bluuebunny/crossref_metadata_2025 huggingface dataset:
iCarer: AAL for the Informal Carers of the Elderly
Authors: Moreno P.A.  , Garcia-Pacheco J.L.  , Charvill J.  , Lofti A.  , Langensiepen C.  , Saunders A.  , Berckmans K.  , Gaspersic J.  , Walton L.  , Carmona M.  , Perez de la Camara S.  , Sanchez-de-Madariaga R.  , Pozo J.  , Muñoz A.  , Pascual M.  , Gomez E.J.
Published: February 2025

In the context of the long-term care for older adults, informal carers play a key role. Daily competing priorities or a care-skills deficit may lead them to stress, anxiety and/or depression. The iCarer project (AAL-2012-5-239) proposes the design and implementation of a cloud-inspired personalised and adaptive platform which will offer support to informal carers of older adults with cognitive impairment. By means of a holistic approach comprising technologies and services addressing the intelligent and interactive monitoring of activities, knowledge management for personalised guidance and orientation, virtual interaction, e-learning, care coordination facilities and social network services, iCarer aims to reduce the informal carer stress and to enhance the quality of care they provide, thus improving their quality of life. The iCarer platform will be evaluated through a multi-centre non-controlled study (4 months; 48 homes located in England and in Slovenia). Currently the iCarer project is completing the development work. The evaluation trial is expected to start in August 2015.
Detecting Learning and Reasoning Patterns in a CDSS for Dementia Investigation
Authors: Lindgren Helena  , Yan Chunli
Published: February 2025

Reasoning conducted in clinical practice is manifested through different and often combined reasoning and learning strategies, adjusted to the characteristics of the available information, the medical professional's experience and skills, and the available tools, such as clinical practice guidelines. This research outlines a design model for supporting the commonly used strategies. This design model was implemented into a clinical decision-support system (CDSS), in addition to a method for detecting reasoning strategies applied when using the CDSS. This method was applied in a case study, with preliminary results presented in this paper and will be further implemented in future studies.
A socio-technical analytical framework on the EHR-organizational innovation interplay: Insights from a public hospital in Greece
Authors: Emmanouilidou Maria
Published: February 2025

The healthcare sector globally is confronted with increasing internal and external pressures that urge for a radical reform of health systems' status quo. The role of technological innovations such as Electronic Health Records (EHR) is recognized as instrumental in this transition process as it is expected to accelerate organizational innovations. This is why the widespread uptake of EHR systems is a top priority in the global healthcare agenda. The successful co-deployment though of EHR systems and organizational innovations within the context of secondary healthcare institutions is a complex and multifaceted issue. Existing research in the field has made little progress thus emphasizing the need for further research contribution that will incorporate a holistic perspective. This paper presents insights about the EHR-organizational innovation interplay from a public hospital in Greece into a socio-technical analytical framework providing a multilevel set of action points for the eHealth roadmap with worldwide relevance.
A methodology for mining clinical data: experiences from TRANSFoRm project
Authors: Danger Roxana  , Corrigan Derek  , Soler Jean K.  , Kazienko Przemyslaw  , Kajdanowicz Tomasz  , Majeed Azeem  , Curcin Vasa
Published: February 2025

Data mining of electronic health records (eHRs) allows us to identify patterns of patient data that characterize diseases and their progress and learn best practices for treatment and diagnosis. Clinical Prediction Rules (CPRs) are a form of clinical evidence that quantifies the contribution of different clinical data to a particular clinical outcome and help clinicians to decide the diagnosis, prognosis or therapeutic conduct for any given patient. The TRANSFoRm diagnostic support system (DSS) is based on the construction of an ontological repository of CPRs for diagnosis prediction in which clinical evidence is expressed using a unified vocabulary. This paper explains the proposed methodology for constructing this CPR repository, addressing algorithms and quality measures for filtering relevant rules. Some preliminary application results are also presented.
Process assessment by automated computation of healthcare quality indicators in hospital electronic health records: a systematic review of indicators
Authors: Chazard Emmanuel  , Babaousmail Djaber  , Schaffar Aurélien  , Ficheur Grégoire  , Beuscart Régis
Published: February 2025

The objective of the work is to extract healthcare process quality indicators from the literature, and to evaluate which of them could be automatically computed using routinely collected data from electronic health records (EHRs). A minimal set of data commonly available in EHRs is first defined. The initial bibliographic query enables to identify 8,744 papers, among which 126 papers describe 440 process indicators. 22.3% of indicators can be automatically computed. The computation of the indicators mostly require diagnoses (99%), drug prescriptions (59%), medical procedures (48%), administrative data (30%), laboratory results (20%), free-text reports with basic keyword research (19%), linkage with the patient's previous stays (11%) and dependence assessment (3%). 77.7% of indicators cannot be automatically computed, mostly because they require a linkage with outpatient data (61%), structured data that are usually not available (43%), unstructured data (26%) or the trace of an information that was given to the patient (8%).
Designing ETL Tools to Feed a Data Warehouse Based on Electronic Healthcare Record Infrastructure
Authors: Pecoraro Fabrizio  , Luzi Daniela  , Ricci Fabrizio L.
Published: February 2025

Aim of this paper is to propose a methodology to design Extract, Transform and Load (ETL) tools in a clinical data warehouse architecture based on the Electronic Healthcare Record (EHR). This approach takes advantages on the use of this infrastructure as one of the main source of information to feed the data warehouse, taking also into account that clinical documents produced by heterogeneous legacy systems are structured using the HL7 CDA standard. This paper describes the main activities to be performed to map the information collected in the different types of document with the dimensional model primitives.
Short-circuit prevention in organic thin film devices by oxidative repair
Authors: Michels Jasper J.  , Oostra A. Jolt  , Blom Paul W.M.
Published: February 2025

Self-healing concepts are nowadays becoming relevant for high-end technologies, such as thin film organic electronics. Inherent to thin film processing is the occurrence of short circuits, which limits performance and production yield. This chapter demonstrates a powerful repair concept for short-circuit prevention both in organic light-emitting diodes and organic solar cells. The significant disruption of the conductivity of the typically applied hole transport material poly(3,4-ethylenedioxythiophene):poly(styrene sulfonic acid) (PEDOT:PSS) by aqueous sodium hypochlorite forms the basis for this repair concept, which allows full optoelectronic recovery of flawed devices.
Noise Reduction for a MEMS-Gyroscope-Based Head Mouse
Authors: Du Jiaying  , Gerdtman Christer  , Lindén Maria
Published: February 2025

In this paper, four different signal processing algorithms which can be applied to reduce the noise from a MEMS-gyroscope-based computer head mouse are presented. MEMS-gyroscopes are small, light, cheap and widely used in many electrical products. MultiPos, a MEMS-gyroscope-based computer head mouse system was designed for persons with movement disorders. Noise such as physiological tremor and electrical noise is a common problem for the MultiPos system. In this study four different signal processing algorithms were applied and evaluated by simulation in MATLAB and implementation in a dsPIC, with aim to minimize the noise in MultiPos. The algorithms were low-pass filter, Least Mean Square (LMS) algorithm, Kalman filter and Weighted Fourier Linear Combiner (WFLC) algorithm. Comparisons and system tests show that these signal processing algorithms can be used to improve the MultiPos system. The WFLC algorithm was found the best method for noise reduction in the application of a MEMS-gyroscope-based head mouse.
Web-Based Multi-Site Feasibility Questionnaire Tool
Authors: Soto-Rey Iñaki  , Trinczek Benjamin  , Amo Jose Ignacio  , Bauselas Jesús  , Dugas Martin  , Fritz Fleur
Published: February 2025

The design of clinical trial (CT) study protocols, currently supported by clinicians, is often a slow and cumbersome process. The Electronic Health Records for Clinical Research (EHR4CR) project supports the design of study protocols through a multi-site patient count cohort system. However, there is still a need to improve the process step in which the clinicians are involved. This research aims to enhance the EHR4CR platform with a tool to support the contact of CT sponsors with clinical investigators to obtain their input regarding feasibility data for the CT protocol design. From a list of requirements, a technical architecture that responds to the needs of feasibility assessments was modelled. With this architecture as a basis, a system that allows users to generate, send, fill out and visualise results of feasibility questionnaires across clinical sites was developed and integrated within the EHR4CR platform. The resulting system improves the current methods by providing direct contact to clinical investigators, facilitating the creation and answer of feasibility questionnaires for CTs.
Health Professionals Information for Diagnostics Related Groups (DRGs) with the Use of a Website
Authors: Mpizopoulou Katerina  , Mpizopoulou Zoe  , Magita Andrianna  , Mechili Aggelos E.  , Diomidous Marianna  , Mantas John
Published: February 2025

In recent years the costs of hospital care in developed countries absorbed a high proportion of total health resources. In Greece, after the establishment of the National Health System (NHS), funding for hospitals comes mainly from the state budget, and social insurance, therefore auditing of hospital cost is imperative to ensure their viability, especially at this time when the country is tested by economic crisis. Overtime many factors for the increase of hospital cost have been mentioned, such as the rapid development of medical technology, the low level of organization of the hospital system and the low productivity of human resources. The problem of rising health expenditure over the past decades is a worldwide phenomenon and it has brought about many changes in traditional retrospective methods for financing in the hospital sector, with prospective financial forms that combine patient composition and needs, and the productive activity of hospital need to the rationalization and contain expenditures. The system of Diagnosis Related Groups was a revolutionary success over the past decades and has now achieved worldwide recognition.
Integrated Electronic Health Record Database Management System: A Proposal
Authors: Schiza Eirini C.  , Panos George  , David Christiana  , Petkov Nicolai  , Schizas Christos N.
Published: February 2025

eHealth has attained significant importance as a new mechanism for health management and medical practice. However, the technological growth of eHealth is still limited by technical expertise needed to develop appropriate products. Researchers are constantly in a process of developing and testing new software for building and handling Clinical Medical Records, being renamed to Electronic Health Record (EHR) systems; EHRs take full advantage of the technological developments and at the same time provide increased diagnostic and treatment capabilities to doctors. A step to be considered for facilitating this aim is to involve more actively the doctor in building the fundamental steps for creating the EHR system and database. A global clinical patient record database management system can be electronically created by simulating real life medical practice health record taking and utilizing, analyzing the recorded parameters. This proposed approach demonstrates the effective implementation of a universal classic medical record in electronic form, a procedure by which, clinicians are led to utilize algorithms and intelligent systems for their differential diagnosis, final diagnosis and treatment strategies.
3D Texture Analysis of Heterogeneous MRI Data for Diagnostic Classification of Childhood Brain Tumours
Authors: Fetit Ahmed E.  , Novak Jan  , Rodriguez Daniel  , Auer Dorothee P.  , Clark Chris A.  , Grundy Richard G.  , Jaspan Tim  , Peet Andrew C.  , Arvanitis Theodoros N.
Published: February 2025

Brain tumours are the most frequently occuring solid tumours affecting childhood, representing 27% of all cancers. The most common posterior fossa tumours are medulloblastoma, pilocytic astrocytoma and ependymoma. Texture Analysis (TA) of Magnetic Resonance Imaging (MRI) aims to represent pixel distributions, intensities and dependencies using mathematically defined features. Such features could potentially provide quantifiable information that is beyond the human vision capabilities, and hence be used to supplement qualitative assessments conducted by radiologists. The primary aim of this study was to carry out a multicentre investigation on the efficacy of 3D TA for diagnostic classification of childhood brain tumours, using conventional MRI images. The data used had been acquired at three different hospitals and consisted of pre-contrast T1 and T2-weighted MRI series, obtained from 121 children diagnosed with medulloblastoma, pilocytic astrocytoma and ependymoma. Using 3D textural features, based on first, second and higher order statistical methods, a support vector machine (SVM) classifier was trained and tested using the leave-one-out cross-validation (LOOCV) approach. An essential outcome of this study is that 3D TA demonstrated a good overall performance, when used on data acquired from a number of centres and using scanners made by different manufacturers and at different magnetic field strengths.
The “SMART Travel Health” Mobile Application Assessment
Authors: Gallos Parisis  , Mantas John
Published: February 2025

An empirical study was conducted to evaluate the users' perception on a pilot mobile application (“SMART Travel Health”), their attitude towards use, and their intention to use it. A theoretical model was constructed based on TAM and other related works. The population was 88 travellers who used the pilot application. Data analysis was performed using partial least squares path modeling. Results highlight the very strong significant effect of perceived ease of use to perceived usefulness, the strong significant effect of perceived usefulness to attitude towards use, as well as, the significant effect of perceived ease of use to attitude towards using the application. Also, the strong significant effect of attitude towards use to behavioral intention to use is presenting the positive perception of the population about this mobile application.
Establishing a National Medical Device Registry in Saudi Arabia: Lessons Learned and Future Work
Authors: Al-Surimi Khaled  , Househ Mowafa  , Almohandis Essam  , Alshagathrh Fahd
Published: February 2025

Medical device evaluation presents several unique challenges due to the great diversity and complexity of medical devices and their rapid technological evolution. There has been a variety of work conducted on the development of disease based registries and health surveillance systems in Saudi Arabia. However, the progress of medical device registry systems and post-market medical device surveillance systems remains in its infancy in Saudi Arabia and within the region. In 2007, a royal decree assigned the responsibility for regulating medical devices to the Saudi Food and Drug Authority (SFDA). Soon afterwards, the SFDA established the Medical Devices National Registry (MDNR) to house medical device information relating to manufacturers, agents, suppliers and end-users. The aim of this paper is to provide an overview on the Medical Device National Registry (MDNR) in Saudi Arabia and describe the current experience and future work of establishing a comprehensive medical device registry and post-market surveillance system in Saudi Arabia.
The Digital Microscopy in Organ Transplantation: Ergonomics of the Tele-Pathological Evaluation of Renal and Liver Grafts
Authors: Mammas Constantinos S.  , Lazaris Andreas  , Kostopanagiotou Georgia  , Lemonidou Chryssa  , Patsouris Eustratios
Published: February 2025

Aim: Ergonomics of Digital Microscopy (DM) based on virtual slides, on Telemedicine Systems (TS) for Tele-Pathological (TPE) evaluation of the grafts (G) in organ transplantation (OT).
Vagal Nerve Stimulation (VNS) Therapy System Implementation at a Neurology Department in Saudi Arabia
Authors: Al Muallem Yahya  , Al Dogether Majed  , Al Ateeq Asma  , Al Moammary Eman  , Al Ghamdi Huda  , Almeshari Meshari  , Househ Mowafa
Published: February 2025

The objective of this paper is to report on the implementation of a Vagal Nerve Stimulation (VNS) Therapy System at a neurology department in Saudi Arabia. Key informant interviews, meeting documents, and experience of the researcher were part of the data collection sources used in the study. A thematic analysis of the data was conducted. The preliminary work shows improvements in epilepsy treatment within the neurology department as a result of the new Vagal Nerve Stimulation (VNS) therapy system. We discuss the lessons learned and identify the limitations of the study. Future work will further investigate the impacts of the VNS system on physician and patient satisfaction and health outcomes.
Feasibility of Interactive Resistance Chair in Older Adults with Diabetes
Authors: Finkelstein Joseph  , Cisse Pape  , Jeong In cheol
Published: February 2025

An interactive resistance chair (RC) exercise system has been designed to support patients at home in following their individualized strengthening exercise plan. The aim of this study was (1) to introduce a computer-assisted home-based resistance exercise for older adults and (2) to demonstrate feasibility of the proposed system in older adults with diabetes. The RC exercise system was well accepted by older adults with diabetes regardless of education level, race or gender. The post-task questionnaires demonstrated ease of system use and satisfaction with the system. The attitudinal survey results showed positive seniors' attitudes towards the RC exercise system. The system usability (SUS) scale score was 94.0±5.76 demonstrating high acceptance of the RC exercise system. From the qualitative interviews, individualized feedback yielded important system upgrade solutions that can be useful in tailoring patient needs, values and preferences specific for seniors with diabetes. Further research is warranted to assess impact of RC exercise system in home setting with a larger sample size in a randomized trial.
Benefits and Barriers of E-Learning for Staff Training in a Medical University
Authors: Franz Stefan  , Behrends Marianne  , Haack Claudia  , Marschollek Michael
Published: February 2025

Learning Management Systems (LMS) are a feasible solution to fulfill the various requirements for e-learning based training in a medical university. Using the LMS ILIAS, the Institute of Diagnostic and Interventional Radiology has designed an e-learning unit about data protection, which has been used by 73% of the department's employees in the first three months. To increase the use of e-learning for staff training, it is necessary to identify barriers and benefits, which encourage the use of e-learning. Therefore, we started an online survey to examine how the employees evaluate this learning opportunity. The results show that 87% of the employees had no technical problems and also competence of Information and Communication Technology (ICT) was no barrier. If anything, reported issues were time shortages and tight schedules. Therefore, short learning modules (less than 20 minutes) are preferred. Furthermore, temporal flexibility for learning is important for 83% of employees.
Human Activity Recognition from Smart-Phone Sensor Data using a Multi-Class Ensemble Learning in Home Monitoring
Authors: Ghose Soumya  , Mitra Jhimli  , Karunanithi Mohan  , Dowling Jason
Published: February 2025

Home monitoring of chronically ill or elderly patient can reduce frequent hospitalisations and hence provide improved quality of care at a reduced cost to the community, therefore reducing the burden on the healthcare system. Activity recognition of such patients is of high importance in such a design. In this work, a system for automatic human physical activity recognition from smart-phone inertial sensors data is proposed. An ensemble of decision trees framework is adopted to train and predict the multi-class human activity system. A comparison of our proposed method with a multi-class traditional support vector machine shows significant improvement in activity recognition accuracies.
Reaching Out to Global Interoperability through Aligning Repository Networks
Authors: Shearer Kathleen  , Mueller Katharina  , Gottschling Maxie
Published: February 2025

COAR is working towards greater interoperability of systems in a number of areas, with an emphasis on open access metadata elements and vocabularies. This paper presents the outcomes of the recently published roadmap on future directions for repository interoperability as well as an overview of the current status of the associations' work related to this topic, i.e. the initiative “Aligning Repository Networks”.
The Role of the IT Department in Information System and Organizational Redesign
Authors: Stub Petersen Lone
Published: February 2025

This paper is based on a qualitative study of IT organization and clinical practice over a period of 3 years supported by additional data during the last 2 years. This paper argues that redesign is central to understanding and developing both healthcare information systems and organizations. The importance of the IT organization is also stressed throughout this paper as a pertinent partner and power when considering organizational change and learning in hospitals as it can serve both as a barrier and a catalyst of change and flexibility in the organization through information systems management. Therefore it is important to consider and secure appropriate forms for redesign and learning in cooperation with the IT department.
Healthcare in Disasters and the Role of RFID
Authors: Madanian Samaneh  , Parry David  , Norris Tony
Published: February 2025

Disasters either natural or man-made are inevitable, and therefore disaster management has always been an important function of government. Since during a disaster healthcare is often adversely affected, a lot of effort has been made in terms of researching effective responses and ways of improving the quality of delivered care to direct casualties and the rest of the community. In this regard, information technology plays an important role to help healthcare systems achieve this goal. One of these technologies that has become popular recently is Radio-Frequency Identification (RFID). This paper explores the relationship between emergency management and disaster healthcare and examines the role of RFID. It is suggested that RFID will become an integral part of disaster healthcare and a means of improving response performance.
Identification of Incidental Pulmonary Nodules in Free-text Radiology Reports: An Initial Investigation
Authors: Oliveira Lucas  , Tellis Ranjith  , Qian Yuechen  , Trovato Karen  , Mankovich Gabe
Published: February 2025

Advances in image quality produced by computed tomography (CT) and the growth in the number of image studies currently performed has made the management of incidental pulmonary nodules (IPNs) a challenging task. This research aims to identify IPNs in radiology reports of chest and abdominal CT by Natural Language Processing techiniques to recognize IPN in sentences of radiology reports. Our preliminary analysis indicates vastly different pulmonary incidental findings rates for two different patient groups.
Translating ICD-11 into French using lexical-based approach: a preliminary study
Authors: Merabti Tayeb  , Grosjean Julien  , Rodrigues Jean-Marie  , Darmoni Stefan Jacques
Published: February 2025

To translate the 11th edition of the International Classification of Diseases (ICD-11) into French, we proposed a lexical approach using Natural Language Processing techniques. This method relies on the 56 biomedical terminologies and ontologies included in the Cross-lingual Health Multiple Terminologies and Ontologies Portal. From a sample of 336 ICD-11 terms, the algorithm translated 164 (49%) terms into at least one French term each.
Adding Sound to ECG
Authors: Mihalas George I.  , Paralescu Sorin  , Tudor Anca  , Andor Minodora
Published: February 2025

This poster presents preliminary results of a project aiming to develop tools for adding sound associated to medical data for potential medical applications. Sonification procedures, the methodology used for testing various sonic representations of ECG, and the results are presented.
Non-Integrated Information and Communication Technologies in the Kidney Transplantation Process in Brazil
Authors: Peres Penteado Alissa  , Fábio Maciel Rafael  , Erbs João  , Feijó Ortolani Cristina Lucia  , Aguiar Roza Bartira  , Torres Pisa Ivan
Published: February 2025

The entire kidney transplantation process in Brazil is defined through laws, decrees, ordinances, and resolutions, but there is no defined theoretical map describing this process. From this representation it's possible to perform analysis, such as the identification of bottlenecks and information and communication technologies (ICTs) that support this process. The aim of this study was to analyze and represent the kidney transplantation workflow using business process modeling notation (BPMN) and then to identify the ICTs involved in the process. This study was conducted in eight steps, including document analysis and professional evaluation. The results include the BPMN model of the kidney transplantation process in Brazil and the identification of ICTs. We discovered that there are great delays in the process due to there being many different ICTs involved, which can cause information to be poorly integrated.
Data Science Solution to Event Prediction in Outsourced Clinical Trial Models
Authors: Dalevi Daniel  , Lovick Susan  , Mann Helen  , Metcalfe Paul D.  , Spencer Stuart  , Hollis Sally  , Ruau David
Published: February 2025

Late phase clinical trials are regularly outsourced to a Contract Research Organisation (CRO) while the risk and accountability remain within the sponsor company. Many statistical tasks are delivered by the CRO and later revalidated by the sponsor. Here, we report a technological approach to standardised event prediction. We have built a dynamic web application around an R-package with the aim of delivering reliable event predictions, simplifying communication and increasing trust between the CRO and the in-house statisticians via transparency. Short learning curve, interactivity, reproducibility and data diagnostics are key here. The current implementation is motivated by time-to-event prediction in oncology. We demonstrate a clear benefit of standardisation for both parties. The tool can be used for exploration, communication, sensitivity analysis and generating standard reports. At this point we wish to present this tool and share some of the insights we have gained during the development.
A Statistical Analysis of Term Occurrences in Radiology Reporting
Authors: Hong Yi  , Zhang Jin  , Zhu Ying  , Zhou Xiaoying
Published: February 2025

To compare term occurrences in free-text radiology reports and RSNA reporting templates, we selected five templates from an RSNA reporting template library and their corresponding free-text reports as a test set, and employed the Wilcoxon signed-rank test to find out whether the terms in RSNA reporting templates match those terms appearing in corresponding free-text radiology reports. The results show that most terms in free-text radiology reports are covered by RSNA reporting templates. By assessing the terminology coverage of existing templates, this study may benefit the growth of the RSNA reporting template library.
Modelling the Medication Management System for Resource Limited Settings: A Formal Representation of the Prescribing and Dispensing Phases
Authors: Ogallo William  , Kanter Andrew S.
Published: February 2025

We propose a conceptual data model for relational databases targeting the prescribing and dispensing phases of the medication management system. The model was developed using recommendations from existing standards and guidelines, with necessary modifications made to suit adoption in resource-limited settings. We present the model as an entity-relationship diagram with 10 entities, 12 relationships and 48 attributes. It is our hope that this work will help mitigate barriers in the implementation of electronic prescribing and dispensing standards in the developing world.
Facilitating Full-text Access to Biomedical Literature Using Open Access Resources
Authors: Kang Hongyu  , Hou Zhen  , Li Jiao
Published: February 2025

Open access (OA) resources and local libraries often have their own literature databases, especially in the field of biomedicine. We have developed a method of linking a local library to a biomedical OA resource facilitating researchers' full-text article access. The method uses a model based on vector space to measure similarities between two articles in local library and OA resources. The method achieved an F-score of 99.61%. This method of article linkage and mapping between local library and OA resources is available for use. Through this work, we have improved the full-text access of the biomedical OA resources.
Case Study: Applying OpenEHR Archetypes to a Clinical Data Repository in a Chinese Hospital
Authors: Min Lingtong  , Wang Li  , Lu Xudong  , Duan Huilong
Published: February 2025

openEHR is a flexible and scalable modeling methodology for clinical information and has been widely adopted in Europe and Australia. Due to the reasons of differences in clinical process and management, there are few research projects involving openEHR in China. To investigate the feasibility of openEHR methodology for clinical information modelling in China, this paper carries out a case study to apply openEHR archetypes to Clinical Data Repository (CDR) in a Chinese hospital. The results show that a set of 26 archetypes are found to cover all the concepts used in the CDR. Of all these, 9 (34.6%) are reused without change, 10 are modified and/or extended, and 7 are newly defined. The reasons for modification, extension and newly definition have been discussed, including granularity of archetype, metadata-level versus data-level modelling, and the representation of relationships between archetypes.
Understanding Deviations from Clinical Practice Guidelines in Adult Soft Tissue Sarcoma
Authors: Goldbraich Esther  , Waks Zeev  , Farkash Ariel  , Monti Marco  , Torresani Michele  , Bertulli Rossella  , Casali Paolo Giovanni  , Carmeli Boaz
Published: February 2025

In recent years we have witnessed the increasing adoption of clinical practice guidelines (CPGs) as decision support tools that guide medical treatment. As CPGs gain popularity, it has become evident that physicians frequently deviate from CPG recommendations, both erroneously and due to sound medical rationale. In this study we developed a methodology to computationally identify these deviation cases and understand their movitation. This was achieved using an integrated approach consisting of natural language processing, data modeling, and comparison methods to characterize deviations from CPG recommendations for 1431 adult soft tissue sarcoma patients. The results show that 48.9% of patient treatment programs deviate from CPG recommendations, with the largest deviation type being overtreatment, followed by differences in drug treatments. Interestingly, we identified over a dozen potential reasons for these deviations, with those directly related to the patients' cancer status being most abundant. These findings can be used to modify CPGs, increase adherence to CPG recommendations, reduce treatment cost, and potentially impact sarcoma care. Our approach can be applied to additional diseases that are subject to high deviation levels from CPGs.
INITIATE: An Intelligent Adaptive Alert Environment
Authors: Jafarpour Borna  , Abidi Samina Raza  , Ahmad Ahmad Marwan  , Abidi Syed Sibte Raza
Published: February 2025

Exposure to a large volume of alerts generated by medical Alert Generating Systems (AGS) such as drug-drug interaction softwares or clinical decision support systems over-whelms users and causes alert fatigue in them. Some of alert fatigue effects are ignoring crucial alerts and longer response times. A common approach to avoid alert fatigue is to devise mechanisms in AGS to stop them from generating alerts that are deemed irrelevant. In this paper, we present a novel framework called INITIATE: an INtellIgent adapTIve AlerT Environment to avoid alert fatigue by managing alerts generated by one or more AGS. We have identified and categories the lifecycle of different alerts and have developed alert management logic as per the alerts' lifecycle. Our framework incorporates an ontology that represents the alert management strategy and an alert management engine that executes this strategy. Our alert management framework offers the following features: (1) Adaptability based on users' feedback; (2) Personalization and aggregation of messages; and (3) Connection to Electronic Medical Records by implementing a HL7 Clinical Document Architecture parser.
Improving Hospital-Wide Early Resource Allocation through Machine Learning
Authors: Gartner Daniel  , Padman Rema
Published: February 2025

The objective of this paper is to evaluate the extent to which early determination of diagnosis-related groups (DRGs) can be used for better allocation of scarce hospital resources. When elective patients seek admission, the true DRG, currently determined only at discharge, is unknown. We approach the problem of early DRG determination in three stages: (1) test how much a Naïve Bayes classifier can improve classification accuracy as compared to a hospital's current approach; (2) develop a statistical program that makes admission and scheduling decisions based on the patients' clincial pathways and scarce hospital resources; and (3) feed the DRG as classified by the Naïve Bayes classifier and the hospitals' baseline approach into the model (which we evaluate in simulation). Our results reveal that the DRG grouper performs poorly in classifying the DRG correctly before admission while the Naïve Bayes approach substantially improves the classification task. The results from the connection of the classification method with the mathematical program also reveal that resource allocation decisions can be more effective and efficient with the hybrid approach.
Fast Model Adaptation for Automated Section Classification in Electronic Medical Records
Authors: Ni Jian  , Delaney Brian  , Florian Radu
Published: February 2025

Medical information extraction is the automatic extraction of structured information from electronic medical records, where such information can be used for improving healthcare processes and medical decision making. In this paper, we study one important medical information extraction task called section classification. The objective of section classification is to automatically identify sections in a medical document and classify them into one of the pre-defined section types. Training section classification models typically requires large amounts of human labeled training data to achieve high accuracy. Annotating institution-specific data, however, can be both expensive and time-consuming; which poses a big hurdle for adapting a section classification model to new medical institutions. In this paper, we apply two advanced machine learning techniques, active learning and distant supervision, to reduce annotation cost and achieve fast model adaptation for automated section classification in electronic medical records. Our experiment results show that active learning reduces the annotation cost and time by more than 50%, and distant supervision can achieve good model accuracy using weakly labeled training data only.
Danish Citizens and General Practitioners' Use of ICT for their Mutual Communication
Authors: Bertelsen Pernille  , Stub Petersen Lone
Published: February 2025

This paper reports on selected findings from a Danish national survey of citizens' perception and use of information and communication technology (ICT) for their health care [1]. Focus is on citizens' use of ICT and on communication with their General Practitioner (GP). It also focuses on citizens' experience of their GPs' ICT use and no use during medical consultations. The responsibility for medical service in Denmark is to a large extent handed over to the primary sector where the GP is the gatekeeper. Our data display that 65% of the adult citizens or their relatives have been using ICT to communicate with their GP. Twenty-two percent have experienced their GP use a computer screen to actively show them something while they have a consultation. Further, our data supports the assumption that the higher the education people have, the more likely they are to use ICT for their health care. The understanding of the use of ICT in communication with the GP is central to monitoring and developing an ICT that supports all citizens and considers new ways in which to enhance quality of care.
Using Publicly Available Data to Characterize Consumers Use of Email to Communicate with Healthcare Providers
Authors: Sandefer Ryan H.  , Khairat Saif S.  , Pieczkiewicz David S.  , Speedie Stuart M.
Published: February 2025

The use of patient focused technology has been proclaimed as a means to improve patient satisfaction and improve care outcomes. The Center for Medicaid/Medicare Services, through its EHR Incentive Program, has required eligible hospitals and professionals to send and receive secure messages from patients in order to receive financial incentives and avoid reimbursement penalties. Secure messaging between providers and patients has the potential to improve communication and care outcomes. The purpose of this study was to use National Health Interview Series (NHIS) data to identify the patient characteristics associated with communicating with healthcare providers via email. Individual patient characteristics were analyzed to determine the likelihood of emailing healthcare providers. The use of email for this purpose is associated with educational attainment, having a usual place of receiving healthcare, income, and geography. Publicly available data such as the NHIS may be used to better understand trends in adoption and use of consumer health information technologies.
A Baseline Patient Model to Support Testing of Medical Cyber-Physical Systems
Authors: Silva Lenardo C.  , Perkusich Mirko  , Almeida Hyggo O.  , Perkusich Angelo  , Lima Mateus A.M.  , Gorgônio Kyller C.
Published: February 2025

Medical Cyber-Physical Systems (MCPS) are currently a trending topic of research. The main challenges are related to the integration and interoperability of connected medical devices, patient safety, physiologic closed-loop control, and the verification and validation of these systems. In this paper, we focus on patient safety and MCPS validation. We present a formal patient model to be used in health care systems validation without jeopardizing the patient's health. To determine the basic patient conditions, our model considers the four main vital signs: heart rate, respiratory rate, blood pressure and body temperature. To generate the vital signs we used regression models based on statistical analysis of a clinical database. Our solution should be used as a starting point for a behavioral patient model and adapted to specific clinical scenarios. We present the modeling process of the baseline patient model and show its evaluation. The conception process may be used to build different patient models. The results show the feasibility of the proposed model as an alternative to the immediate need for clinical trials to test these medical systems.
Identifying Repetitive Institutional Review Board Stipulations by Natural Language Processing and Network Analysis
Authors: Kury Fabrício S.P.  , Cimino James J.
Published: February 2025

The corrections (“stipulations”) to a proposed research study protocol produced by an institutional review board (IRB) can often be repetitive across many studies; however, there is no standard set of stipulations that could be used, for example, by researchers wishing to anticipate and correct problems in their research proposals prior to submitting to an IRB. The objective of the research was to computationally identify the most repetitive types of stipulations generated in the course of IRB deliberations. The text of each stipulation was normalized using the natural language processing techniques. An undirected weighted network was constructed in which each stipulation was represented by a node, and each link, if present, had weight corresponding to the TF-IDF Cosine Similarity of the stipulations. Network analysis software was then used to identify clusters in the network representing similar stipulations. The final results were correlated with additional data to produce further insights about the IRB workflow. From a corpus of 18,582 stipulations we identified 31 types of repetitive stipulations. Those types accounted for 3,870 stipulations (20.8% of the corpus) produced for 697 (88.7%) of all protocols in 392 (also 88.7%) of all the CNS IRB meetings with stipulations entered in our data source. A notable peroportion of the corrections produced by the IRB can be considered highly repetitive. Our shareable method relied on a minimal manual analysis and provides an intuitive exploration with theoretically unbounded granularity. Finer granularity allowed for the insight that is anticipated to prevent the need for identifying the IRB panel expertise or any human supervision.
Nonadherence to Oral Antihyperglycemic Agents: Subsequent Hospitalization and Mortality among Patients with Type 2 Diabetes in Clinical Practice
Authors: Zhu Vivienne J.  , Tu Wanzhu  , Rosenman Marc B.  , Overhage J. Marc
Published: February 2025

Using real-world clinical data from the Indiana Network for Patient Care, we analyzed the associations between non-adherence to oral antihyperglycemic agents (OHA) and subsequent diabetes-related hospitalization and all-cause mortality for patients with type 2 diabetes. OHA adherence was measured by the annual proportion of days covered (PDC) for 2008 and 2009. Among 24,067 eligible patients, 35,507 annual PDCs were formed. Over 90% (n=21,798) of the patients had a PDC less than 80%. In generalized linear mixed model analyses, OHA non-adherence is significantly associated with diabetes related hospitalizations (OR: 1.2; 95% CI [1.1,1.3]; p<0.0001). Older patients, white patients, or patients who had ischemic heart disease, stroke, or renal disease had higher odds of hospitalization. Similarly, OHA non-adherence increased subsequent mortality (OR: 1.3; 95% CI [1.02, 1.61]; p<0.0001). Patient age, male gender, income and presence of ischemic heart diseases, stroke, and renal disease were also significantly associated with subsequent all-cause death.
Virtual Microscopy Large Slide Automated Acquisition: Error Analysis and Validation
Authors: Mancino Axel V.  , Roger Alyson  , Muscolo Domingo L.  , Farfalli German L.  , Roitman Pablo D.  , Aponte-Tinao Luis A.  , Ritacco Lucas E.  , Milano Federico E.
Published: February 2025

The aim of this work is to assess and analyze the discrepancies introduced in the reconstruction of an entire tumoral bone slice from multiple field acquisitions of a large microscopy slide. The reconstruction tends to preserve the original structural information and its error is estimated by comparing the reconstructed images of eight samples against single pictures of these samples. This comparison is held using the Structural Similarity index. The measurements show that smaller samples yield better results. The detected errors are introduced by the insufficiently corrected optical distortion caused by the camera lens, which tends to accumulate along the sample. Nevertheless, the maximum error encountered does not exceed 0.39 mm, which is smaller than the maximum tolerable error for the intended application, stated in 1mm.
Mining Temporal and Data Constraints Associated with Outcomes for Care Pathways
Authors: Li Xiang  , Liu Haifeng  , Mei Jing  , Yu Yiqin  , Xie Guotong
Published: February 2025

A care/clinical pathway defines a standardized care process for a specific patient group, which consists of clinical goals, activities, data attributes, and constraints describing temporal dependencies and data preconditions of the activities. The constraints, which are the key elements to represent the best practices, are difficult to define due to the variations in different regions and populations. In this paper, we propose an approach to discover temporal and data constraints that are correlated with clinical outcomes for care pathways. For each activity of interest, we extract a set of associated event-condition-action (ECA) rules from electronic medical records (EMR) to represent the temporal and data preconditions of the activity, by using our modified association rule mining algorithm. Then the best ECA rule that is significantly more likely to lead to a positive outcome is translated into the constraint on the activity. The approach has been applied to real-world EMR, and discovered meaningful constraints for different groups of type 2 diabetes patients, which can be used to provide decision support during individual patient care.
Acquiring Plausible Predications from MEDLINE by Clustering MeSH Annotations
Authors: Miñarro-Giménez Jose Antonio  , Kreuzthaler Markus  , Bernhardt-Melischnig Johannes  , Martínez-Costa Catalina  , Schulz Stefan
Published: February 2025

The massive accumulation of biomedical knowledge is reflected by the growth of the literature database MEDLINE with over 23 million bibliographic records. All records are manually indexed by MeSH descriptors, many of them refined by MeSH subheadings. We use subheading information to cluster types of MeSH descriptor co-occurrences in MEDLINE by processing co-occurrence information provided by the UMLS. The goal is to infer plausible predicates to each resulting cluster. In an initial experiment this was done by grouping disease-pharmacologic substance co-occurrences into six clusters. Then, a domain expert manually performed the assignment of meaningful predicates to the clusters. The mean accuracy of the best ten generated biomedical facts of each cluster was 85%. This result supports the evidence of the potential of MeSH subheadings for extracting plausible medical predications from MEDLINE.