developing effective interventions for adolescents.
A Framework Facilitates Development of a Mobile App
Authors: Choi Jeeyae  , Baker Elizabeth  , Nalawade Swanand  , Peacock Anna  , Lee Hanjoo  , Choi Woo Jung
Published: February 2025

Due to the advance of mobile technology, use of mobile devices such as smartphones has been growing rapidly in the U.S. and worldwide. Many health related mobile apps have been developed for care professionals and patients as well. However, studies indicate that there is a gap between science and commercially developed mobile apps. In addition to this, there is no framework to guide devlopment of a mobile app to overcome many challenges and obstacles. Through the development of a pain management mobile app for cancer patients, a framework was developed. A proposed framework was based on the technology acceptance model, ensuring usefulness and ease of use for end users. The first two steps in the framework enforce accurate knowledge translation and communication to build a science based mobile app. Iterative decisions points between steps enhance accomplishment of each step.
Automatic Detection of Depression by Using a Neural Network
Authors: Raeiati Banadkooki Mahsa  , Mielke Corinna  , Wolf Klaus-Hendrik  , Haux Reinhold  , Marschollek Michael
Published: February 2025

Depression is the most common psychiatric disorder worldwide, which affects more than 300 million people. We aimed to detect depressed patients and healthy people automatically. We work on the PHQ-9 questionnaires and reduced it to a PHQ-5 questionnaires with a new cut-off value of 8 to detect depressed patients. We trained a Neural Network with 70% of our dataset. Then, the proposed classifier was tested with two datasets. The first one consists of 30% of PHQ-5 datasets, which could achieve 85.69%, 99.11% and 90.56% for accuracy, sensitivity and specificity respectively. The second test dataset consists of physical patient's parameters which recorded during a study in the Hanover Medical School. This classifier has shown good results in the detection of depression based on these two datasets.
Deploying Cloud Computing in the Greek Healthcare System: A Modern Development Proposal Incorporating Clinical and Laboratory Data
Authors: Nikolopoulos Markos  , Karampela Irene  , Tzortzis Evangelos  , Dalamaga Maria
Published: February 2025

Cloud computing is a reality in most business sectors. Hospitals have been more reluctant to adopt cloud technology due to strict data security regulations. Cloud could provide economies of scale reducing Information Technology spending in the Greek state-owned hospitals, while giving the opportunity to the hospitals to upgrade their profile offering web-based services. We propose a simple, robust and easy to apply approach for the Greek hospitals, focusing on clinical and laboratory data in order to move to the cloud environment. To the best of our knowledge, there is no other study regarding the adoption of cloud infrastructure in the Greek hospital sector. This innovative method could transform the business model of the hospitals.
An Approach for Dynamic Vital Parameter Monitoring – Prototype Development
Authors: Schweitzer Marco  , Huber Lukas  , Gorfer Thilo  , Hörbst Alexander
Published: February 2025

The alpine space is characterized with rural regions, often hard to reach for mobile care. As part of the EU-funded INTESI project, a mobile platform for vital sign self-monitoring for patients who receive mobile care was developed. Based on a thorough analysis of user requirements and available technology a platform was established, that integrates several Bluetooth low energy devices for measuring vital signs. The developed VITAMO app further enables clients and nurses to easily govern measurements and jointly take control of a client's health during the care process. In addition, the system supports the communication of clients and nurses electronically. The internal data structure adheres to current healthcare standards e.g. FHIR and offers easy interfaces for future applications. The complete system was applied in a pilot study and got formally evaluated.
On the Representation of Machine Learning Results for Delirium Prediction in a Hospital Information System in Routine Care
Authors: Veeranki Sai  , Hayn Dieter  , Eggerth Alphons  , Jauk Stefanie  , Kramer Diether  , Leodolter Werner  , Schreier Günter
Published: February 2025

Digitalisation of health care for the purpose of medical documentation lead to huge amounts of data, hence having an opportunity to derive knowledge and associations of different attributes recorded. Many health care events can be prevented when identified. Machine learning algorithms could identify such events but there is ambiguity in understanding the suggestions especially in clinical setup. In this paper we are presenting how we explain the decision based on random forest to health care professionals in the course of the project predicting delirium during hospitalisation on the day of admission.
Ambulance Arrivals and ED Flow – A Queensland Perspective
Authors: Khanna Sankalp  , Boyle Justin  , Bosley Emma  , Lind James
Published: February 2025

While it is widely accepted that whole of hospital solutions are necessary to reduce the ever-increasing burden on the public health system, little research has focussed on understanding the relationship between ambulance arrival related flow metrics and emergency department (ED) crowding. Queensland Ambulance Service (QAS) shares patient load across multiple hospitals, and receiving facilities strive to meet a Patient Off Stretcher Time (POST) target of 30 minutes. We examine ambulance arrival data from the QAS and ED patient arrival data from 15 major metropolitan hospitals across Queensland, to understand temporal variations in POST performance and examine the relationship between POST performance and ED crowding. The findings suggest a relationship between ED occupancy levels and both ambulances waiting at the ED door and average POST at larger hospitals. No relationship between POST and ED length of stay was found, perhaps due to competing ED National Emergency Access Targets (NEAT). Further modelling is recommended to formally test these observations.
Experts' Insights into eHealth-Legislation: Comparing Switzerland and Germany
Authors: Naumann Laura  , Babitsch Birgit  , Hübner Ursula
Published: February 2025

This prospective longitudinal study aims at better understanding eHealth success factors in different European nations, esp. the role of eHealth-legislation in Switzerland and Germany. Qualitative interviews with 39 matched experts from a large variety of institutions in both nations were conducted. The individual statements in the interviews and the overall satisfaction rating indicate a clear trend for a more optimistic attitude towards the law in Switzerland than in Germany. This result is not surprising given the history of a telematics infrastructure in Germany. Cross-country learning topics for German politicians are the inclusion of the inpatient sector and the focus on one major application. In a next step, interview results from Austria will be included and with that the scope of study findings enriched.
De-Identification of German Medical Admission Notes
Authors: Richter-Pechanski Phillip  , Riezler Stefan  , Dieterich Christoph
Published: February 2025

Medical texts are a vast resource for medical and computational research. In contrast to newswire or wikipedia texts medical texts need to be de-identified before making them accessible to a wider NLP research community. We created a prototype for German medical text de-identification and named entity recognition using a three-step approach. First, we used well known rule-based models based on regular expressions and gazetteers, second we used a spelling variant detector based on Levenshtein distance, exploiting the fact that the medical texts contain semi-structured headers including sensible personal data, and third we trained a named entity recognition model on out of domain data to add statistical capabilities to our prototype. Using a baseline based on regular expressions and gazetteers we could improve F2-score from 78% to 85% for de-identification. Our prototype is a first step for further research on German medical text de-identification and could show that using spelling variant detection and out of domain trained statistical models can improve de-identification performance significantly.
OSSE Goes FAIR – Implementation of the FAIR Data Principles for an Open-Source Registry for Rare Diseases
Authors: Schaaf Jannik  , Kadioglu Dennis  , Goebel Jens  , Behrendt Christian-Alexander  , Roos Marco  , van Enckevort David  , Ückert Frank  , Sadiku Fatlume  , Wagner Thomas O.F.  , Storf Holger
Published: February 2025

The Open Source Registry for Rare Diseases (OSSE) provides a concept and a software for the management of registries for patients with rare diseases. A disease is defined as rare if less than 5 out of 10,000 people are affected. Up to date, approximately 6,000 rare diseases are catalogued. Networking and data exchange for research purposes remains challenging due to the paucity of interoperability and due to the fact that small data stocks are stored locally. The so called “Findable, Accessible, Interoperable, Reusable” (FAIR) Data Principles have been developed to improve research in the field of rare diseases. Subsequently, the OSSE architecture was adapted to implement the FAIR Data Principles. Therefore, the so-called FAIR Data Point was integrated into OSSE to provide a description of metadata in a FAIR manner. OSSE relies on the existing metadata repository (MDR), which is used in to define data elements in the system. This is an important step towards unified documentation across multiple registries. The integration and use of new procedures to improve interoperability plays an important role in the context of registries for rare diseases.
A Web Service to Suggest Semantic Codes Based on the MDM-Portal
Authors: Hegselmann Stefan  , Storck Michael  , Geßner Sophia  , Neuhaus Philipp  , Varghese Julian  , Dugas Martin
Published: February 2025

Annotation with semantic codes helps to overcome interoperability issues for electronic documentation in medicine. However, the manual annotation process is laborious and semantic codes are ambiguous. We developed a publicly accessible web service to alleviate these drawbacks with a sophisticated and fast search mechanism based on more than 330,000 semantic code suggestions. These suggestions are derived from semantically annotated data elements contained in the Portal of Medical Data Models manually curated by medical professionals. Integrating this suggestion service can support the manual annotation process and strengthen uniform coding. Integration is demonstrated for two separate data model editors. Usage statistics show over 5,500 suggestion requests per month for semantic annotation of items. The web service may also prove helpful for automatic semantic coding.
Methodologies for Improving the Quality and Safety of Telehealth Systems
Authors: Borycki Elizabeth M.  , Kushniruk Andre W.
Published: February 2025

A range of telehealth applications have been developed. In Canada, telehealth shows considerable promise given the country's large geographical area and need for support in rural areas. In this paper, the authors describe our method for ensuring the quality and safety of telehealth applications by applying clinical simulations. These simulations allow for testing and fine-tuning of telehealth applications before they are released on a large scale. Two applications are briefly described, one involving tele-triage and a second involving tele-nursing. The potential of the approach is discussed along with considerations in its application to ensure the quality and safety of telehealth technologies.
Data Reuse Through Anesthesia Data Warehouse: Searching for New Use Contexts
Authors: Lamer Antoine  , Demay Anaïs  , Marcilly Romaric
Published: February 2025

Introduction: Due to high volumes of data routinely recorded through Hospital Information System, data reuse has become important in recent years. A data warehouse was developed in the Lille University Hospital to reuse anesthesia data. At the moment, it is mainly used for clinical research, by offering extraction of data tables to answer a clinical question. In this article, we try to identify other contexts of data reuse than the one currently provided by the data warehouse, in comparison with those in the literature.
Towards a Decision Support System for Improved Accessibility in Multi-Family Housing: Co-Design of an Application for Environmental Barrier Inventory
Authors: Jonsson Oskar  , Slaug Björn  , Mårtensson Knut  , Hansson Adrian  , Schmidt Steven M.  , Iwarsson Susanne
Published: February 2025

The demand for accessible housing is increasing. More people are expected to live longer and live more years with reduced functional capacity in ordinary multi-family housing. To address this, detailed knowledge of accessibility problems in the existing housing stock and systems that could contribute to efficient collaboration between housing industry and authorities concerned is needed. This paper introduces a project with the overarching aim to develop and evaluate a new decision support system (DSS) to inventory and support decision-making for improved accessibility in multi-family housing in Sweden. The specific aim is to describe the initial app development phase and to investigate the design-team interactions and their impact on the outcome. The app will constitute the core part of the new DSS. This phase involved co-design to fit the practice context at target and meet users' needs and expectations. The co-design process served to identify user requirements to guide the development. Housing Enabler (an internationally acknowledged instrument for assessment and analysis of accessibility problems) was the methodological starting point. The prototype app enables professional inventory of environmental barriers and registration of subsequent work for accessibility improvements. A fully functional prototype of an app including an example apartment database is ready for usability studies and further iterative refinements.
Applying Learning: Student Experience of Research Skills Module
Authors: Mc Donnell Sorca
Published: February 2025

Social Care students undertake a research methods module with a focus on quantitative methods. A core aim of the module is for students to develop their research skills by applying them to a project. This paper will explore the student experience of engaging in this process and the impact on their learning and skill development. The impact on the students' engagement in the exploration of ethical issues and critical thinking is also explored. Bloom (1956) [2] emphasises the key ways that learning happens, with higher levels focusing on Application, Analysis and Synthesis. This research explores the extent to which completing a continuous assessment project, applying research, may impact on student skill development and learning. Links are made to social constructivism and the impact on learning. The research methodology used is a quantitative approach involving an online survey of students who have engaged in the module. Ethical considerations were carefully applied including informed consent, confidentiality and anonymity. The findings highlight the participant's view of the impact of the research project on their knowledge and skill development.
Towards a Universal Design Evaluation for Assessing the Performance of the Built Environment
Authors: Mosca Erica Isa  , Capolongo Stefano
Published: February 2025

Universal Design is a recent and innovative strategy aimed at designing spaces that are as accessible and inclusive as possible. It considers the broadest range of users, and goes beyond the prescriptive approach of accessibility legislation. Theoretical research on this strategy is currently increasing, but the reliability of its principles remains limited in design practice and it struggles to guarantee performance-based knowledge to designers. Therefore, a practical evaluation method based on reliable performance criteria is required.
Early Usability Assessment of a Conversational Agent for HPV Vaccination
Authors: Amith Muhammad  , Zhu Anna  , Cunningham Rachel  , Lin Rebecca  , Savas Lara  , Shay Laura  , Chen Yong  , Gong Yang  , Boom Julie  , Roberts Kirk  , Tao Cui
Published: February 2025

With the emerging use of speech technology in consumer goods, we experimented with the application of conversational agents for the communication of health information relating to HPV vaccine. Research have stated that one-to-one contact between providers and patients have a variety of positive influences on patients' perception towards vaccines, even leading to uptake, compared to paper-based methods. We implemented a Wizard of Oz experiment that counsels adults with children (n=18) on the HPV vaccine, using an iPad tablet and dialogue script developed by public health collaborators, and for early testing of a prospective conversational agent in this area. Our early results show that non-vaccine hesitant parents believed that agent was easy to use and had capabilities needed, despite the desire for additional features. Our future work will involve developing a dialogue engine to provide automated dialogue interaction and future improvements and experimentation for the speech interface.