bluuebunny/crossref_metadata_2025 huggingface dataset:
Methods for Detecting Malfunctions in Clinical Decision Support Systems
Authors: Wright Adam  , Hickman Trang T.  , McEvoy Dustin  , Aaron Skye  , Ai Angela  , Ash Joan S.  , Andersen Jan Marie  , Ramoni Rachel  , Hauskrecht Milos  , Embi Peter  , Schreiber Richard  , Sittig Dean F.  , Bates David W.
Published: February 2025

Clinical decision support systems, when used effectively, can improve the quality of care. However, such systems can malfunction, and these malfunctions can be difficult to detect. In this poster, we describe four methods of detecting and resolving issues with clinical decision support: 1) statistical anomaly detection, 2) visual analytics and dashboards, 3) user feedback analysis, 4) taxonomization of failure modes/effects.
Development of Parkinson Patient Generated Data Collection Platform Using FHIR and IoT Devices
Authors: Kim Dae-Young  , Hwang Sun-ho  , Kim Min-Gyu  , Song Joon-Hyun  , Lee Sin-Woong  , Kim Il Kon
Published: February 2025

Internet of Things (IoT) devices can be effectively used in cases where continuous observation of patients is required, such as Parkinson's disease. This is due to the characteristics of the IoT (Internet of Things), which allows data to be measured and transmitted at any time, anywhere. In this study, we developed a health data collection platform that stores and transmits the foot pressure data of Parkinson patients using FHIR (Fast Healthcare Interoperability Resources). The platform can be used to collect the foot pressure of a large number of Parkinson's patients. Based on the accumulated data, it is possible to identify abnormal behaviors such as walking pattern, tilt and instability of stride length in patients with Parkinson's disease. Based on the results of this study, accurate diagnosis and treatment of Parkinson's disease can be made.
Developing a Mobile Wellness Management System for Healthy Lifestyle by Analyzing Daily Living Activities
Authors: Lim Chae-Gyun  , Kim Zae Myung  , Choi Ho-Jin
Published: February 2025

It is important to protect health and improve quality of life for people, without causing them inconvenience in today's world. Since most people are living a busy life dealing with various activities at work, school, or home, there is a need for systematic analysis of their life patterns. However, since person's life patterns could change depending on ambient environmental factors, an effective management scheme to specify one's state is required. We propose a method, in this paper, to support and enhance the personal healthy life patterns by analyzing the daily life data that has been continuously recorded by wearable sensors, such as activity trackers. We implement a mobile wellness management system by learning RNN-based user's lifestyle model, and developing behavior recommendation using greedy policy. We also consider user context and feedback to personalize each user's lifestyle.
The Study of Smartphone Usage Competency Assessment and Training for the Elderly
Authors: Lu Sheng-Chieh  , Wen Tzu-Ning  , Chang Po-Lun
Published: February 2025

This study aimed at developing an assessment of smartphone usage competence and constructing a training program for the elderly. A list of smartphone usage competencies with 34 items was defined through expert survey and panel. Based on the competence and previous literature, a training program and learning aids were designed in this study. There were 41 participants in our program. The results of self-administrated smartphone usage ability questionnaire indicated that all competencies were significantly improved after training. However, the results also demonstrated that some items were still difficult for the elderly to comprehend. Overall, this study provided a first exploration of defining smartphone usage competency and built a training program for the elderly. With strong suggestion, future mobile health (mHealth) services can follow this study to insure the smartphone usage ability of the elderly.
Are Health Literacy and eHealth Literacy the Same or Different?
Authors: Monkman Helen  , Kushniruk Andre W.  , Barnett Jeff  , Borycki Elizabeth M.  , Greiner Leigh E.  , Sheets Debra
Published: February 2025

Many researchers assume that there is a relationship between health literacy and eHealth literacy, yet it is not clear whether the literature supports this assumption. The purpose of this study was to determine if there was a relationship between health and eHealth literacy. To this end, participants' (n = 36) scores on the Newest Vital Sign (NVS, a health literacy measure) were correlated with the eHealth Literacy Scale (eHEALS, an eHealth literacy measure). This analysis revealed no relationship (r = −.041, p = .81) between the two variables. This finding suggests that eHealth Literacy and health literacy are dissimilar. Several possible explanations of the pattern of results are proposed. Currently, it does not seem prudent to use the eHEALS as the sole measure of eHealth literacy, but rather researchers should continue to complement it with a validated health literacy screening tool.
Acceptance of Using an Ecosystem of Mobile Apps for Use in Diabetes Clinic for Self-Management of Gestational Diabetes Mellitus
Authors: Pais Sarita  , Parry Dave  , Petrova Krassie  , Rowan Janet
Published: February 2025

Mobile applications (apps) for self-management of diseases such as diabetes and for general well-being, including keeping track of food, diet, and exercise, are widely available. However, consumers face a flood of new mobile apps in the app stores and have no guidance from clinicians about choosing the appropriate app. As much as clinicians would like to support a patient-centered approach and promote health and wellness mobile apps, they may be unable to provide advice due to the lack of comprehensive and reliable app reviews. This research reviewed a selection of health and wellness mobile apps suitable for the self-management of gestational diabetes mellitus (GDM). A prototype of an ecosystem that integrated the data generated by the apps was built and its usefulness and ease of use were evaluated. The results show that the ecosystem can provide support for GDM self-management by sharing health and wellness data across the diabetes clinic.
Mobile Application for Pregnant Women: What Do Mothers Say?
Authors: Sommer Janine  , Daus Mariana  , Smith María  , Luna Daniel
Published: February 2025

Today, health information technologies are constantly expanding and changing, allowing more and more people to use different mobile applications to receive information and control their health condition. Based on the need to implement an application for pregnant women in the Personal Health Record (PHR) of Hospital Italiano de Buenos Aires (HIBA), an Australian survey was carried out to measure the use and utility of a pregnancy application (pregnancy app). Our results were broadly in agreement with the reference values. The survey was distributed through social networks (Facebook and Twitter) during September 2016. We obtained 235 responses from Spanish-speaking women, mostly Argentinian. In conclusion, it could be observed that a pregnancy app offers the possibility of a greater follow-up and provides reassurance to the pregnant women who use it.
MedEx/J: A One-Scan Simple and Fast NLP Tool for Japanese Clinical Texts
Authors: Aramaki Eiji  , Yano Ken  , Wakamiya Shoko
Published: February 2025

Because of recent replacement of physical documents with electronic medical records (EMR), the importance of information processing in the medical field has increased. In light of this trend, we have been developing MedEx/J, which retrieves important Japanese language information from medical reports. MedEx/J executes two tasks simultaneously: (1) term extraction, and (2) positive and negative event classification. We designate this approach as a one-scan approach, providing simplicity of systems and reasonable accuracy. MedEx/J performance on the two tasks is described herein: (1) term extraction (Fβ = 1= 0.87) and (2) positive–negative classification (Fβ = 1= 0.63). This paper also presents discussion and explains remaining issues in the medical natural language processing field.
Detecting Protected Health Information in Heterogeneous Clinical Notes
Authors: Henriksson Aron  , Kvist Maria  , Dalianis Hercules
Published: February 2025

To enable secondary use of healthcare data in a privacy-preserving manner, there is a need for methods capable of automatically identifying protected health information (PHI) in clinical text. To that end, learning predictive models from labeled examples has emerged as a promising alternative to rule-based systems. However, little is known about differences with respect to PHI prevalence in different types of clinical notes and how potential domain differences may affect the performance of predictive models trained on one particular type of note and applied to another. In this study, we analyze the performance of a predictive model trained on an existing PHI corpus of Swedish clinical notes and applied to a variety of clinical notes: written (i) in different clinical specialties, (ii) under different headings, and (iii) by persons in different professions. The results indicate that domain adaption is needed for effective detection of PHI in heterogeneous clinical notes.
Assessing Data Integration and Quality for the Evaluation of Point-of-Care Testing Across Rural and Remote Emergency Departments in Australia
Authors: Li Ling  , McCaughey Euan  , Iles-Mann Juliana  , Sargeant Andrew  , Dahm Maria R.  , Mumford Virginia  , Westbrook Johanna I.  , Georgiou Andrew
Published: February 2025

In Australia, New South Wales Health Pathology's implementation of managed Point-of-Care Testing (PoCT) services across rural and remote emergency departments (EDs) has the potential to significantly improve access to results for certain types of pathology laboratory tests and help to deliver timely patient care. The aim of this study was to assess the quality of the datasets, including the integration of PoCT results into clinical systems, as a precursor to the application of an evaluation framework for monitoring the delivery of PoCT services and their impact on patient care. Three datasets, including laboratory, ED presentations and hospital admissions data were extracted from the relevant clinical information systems. Each dataset was assessed on six dimensions: completeness, uniqueness, timeliness, validity, accuracy, and consistency. Data incompleteness was the largest problem. Assessing the PoCT data integration and data quality is a precondition for the evaluation of PoCT and for monitoring and improving service delivery.
Scholarly Information Extraction Is Going to Make a Quantum Leap with PubMed Central (PMC)
Authors: Matthies Franz  , Hahn Udo
Published: February 2025

With the increasing availability of complete full texts (journal articles), rather than their surrogates (titles, abstracts), as resources for text analytics, entirely new opportunities arise for information extraction and text mining from scholarly publications. Yet, we gathered evidence that a range of problems are encountered for full-text processing when biomedical text analytics simply reuse existing NLP pipelines which were developed on the basis of abstracts (rather than full texts). We conducted experiments with four different relation extraction engines all of which were top performers in previous BioNLP Event Extraction Challenges. We found that abstract-trained engines loose up to 6.6% F-score points when run on full-text data. Hence, the reuse of existing abstract-based NLP software in a full-text scenario is considered harmful because of heavy performance losses. Given the current lack of annotated full-text resources to train on, our study quantifies the price paid for this short cut.
Automated Evaluation System for Human Pupillary Behavior
Authors: Silva Cleyton Rafael Gomes  , Gonçalves Cristhiane  , Camilo Eduardo N.R.  , Boaretti dos Santos Fabio  , Siqueira Joyce  , de Albuquerque Eduardo Simões  , de Melo Nunes Soares Fabrízzio Alphonsus Alves  , de Oliveira Leandro Luís Galdino  , da Costa Ronaldo Martins
Published: February 2025

Analyzing human pupillary behavior is a non-invasive method for evaluating neurological activity. This method contributes to the medical field because changes in pupillary behavior can be correlated with several health conditions such as Parkinson, Alzheimer, autism and diabetes. Analyzing human pupillary behavior is simple and low-cost, and may be used as a complementary diagnosis. Therefore, this work aims to develop an automated system to evaluate human pupillary behavior. The solution consists of a portable recording device, a pupillometer; integrated with a recording and evaluation software based on computer vision. The system is able to stimulate, record, measure and extract relevant features of human pupillary behavior. The results show that the proposed system is fast and accurate, and can be used as an assessment tool for real and extensive clinical practice and research.
A Bayesian Network Model of Head and Neck Squamous Cell Carcinoma Incorporating Gene Expression Profiles
Authors: Wu Shuyang  , Law Anthony  , Whipple Mark E.
Published: February 2025

Radiation therapy allows precision targeting of certain groups of lymph nodes and is a treatment for metastatic head and neck squamous cell carcinoma. In current practice, there is approximately 15% probability that physicians inadvertently treat healthy tissue or leave the cancerous lymph nodes untreated. The aim of this work is to improve the accuracy of medical decision-making by extending existing predictive models to capture the probabilities of finding cancerous lymph nodes at each of the six image-based surgical neck level using a patient's genetic profile, primary tumor site and tumor size. Our model was trained with publicly available data extracted from the Cancer Genome Atlas (TCGA) and validated against the TCGA dataset both with and without genetic information. Results show that genetic profile data improves model accuracy. These findings suggest that our predictive model may improve the accuracy of clinical decision-making, especially for patients with more advanced metastasis. However, more data is needed to ensure significance of the proposed effects, as well as to improve accuracy of the overall model.
Tracking the Implementation of Electronic Medical Records in Dubai, United Arab Emirates, Using an Adoption Benchmarking Tool
Authors: El-Hassan Osama  , Sharif Amer  , Al Redha Mohammad  , Blair Iain
Published: February 2025

In the United Arab Emirates (UAE), health services have developed greatly in the past 40 years. To ensure they continue to meet the needs of the population, innovation and change are required including investment in a strong e-Health infrastructure with a single transferrable electronic patient record. In this paper, using the Emirate of Dubai as a case study, we report on the Middle East Electronic Medical Record Adoption Model (EMRAM). Between 2011–2016, the number of participating hospitals has increased from 23 to 33. Currently, while 20/33 of hospitals are at Stage 2 or less, 10/33 have reached Stage 5. Also Dubai's median EMRAM score in 2016 (2.5) was higher than the scores reported from Australia (2.2), New Zealand (2.3), Malaysia (0.06), the Philippines (0.06) and Thailand (0.5). EMRAM has allowed the tracking of the progress being made by healthcare facilities in Dubai towards upgrading their information technology infrastructure and the introduction of electronic medical records.
Retrofitting Concept Vector Representations of Medical Concepts to Improve Estimates of Semantic Similarity and Relatedness
Authors: Yu Zhiguo  , Wallace Byron C.  , Johnson Todd  , Cohen Trevor
Published: February 2025

Estimation of semantic similarity and relatedness between biomedical concepts has utility for many informatics applications. Automated methods fall into two categories: methods based on distributional statistics drawn from text corpora, and methods using the structure of existing knowledge resources. Methods in the former category disregard taxonomic structure, while those in the latter fail to consider semantically relevant empirical information. In this paper, we present a method that retrofits distributional context vector representations of biomedical concepts using structural information from the UMLS Metathesaurus, such that the similarity between vector representations of linked concepts is augmented. We evaluated it on the UMNSRS benchmark. Our results demonstrate that retrofitting of concept vector representations leads to better correlation with human raters for both similarity and relatedness, surpassing the best results reported to date. They also demonstrate a clear improvement in performance on this reference standard for retrofitted vector representations, as compared to those without retrofitting.
An Experimental Comparison of Quality Models for Health Data De-Identification
Authors: Eicher Johanna  , Kuhn Klaus A.  , Prasser Fabian
Published: February 2025

When individual-level health data are shared in biomedical research, the privacy of patients must be protected. This is typically achieved by data de-identification methods, which transform data in such a way that formal privacy requirements are met. In the process, it is important to minimize the loss of information to maintain data quality. Although several models have been proposed for measuring this aspect, it remains unclear which model is best suited for which application. We have therefore performed an extensive experimental comparison. We first implemented several common quality models into the ARX de-identification tool for biomedical data. We then used each model to de-identify a patient discharge dataset covering almost 4 million cases and outputs were analyzed to measure the impact of different quality models on real-world applications. Our results show that different models are best suited for specific applications, but that one model (Non-Uniform Entropy) is particularly well suited for general-purpose use.
Analysis of the Updated Swedish Regulatory Framework of the Patient Accessible Electronic Health Record in Relation to Usage Experience
Authors: Scandurra Isabella  , Pettersson Maria  , Eklund Benny  , Lyttkens Leif
Published: February 2025

In Sweden, all citizens can (in 2017) access their health data online from all county councils using one national eHealth service. However, depending on where the patient lives, different information is provided as care providers have assessed differently how to apply the National Regulatory Framework (NRF). The NRF recently was updated and this paper analyses version 2.0 should now serve as the guideline for all county councils. Potential improvements are analyzed in relation to patient experiences of using the service, and the rationale for each change in the NRF is discussed. Two real case quotations are used to illustrate potential implications for the patient when the new version is placed into operation. Results indicate that this NRF allows for opportunities to create a national eHealth service that better supports patient-centered care and improves health information outcome.
Augmented Reality in Nursing: Designing a Framework for a Technology Assessment
Authors: Wüller Hanna  , Garthaus Marcus  , Remmers Hartmut
Published: February 2025

During the last decade, research emphasized the wide range of possibilities of augmented reality (AR). At the same time, Information Technology usage in nursing increased. The question occurs if AR can have reasonable fields of application in nursing. Nursing hinges strongly on the emotional and physical relationship between patients and their nurses. This may lead to ethical conflicts while implementing AR leading to special challenges. Therefore the realization of a technology assessment (TA) seams to be reasonable. We designed a framework for a TA of AR in nursing through workshops with nursing scientists and practical partners. The framework is designed to address ethical aspects of AR in nursing through techno-ethical scenarios, a plausibility assessment, and a participatory approach.
Text Data Mining of Aged Care Accreditation Reports to Identify Risk Factors in Medication Management in Australian Residential Aged Care Homes
Authors: Jiang Tao  , Qian Siyu  , Hailey David  , Ma Jun  , Yu Ping
Published: February 2025

This study aimed to identify risk factors in medication management in Australian residential aged care (RAC) homes. Only 18 out of 3,607 RAC homes failed aged care accreditation standard in medication management between 7th March 2011 and 25th March 2015. Text data mining methods were used to analyse the reasons for failure. This led to the identification of 21 risk indicators for an RAC home to fail in medication management. These indicators were further grouped into ten themes. They are overall medication management, medication assessment, ordering, dispensing, storage, stock and disposal, administration, incident report, monitoring, staff and resident satisfaction. The top three risk factors are: “ineffective monitoring process” (18 homes), “noncompliance with professional standards and guidelines” (15 homes), and “resident dissatisfaction with overall medication management” (10 homes).
An Ontology-Based Approach to Estimate the Frequency of Rare Diseases in Narrative-Text Radiology Reports
Authors: Kahn Jr. Charles E.
Published: February 2025

This study sought to use ontology-based knowledge to identify patients with rare diseases and to estimate the frequency of those diseases in a large database of radiology reports. Natural language processing methods were applied to 12,377,743 narrarive-text radiology reports of 7,803,811 patients at an academic health system. Using knowledge from the Orphanet Rare Disease Ontology and Radiology Gamuts Ontology, 1,154 of 6,794 rare diseases (17.0%) were observed in a total of 237,840 patients (3.05%). Ninety of 2,129 diseases (4%) with known prevalence less than 1 per 1,000,000 were observed in the database, whereas 100 of 173 diseases (58%) with prevalence greater than 1 per 10,000 were observed; the difference was statistically significant (p < .00001). Automated ontology-based search of radiology reports can estimate the frequency of rare diseases, and those diseases with higher known prevalence were significantly more likely to appear in radiology reports.
Interoperability of Disease Concepts in Clinical and Research Ontologies: Contrasting Coverage and Structure in the Disease Ontology and SNOMED CT
Authors: Raje Satyajeet  , Bodenreider Olivier
Published: February 2025

Objectives. To contrast the coverage of diseases between the Disease Ontology (DO) and SNOMED CT, and to compare the hierarchical structure of the two ontologies.
An OMOP CDM-Based Relational Database of Clinical Research Eligibility Criteria
Authors: Si Yuqi  , Weng Chunhua
Published: February 2025

Eligibility criteria are important for clinical research protocols or clinical practice guidelines for determining who qualify for studies and to whom clinical evidence is applicable, but the free-text format is not amenable for computational processing. In this paper, we described a practical method for transforming free-text clinical research eligibility criteria of Alzheimer's clinical trials into a structured relational database compliant with standards for medical terminologies and clinical data models. We utilized a hybrid natural language processing system and a concept normalization tool to extract medical terms in clinical research eligibility criteria and represent them using the OMOP Common Data Model (CDM) v5. We created a database schema design to store syntactic relations to facilitate efficient cohort queries. We further discussed the potential of applying this method to trials on other diseases and the promise of using it to accelerate clinical research with electronic health records.
Formalizing Evidence Type Definitions for Drug-Drug Interaction Studies to Improve Evidence Base Curation
Authors: Utecht Joseph  , Brochhausen Mathias  , Judkins John  , Schneider Jodi  , Boyce Richard D.
Published: February 2025

In this research we aim to demonstrate that an ontology-based system can categorize potential drug-drug interaction (PDDI) evidence items into complex types based on a small set of simple questions. Such a method could increase the transparency and reliability of PDDI evidence evaluation, while also reducing the variations in content and seriousness ratings present in PDDI knowledge bases. We extended the DIDEO ontology with 44 formal evidence type definitions. We then manually annotated the evidence types of 30 evidence items. We tested an RDF/OWL representation of answers to a small number of simple questions about each of these 30 evidence items and showed that automatic inference can determine the detailed evidence types based on this small number of simpler questions. These results show proof-of-concept for a decision support infrastructure that frees the evidence evaluator from mastering relatively complex written evidence type definitions.
The Role of Beta Conversion in Functional Programming
Authors: Menšík Marek  , Duží Marie  , Kermaschek Jakub
Published: February 2025

The paper deals with the fundamental computational rule of functional programming languages, namely the rule of beta conversion. This rule specifies the way in which a function f is applied to its argument a. There are two possible ways of executing the conversion, to wit ‘by name’ and ‘by value’. It has been proved that these two ways are not operationally equivalent, and, which is worse, the execution by name is not a denotationally equivalent transformation in the logic of partial functions. Since Transparent Intensional Logic (TIL) is a partial, typed lambda calculus, we examine the validity of the rule in TIL, or rather in its computational variant the TIL-Script language. We show that there are contexts in which the rule by name can be validly applied. The main result is the specification of such contexts, and comparison with the reduction by value. To this end, we present a tool that recognizes a context in which a formal parameter of a given calling procedure occurs and interactively navigates the user to a correct way of reduction. In case of an invalid way the program informs the user about the problem and warns against undesirable side effects. As a result, the program proposes to execute the rule by value.
Prediction of Freezing of Gait in Patients with Parkinson's Disease Using EEG Signals
Authors: Handojoseno A.M. Ardi  , Naik Ganesh R.  , Gilat Moran  , Shine James M.  , Nguyen Tuan N.  , Ly Quynh T.  , Lewis Simon J.G.  , Nguyen Hung T.
Published: February 2025

Freezing of gait (FOG) is an episodic gait disturbance affecting initiation and continuation of locomotion in many Parkinson's disease (PD) patients, causing falls and a poor quality of life. FOG can be experienced on turning and start hesitation, passing through doorways or crowded areas dual tasking, and in stressful situations. Electroencephalography (EEG) offers an innovative technique that may be able to effectively foresee an impending FOG. From data of 16 PD patients, using directed transfer function (DTF) and independent component analysis (ICA) as data pre-processing, and an optimal Bayesian neural network as a predictor of a transition of 5 seconds before the impending FOG occurs in 11 in-group PD patients, we achieved sensitivity and specificity of 85.86% and 80.25% respectively in the test set (5 out-group PD patients). This study therefore contributes to the development of a non-invasive device to prevent freezing of gait in PD.
Caring for Carers of People with Dementia: A Protocol for Harnessing Innovation Through Deploying Leading Edge Technologies to Enable Virtual Support Groups and Services
Authors: Parkinson Lynne  , Banbury Annie  , Livingstone Anne  , Gordon Steven  , Ray Biplob  , Byrne Louise  , Nancarrow Susan  , Doran Chris  , McAllister Margaret  , Petersen Carrie  , Pedell Sonja  , Wood Denise
Published: February 2025

In rural Australia, knowledge and utilisation of support by informal carers is lacking. During the caregiving period, socioemotional support from family and friends plays an important role in sustaining caregiving activities. Post-care, these social networks facilitate adjustment to role change and dealing with grief. Developing and improving access to peer support to enable carers to effectively cope with the challenges of caring may positively influence their caring experience. The primary objective of this project is to examine the response of isolated rural carers for older people with dementia to a videoconference (VC) based peer support and information program. Will participation in the program improve self-efficacy, quality of life, and mental health? Secondary objectives are to develop a VC based peer support program for isolated rural carers for older people with dementia, using a co-design approach; and to assess the feasibility of VC technology for enhancing social support to family caregivers in their homes. This project will collaboratively co-design and evaluate a facilitated VC peer support and information program to carers of people with dementia within rural areas. Carers will be recruited through community health and care providers. Program development will use an information sharing approach to facilitate social interaction. A focus of the project is to use off-the-shelf technology which will be more accessible than specialised bespoke solutions that are currently popular in this area of research. A mixed methods repeated measures randomized wait list design will be used to evaluate the project. The primary outcomes are self-efficacy, quality of life, and mental health. Secondary outcomes are perceived social support and user satisfaction with the technology, and intention to continue VC interaction.
Implementation of Fast Healthcare Interoperability Resources for an Integration of Laboratory and Hospital Information Systems
Authors: Kopanitsa Georgy  , Ivanov Alexandr
Published: February 2025

Electronic exchange of medical data between clinics and test centers makes the testing process more efficient, enables continuity of care record and reuse of medical data. The presented project employs HL 7 FHIR approach to model clinical concepts for the medical data exchange between a test center and different hospitals. Using a standard FHIR editor we have modeled 1226 observation profiles, 2396 commercial tests profiles that are mapped to 3249 production tests profiles. We have also defined a concept of an order and developed RESTfull API protocol to facilitate the ordering process. Now the data exchange system is in production and processes more than 20 000 test orders with more than 40 000 tests a day.
Integrating Biobank Data into a Clinical Data Research Network: The IBCB Project
Authors: Bouzille Guillaume  , Jouhet Vianney  , Turlin Bruno  , Clement Bruno  , Desille Mireille  , Riou Christine  , Hajjar Moufid  , Delamarre Denis  , Le Quilleuc Danielle  , Thiessard Frantz  , Cuggia Marc
Published: February 2025

Development of biobanks is still hampered by difficulty to collect high quality sample annotations using patient clinical information. The IBCB project evaluated the feasibility of a nationwide clinical data research network for this purpose. Method: the infrastructure, based on eHOP and I2B2 technologies, was interfaced with the legacy IT components of 3 hospitals. The evaluation focused on the data management process and tested 5 expert queries in Hepatocarcinoma. Results: the integration of biobank data was comprehensive and easy. Five out of 5 queries were successfully performed and shown consistent results with the data sources excepted one query which required to search in unstructured data. The platform was designed to be scalable and showed that with few effort biobank data and clinical data can be integrated and leveraged between hospitals. Clinical or phenotyping concepts extraction techniques from free text could significantly improve the samples annotation with fine granularity information.
Modelling Feedback in Virtual Patients: An Iterative Approach
Authors: Stathakarou Natalia  , Kononowicz Andrzej A.  , Henningsohn Lars  , McGrath Cormac
Published: February 2025

Virtual Patients (VPs) offer learners the opportunity to practice clinical reasoning skills and have recently been integrated in Massive Open Online Courses (MOOCs). Feedback is a central part of a branched VP, allowing the learner to reflect on the consequences of their decisions and actions. However, there is insufficient guidance on how to design feedback models within VPs and especially in the context of their application in MOOCs. In this paper, we share our experiences from building a feedback model for a bladder cancer VP in a Urology MOOC, following an iterative process in three steps. Our results demonstrate how we can systematize the process of improving the quality of VP components by the application of known literature frameworks and extend them with a feedback module. We illustrate the design and re-design process and exemplify with content from our VP. Our results can act as starting point for discussions on modelling feedback in VPs and invite future research on the topic.
Comparing the German Emergency Department Medical Record with the US HL7 Data Elements for Emergency Department Systems
Authors: Brammen Dominik  , Eggert Paul  , Lucas Benjamin  , Heermann-Langford Laura  , McClay James C.
Published: February 2025

Interoperability between emergency department (ED) information systems requires a shared data specification. In 2013 Health Level Seven International, an international standards body, approved a specification for Data Elements for Emergency Department Systems (DEEDS) for use in the United States. A similar specification was created in Germany for national employment, defining data elements and forms. This study presents the first step in the efforts to harmonize the two data definitions for International approval by comparing the meaning of the German Emergency Department Medical Record (GEDMR) data element definitions with the US DEEDS using a methodology for terminology mapping from ISO/TR 12300. The comparison between GEDMR and DEEDS did show significant differences in certain domains. The results support development of an international standard for ED data elements.
Compatibility Between Metadata Standards: Import Pipeline of CDISC ODM to the Samply.MDR
Authors: Kock-Schoppenhauer Ann-Kristin  , Ulrich Hannes  , Wagen-Zink Stefanie  , Duhm-Harbeck Petra  , Ingenerf Josef  , Neuhaus Philipp  , Dugas Martin  , Bruland Philipp
Published: February 2025

The establishment of a digital healthcare system is a national and community task. The Federal Ministry of Education and Research in Germany is providing funding for consortia consisting of university hospitals among others participating in the “Medical Informatics Initiative”. Exchange of medical data between research institutions necessitates a place where meta information for this data is made accessible. Within these consortia different metadata registry solutions were chosen. To promote interoperability between these solutions, we have examined whether the portal of Medical Data Models is eligible for managing and communicating metadata and relevant information across different data integration centres of the Medical Informatics Initiative and beyond. Apart from the MDM-portal, some ISO 11179-based systems such as Samply.MDR as well as openEHR-based solutions are going to be applyed. In this paper, we have focused on the creation of a mapping model between the CDISC ODM standard and the Samply.MDR import format. In summary, it can be stated that the mapping model is feasible and promote the exchangeability between different metadata registry approaches.
Fit by Bits: An Explorative Study of Sports Physiotherapists' Perception of Quantified Self Technologies
Authors: Allouch Somaya Ben  , van Velsen Lex
Published: February 2025

Our aim was to determine sport physiotherapists' attitudes towards Quantified Self technology usage and adoption and to analyze factors that may influence this attitude. A survey was used to study a sample in the Netherlands. Assessment was made of attitudes of towards Quantified Self technology usage by clients of therapists, by therapists themselves and intention to adopt Quantified Self technology. Results show that the uptake of Quantified Self technology by sports physiotherapists is rather low but that the intention to adopt Quantified Self technology by sports physiotherapists is quite high. These results can provide a foundation to provide an infrastructure for sports physiotherapists to fulfill their wishes with regard to Quantified Self technology.
Physicians' Perceptions About PHR for Inpatients. Qualitative Study
Authors: Frangella Julia  , Garcia Gabriela  , Bruchanski Lucila  , Smith María  , Sommer Janine  , Rapisarda Romina  , Luna Daniel
Published: February 2025

The aim of this article was to know physician perceptions about a PHR for inpatients and to examine ways to take advantage of possible functionalities that could help physicians in their daily workflow. This qualitative research, was conducted through: two focus groups and nine personal interviews performed with internal medicine physicians. Collection and analysis of obtained data was carried out by two professionals. It was made by the codification and categorization of data based on a process of constant comparison. The authors agreed upon three main dimensional themes: information, physician-patient/relatives communication, impact of PHR in physician workload. Physicians suggested functionalities and expressed concerns related to the management of sensitive information. As a conclusion we understand that it is crucial to involve physicians along PHR's development. This will help to overcome barriers and will improve adoption chances. Physicians will be directly affected by the implementation of a PHR for inpatients.
The Importance of Data Quality and Context Information in Indicator Production: Proof of Concept in a Metropolitan Paediatric Emergency Department
Authors: Viana João  , Santos Almeida  , Freitas Alberto
Published: February 2025

In the Paediatric emergency department scenario there were considerable efforts developing indicators over the past decade, specially referring to process, e.g. timeliness. Nevertheless, to fully characterize quality in Paediatric emergency department, indicators are developed but require further assessment and a more complete validation. This paper's aim is to emphasise the importance of data quality, data cleaning and the indicator choice in indicator production. The dataset provided for this analysis is from the São João Hospital Centre's information system and is composed by records of all the visits to the paediatrics emergency department from the 1st of January of 2014 to the 31st of December 2016. Only the variables time from admission to triage, admission to physician and length of stay were selected from the dataset to be analysed. Summary statistics and plots of each variable through the hours of the day were produced. Considering waiting time from admission till being seen by a physician, the variability of the arithmetic mean and median through the hours of the day range from 18 to 73 and 14 to 49 minutes of waiting time respectively. The maximum difference between indicators at a specific time happens at 0 a.m. and is 24 minutes. When considering waiting time from admission to triage the arithmetic mean is 15.2 however 75% of the children i.e. 3rd quartile waited 12 minutes or less. The choice of indicator is essential, it should accurately reflect what is being measured, taking into account the action that might be taken with the information.
Vaccine Hesitancy in Discussion Forums: Computer-Assisted Argument Mining with Topic Models
Authors: Skeppstedt Maria  , Kerren Andreas  , Stede Manfred
Published: February 2025

Arguments used when vaccination is debated on Internet discussion forums might give us valuable insights into reasons behind vaccine hesitancy. In this study, we applied automatic topic modelling on a collection of 943 discussion posts in which vaccine was debated, and six distinct discussion topics were detected by the algorithm. When manually coding the posts ranked as most typical for these six topics, a set of semantically coherent arguments were identified for each extracted topic. This indicates that topic modelling is a useful method for automatically identifying vaccine-related discussion topics and for identifying debate posts where these topics are discussed. This functionality could facilitate manual coding of salient arguments, and thereby form an important component in a system for computer-assisted coding of vaccine-related discussions.
Process Mining in Primary Care: A Literature Review
Authors: Williams Richard  , Rojas Eric  , Peek Niels  , Johnson Owen A.
Published: February 2025

Process mining is the discipline of discovering processes from event logs, checking the conformance of real world events to idealized processes, and ultimately finding ways to improve those processes. It was originally applied to business processes and has recently been applied to healthcare. It can reveal insights into clinical care pathways and inform the redesign of healthcare services. We reviewed the literature on process mining, to investigate the extent to which process mining has been applied to primary care, and to identify specific challenges that may arise in this setting. We identified 143 relevant papers, of which only a small minority (n=7) focused on primary care settings. Reported challenges included data quality (consistency and completeness of routinely collected data); selection of appropriate algorithms and tools; presentation of results; and utilization of results in real-world applications.
PaFloChar: An Innovating Approach to Characterise Patient Flows in Myocardial Infarction
Authors: Pinaire Jessica  , Azé Jérôme  , Bringay Sandra  , Poncelet Pascal  , Genolini Christophe  , Landais Paul
Published: February 2025

A better knowledge of patient flows would improve decision making in health planning. In this article, we propose a method to characterise patients flows and also to highlight profiles of care pathways considering times and costs. From medico-administrative data, we extracted spatio-temporal patterns. Then, we clustered time between hospitalisations and cost trajectories in order to identify profiles of change over time. This approach may support renewed management strategies.
Biomedical Informatics – How to Choose the Best Tool for Each Task
Authors: Maia Fábio  , Silva Luís Bastião  , Oliveira José Luís
Published: February 2025

The ever-increasing number of bioinformatics software tools that are publicly available, is leading to greater expectations about its regular use in clinical practice. However, from the end-users' perspective, they face many time the challenge of choosing the right tool for each task, from a panoply of solutions that have been developed over the years. In this paper, we propose a benchmarking methodology, based on a set of performance indicators, which can be used to identify the best methods and tools for each particular use case, both in research as in clinical practice.
Climate Change and Health as Massive Open Online Courses
Authors: Barteit Sandra  , Sié Ali  , Yé Maurice  , Depoux Anneliese  , Sauerborn Reiner
Published: February 2025

To teach the basics of climate change and health - such as the nature of health impacts, best practices in adoption strategies and promotion in health co-benefits, mitigation and adaptation strategies - we have developed three massive open online courses (MOOCs). We analysed the three MOOCs with regards to different factors such as course content, student motivation, instructor behaviour, co-learner effects, design and implementation effects. We conducted online surveys for all three MOOCs based on the research model of Hone et al., extended with regards to student's motivation and course outcomes. In total, we evaluated 6898 students, of which 101 students took part in the online survey. We found differences in completion rates and country of origin for the three MOOCs. The francophone MOOC was found to have a high number of participants from lower-income- and low-and-middle-income countries. The majority of participants were aged between 22 and 40 years of age and had mainly a graduate educational background. The primary motivation to join the MOOC was the knowledge and skills gained as a result of taking the course. The three MOOCs on climate change and health had a reach of almost 7000 students worldwide, as compared to the scope of a face-to-face course on the same topic of 30 students, including students from resource-low environments that are already vulnerable to current changes in climate. The evaluation of the MOOCs outlined the current impact. However, further research has to be conducted to be able to get insights into the impact over time.
A Framework for Usability Evaluation in EHR Procurement
Authors: Tyllinen Mari  , Kaipio Johanna  , Lääveri Tinja
Published: February 2025

Usability should be considered already by the procuring organizations when selecting future systems. In this paper, we present a framework for usability evaluation during electronic health record (EHR) system procurement. We describe the objectives of the evaluation, the procedure, selected usability attributes and the evaluation methods to measure them. We also present the emphasis usability had in the selection process. We do not elaborate on the details of the results, the application of methods or gathering of data. Instead we focus on the components of the framework to inform and give an example to other similar procurement projects.
User Evaluation of a Smartphone Application for Anticoagulation Therapy
Authors: Smaradottir Berglind  , Martinez Santiago  , Borycki Elizabeth  , Loudon Gareth  , Kushniruk Andre  , Jortveit Jarle  , Fensli Rune
Published: February 2025

Anticoagulation therapy with Warfarin is used for specific cardiovascular diseases to control the ability of blood clotting. Traditional ways of self-management therapy are based on paper forms and procedures. This paper presents an evaluation of the smartphone application Warfarin Guide, a computer-assisted decision-support system used to help patients in their management of anticoagulation therapy related to International Normalized Ratio (INR) values. The evaluation consisted of a usability test with 4 participants and a field test with 14 participants who used the application at home during four months. A mixed methods research approach included quantitative and qualitative analysis of the test results. The results showed that participants evaluated the Warfarin Guide as ‘useful’ for self-management of anticoagulation therapy, reporting key issues for further improvement.
An mHealth Application for Educating and Monitoring Patients Treated with a Ketogenic Diet Regimen
Authors: Zini Elisa Maria  , Tagliabue Anna  , Trentani Claudia  , Ferraris Cinzia  , Boninsegna Rosangela  , Quaglini Silvana  , Lanzola Giordano
Published: February 2025

Ketogenic Diet (KD) is a high-fat diet used to treat refractory epilepsy in patients, also including children. Because of the inherent differences with a balanced diet, patients starting KD face an abrupt switch of dietary habits. Moreover, KD is associated with several side effects that should be closely monitored. In this paper, we propose an mHealth application for training and empowering patients in managing KD. The application also acts as a bridge connecting patients with the health care staff for coaching and monitoring purposes.
Modelling Levels of Collaboration Among Health and Social Care Professionals in the Management of a Mental Health Plan
Authors: Luzi Daniela  , Pecoraro Fabrizio  , Tamburis Oscar
Published: February 2025

Professional collaboration among health and social care providers is considered an essential pattern to improve the integration of care. This is particularly important considering the planning activities for children with complex conditions. In this paper the level of collaboration among professionals in the development and implementation of the personalized plan in the mental health domain is analysed across 30 EU/EEA countries within the MOCHA project.