bluuebunny/crossref_metadata_2025 huggingface dataset:
A Data-Driven Method of Discovering Misspellings of Medication Names on Twitter
Authors: Jiang Keyuan  , Chen Tingyu  , Huang Liyuan  , Calix Ricardo A.  , Bernard Gordon R.
Published: February 2025

Twitter, as a microblogging social media platform, has seen increasing applications of its data for pharmacovigilance which is to monitor and promote safe uses of pharmaceutical products. Medication names are typically used as keywords to query social media data. It is known that medication names are misspelled on social media, and finding the misspellings is challenging because there exists no a priori knowledge as to how people would misspell a medication name. We developed a data-driven, relational similarity-based approach to discover misspellings of medication names. Our approach is based upon the assumption of the identical (or similar) association of a medicine with its effects whether the medication is correctly spelled or misspelled. With distributed representations of the words in tweets posted in recent 24 months, we were able to discover a total of 54 misspellings of 6 medicines whose indications containing headache. Our search results also show that Twitter posts with misspellings of codeine and ibuprofen can be more than 10% of all the tweets associated with each of the medicines. Compared with the phonetics-based approach, our method discovered more actual misspellings used on Twitter.
The (Re)-Relaunching of the DMP, the French Shared Medical Record: New Features to Improve Uptake and Use
Authors: Séroussi Brigitte  , Bouaud Jacques
Published: February 2025

Health care delivery for patients with chronic conditions is complex and confusing. Care is often fragmented, less effective, and sometimes harmful. Given the potential for EHRs and other health IT systems to facilitate information flow between providers, patients, and settings, health IT-based measures are of particular interest for care coordination. Health information exchange (HIE) has the potential to improve the quality of healthcare by enabling providers with better access to patient information from multiple sources at the point of care. However, many barriers to HIE use have been reported. Another solution relies on the implementation of a nationwide centralized framework of clinical information sharing with “new” secure online care records stored in specifically created platforms. The French DMP follows this model but the adoption of the tool has been historically poor. In 2016, a renovation of the DMP program was launched in nine pilot French departments and new features have been implemented: the DMP content has been fully specified, patients can create their DMP by themselves, DMPs are automatically filled in by data claims, a mobile app has been developed, and technical issues about DMP and EHRs interoperability have been resolved. In October 2017, over 900,000 people have a DMP with an average new DMP being created every minute. These results have to be confirmed in 2018 when the new DMP will be deployed on the whole French territory.
YORwalK: Desiging a Smartphone Exercise Application for People with Intermittent Claudication
Authors: Shalan Ahmed  , Abdulrahman Abubakar  , Habli Ibrahim  , Tew Garry  , Thompson Andrew
Published: February 2025

Peripheral Arterial Disease (PAD) is a chronic cardiovascular disease. It is highly prevalent in older adults. Mobile Health (mHealth) and Telehealth technologies are considered two central digital solutions for enabling patient-centred care. There is evidence that physical activity apps can improve health outcomes in adults. The aim of this project is to develop a prototype of smart phone app to target patients with PAD, which we named YORwalK, to promote exercise and track changes in walking ability in this population. We used a multidisciplinary team combined with a User Centred Design approach. We performed an evaluation survey using modified System Usability Scale (SUS). The survey was to assess the usability of the App and completed by health care professionals. The App was developed based on the concept of promoting behaviour change through feedback and life style prompts. YORwalK features incorporate self-monitoring and motivating feedback. SUS result indicating higher usability of the App.
Medical Data Analytics Is Not a Simple Task
Authors: Babič František  , Vadovský Michal  , Paralič Ján
Published: February 2025

Data analytics represents a new chance for medical diagnosis and treatment to make it more effective and successful. This expectation is not so easy to achieve as it may look like at a first glance. The medical experts, doctors or general practitioners have their own vocabulary, they use specific terms and type of speaking. On the other side, data analysts have to understand the task and to select the right algorithms. The applicability of the results depends on the effectiveness of the interactions between those two worlds. This paper presents our experiences with various medical data samples in form of SWOT analysis. We identified the most important input attributes for the target diagnosis or extracted decision rules and analysed their interestingness with cooperating doctors, for most promising new cut-off values or an investigation of possible important relations hidden in data sample. In general, this type of knowledge can be used for clinical decision support, but it has to be evaluated on different samples, conditions and ideally in long-term studies. Sometimes, the interaction needed much more time than we expected at the beginning but our experiences are mostly positive.
Midlevel Maternity Providers' Preferences of a Childbirth Monitoring Tool in Low-Income Health Units in Uganda
Authors: Balikuddembe Michael S.  , Wakholi Peter K.  , Tumwesigye Nazarius M.  , Tylleskär Thorkild
Published: February 2025

A third of women in childbirth are inadequately monitored, partly due to the tools used. Some stakeholders assert that the current labour monitoring tools are not efficient and need improvement to become more relevant to childbirth attendants. The study objective was to explore the expectations of maternity service providers for a mobile childbirth monitoring tool in maternity facilities in a low-income country like Uganda. Semi-structured interviews of purposively selected midwives and doctors in rural-urban childbirth facilities in Uganda were conducted before thematic data analysis. The childbirth providers expected a tool that enabled fast and secure childbirth record storage and sharing. They desired a tool that would automatically and conveniently register patient clinical findings, and actively provide interactive clinical decision support on a busy ward. The tool ought to support agreed upon standards for good pregnancy outcomes but also adaptable to the patient and their difficult working conditions. The tool functionality should include clinical data management and real-time decision support to the midwives, while the non-functional attributes include versatility and security.
MOVE: A Mobile App Designed for Social Health Relations in Residential Areas
Authors: Kanstrup Anne Marie  , Bertelsen Pernille  , Nunez Heilyn Camacho  , Svarre Tanja  , Stage Jan
Published: February 2025

This paper describes the design of MOVE, a mobile app to support people in forming social relations around exercise in residential areas. MOVE was developed in collaboration with residents and health professionals in a neighbourhood identified as a high-risk health area. The app is targeted to those who are motivated but challenged to do exercise and based on a conceptual model to provide users a social horizon of exercise activities in their residential area. We present the design and first evaluation of MOVE, including usability evaluations in controlled and natural settings. Results from these evaluations indicate that MOVE is a promising platform to support local social health relations once the identified usability problems are resolved.
A Feasibility Study on the Implementation of Teleconsultation in Tuberculosis Patients in Zabol City of Iran
Authors: Sheikhtaheri Abbas  , Saravani-Aval Samane  , Farzi Jebrail  , Bagheri Somayeh  , Kayvanloo Fatemeh  , Bayat Mitra
Published: February 2025

Teleconsultation can be used for tuberculosis patients, especially in deprived area. We surveyed all of 60 employees in health centers and tuberculosis center in such area in Iran about feasibility (organizational, technical, human and environmental readiness) of implementing teleconsultation and its barriers. We found that human readiness was moderate and other aspects were weak. Furthermore, the main obstacles were the shortage of computer equipment (40%), technical infrastructure (35%), lack of funds (33.3%), lack of awareness (33.3%), and employee resistance (33.3%). Implementing teleconsultation for tuberculosis patients is not completely feasible in this area and requires improvement in organizational, technical and environmental factors.
Using Model-Based Recursive Partitioning for Treatment-Subgroup Interactions Detection in Real-World Data: A Myocardial Infarction Case Study
Authors: Chen Tiange  , Li Xiang  , Yang Jingang  , Hu Jingyi  , Xu Meilin  , Qin Yong  , Yang Yuejin
Published: February 2025

The effects of treatment often vary over subpopulations characterized by baseline patient features. Detection of such treatment-subgroup interaction is of central importance to precision medicine and personalized care. In this paper, we propose an analytical framework for treatment-subgroup interactions detection and treatment effectiveness heterogeneity evaluation in a real-world data setting. Model-based recursive partitioning analysis (MOB) is used for subgroup identification, filter-based confounder selection and multivariate logistic regression are used for confounding reduction and treatment effectiveness assessment. We illustrate this approach by a real-world case study that analyzes the effects of 15 drugs among patients with myocardial infarction (MI) using China Acute Myocardial Infarction (CAMI) registry data. The results show that our approach effectively identifies meaningful patient subgroups involved in treatment-subgroup interactions and thus can potentially aid decision making in personalized medicine.
Medical System Choice: Information That Affects the Selection of Healthcare Provider in Australia?
Authors: Sahama Tony  , Stranieri Andrew  , Butler-Henderson Kerryn  , Golden Isaac
Published: February 2025

Many complementary and alternative medical practices (CAM) are readily assessable in Australia alongside Allopathic practitioners. Although CAM practices are prevalent, little is known about how patients seek and use information when deciding which system to consult. We report some preliminary findings of a longitudinal study, designed to solicit factors that influence the Australian public when selecting from diverse medical systems. Fifty-four general public participants, willing to provide their confidential and anonymous opinion were included. The magnitudes of importance, critical in influencing factors, were screened. Results indicated a medical system was selected for its effectiveness, safety, credentials and care (p<0.001). Consultation time, convenience, cost, empowerment and rapport were less important factors (p<0.001) influencing selection of a medical system. The level of choices by participants [χ2(1, N=54) = 53.445, p<0.001] follow similar trends found for those in conventional medical systems. This contrasts with findings in other locations, where cost and time were major contributing factors when selecting medical systems.
Automatic Annotation of French Medical Narratives with SNOMED CT Concepts
Authors: Gaudet-Blavignac Christophe  , Foufi Vasiliki  , Wehrli Eric  , Lovis Christian
Published: February 2025

Medical data is multimodal. In particular, it is composed of both structured data and narrative data (free text). Narrative data is a type of unstructured data that, although containing valuable semantic and conceptual information, is rarely reused. In order to assure interoperability of medical data, automatic annotation of free text with SNOMED CT concepts via Natural Language Processing (NLP) tools is proposed. This task is performed using a hybrid multilingual syntactic parser. A preliminary evaluation of the annotation shows encouraging results and confirms that semantic enrichment of patient-related narratives can be accomplished by hybrid NLP systems, heavily based on syntax and lexicosemantic resources.
Enabling Analytics on Sensitive Medical Data with Secure Multi-Party Computation
Authors: Veeningen Meilof  , Chatterjea Supriyo  , Horváth Anna Zsófia  , Spindler Gerald  , Boersma Eric  , van der Spek Peter  , van der Galiën Onno  , Gutteling Job  , Kraaij Wessel  , Veugen Thijs
Published: February 2025

While there is a clear need to apply data analytics in the healthcare sector, this is often difficult because it requires combining sensitive data from multiple data sources. In this paper, we show how the cryptographic technique of secure multi-party computation can enable such data analytics by performing analytics without the need to share the underlying data. We discuss the issue of compliance to European privacy legislation; report on three pilots bringing these techniques closer to practice; and discuss the main challenges ahead to make fully privacy-preserving data analytics in the medical sector commonplace.
Engaging Stakeholders in the Design and Usability Evaluation of a Decision Aid to Improve Secondary Stroke Prevention
Authors: Porat Talya  , Liao Zhining  , Curcin Vasa
Published: February 2025

Stroke survivors have a nearly 40% risk of recurrent stroke during the first 10 years. Effective secondary stroke prevention strategies are sub-optimally used, and hence, developing interventions to enable healthcare professionals and stroke survivors to manage risk factors more effectively are required. In this paper we describe the usability evaluation of a decision aid designed in collaboration with stakeholders to reduce the risk of a recurrent stroke. The decision aid was found usable and acceptable by both general practitioners and stroke survivors. Concerns and suggestions for improving the decision aid are discussed.
Scrutinizing SNOMED CT's Ability to Reconcile Clinical Language Ambiguities with an Ontology Representation
Authors: Rodrigues Jean Marie  , Schulz Stefan  , Mizen Bassim  , Trombert Béatrice  , Rector Alan
Published: February 2025

An important SNOMED CT use case is to support semantic interoperability between electronic health records and aggregation terminologies such as ICD. From the ongoing alignment exercise between SNOMED CT and the new version of ICD, now in its pre-final form, we studied whether the ambiguity of clinical language as displayed by SNOMED CT synonyms hampers the quality of SNOMED CT axioms following the SNOMED CT “concept model”. We measure the rate of synonyms in the semantic misalignment between classes from the chapter on circulatory diseases of the ICD-11 beta version and SNOMED CT concepts with the same description names. Our study confirms that SNOMED CT synonyms are ambiguous and that there is a need to increase the number of SNOMED CT fully defined representations of Fully Specified Names (FSN), and of synonyms independently of their relations.
Effect of Nursing Assessment on Predictive Delirium Models in Hospitalised Patients
Authors: Veeranki Sai P.K.  , Hayn Dieter  , Kramer Diether  , Jauk Stefanie  , Schreier Günter
Published: February 2025

Delirium is an acute neuropsychiatric syndrome which is common in elderly patients during their hospitalisation and is associated with an increased mortality and morbidity. Since delirium is a) often underdiagnosed and b) preventable if early signs are detected,igh expectations are set in delirium risk assessment during hospital admission. In our latest studies, we showed that delirium prediction using machine learning algorithms is possible based on the patients' health history. The aim of this study is to compare the influence of nursing assessment data on prediction models with clinical and demographic data. We approached the problem by a) comparing the performance of predictive models including nursing data with models based on clinical and demographic data only and b) analysing the feature importance of all available features. From our results we concluded that nursing assessment data can improve the performance of delirium prediction models better than demographic, laboratory, diagnosis, procedures, and previous transfers' data alone.
Effects of Medical Device Regulations on the Development of Stand-Alone Medical Software: A Pilot Study
Authors: Blagec Kathrin  , Jungwirth David  , Haluza Daniela  , Samwald Matthias
Published: February 2025

Background: Medical device regulations which aim to ensure safety standards do not only apply to hardware devices but also to standalone medical software, e.g. mobile apps.
Modeling of ETL-Processes and Processed Information in Clinical Data Warehousing
Authors: Tute Erik  , Steiner Jochen
Published: February 2025

Background: Literature describes a big potential for reuse of clinical patient data. A clinical data warehouse (CDWH) is a means for that.
Towards Phenotyping of Clinical Trial Eligibility Criteria
Authors: Löbe Matthias  , Stäubert Sebastian  , Goldberg Colleen  , Haffner Ivonne  , Winter Alfred
Published: February 2025

Background: Medical plaintext documents contain important facts about patients, but they are rarely available for structured queries. The provision of structured information from natural language texts in addition to the existing structured data can significantly speed up the search for fulfilled inclusion criteria and thus improve the recruitment rate.
Towards a Single Data Exchange Standard for Use in Healthcare and in Clinical Research
Authors: Aerts Jozef
Published: February 2025

Background: The development processes of data exchange standards for use in healthcare are very different from those used in clinical research. Healthcare data standards are traditionally developed by the Health Level 7 (HL7) organization, whereas those for use in clinical research are mostly developed by the Clinical Data Interchange Standards Consortium. No alignment of these standards has so far taken place.
Effectiveness of Anonymization Methods in Preserving Patients' Privacy: A Systematic Literature Review
Authors: Langarizadeh Mostafa  , Orooji Azam  , Sheikhtaheri Abbas
Published: February 2025

Background: An ever growing for application of electronic health records (EHRs) has improved healthcare providers' communications, access to data for secondary use and promoted the quality of services. Patient's privacy has been changed to a great issue today since there are large loads of critical information in EHRs. Therefore, many privacy preservation techniques have been proposed and anonymization is a common one.
Improving Patient Motivation Towards Physical Rehabilitation Treatments with PlayTherapy Exergame
Authors: Gamboa Edwin  , Ruiz Camilo  , Trujillo Maria
Published: February 2025

A key problem in physical rehabilitation treatments is patient motivation since those treatments involve slow, repetitive, and often painful movements. Consequently, little progress may be achieved after a session, leading to longer or even uncompleted treatments. In this paper, PlayTherapy a platform to assist physical rehabilitation treatments is described. PlayTherapy is composed of two main components: (i) a rehabilitation digital exergame, consisting of a set of movement based and interactive mini-games; (ii) an information management system that keeps patient personal progress. Both components were developed in collaboration with a group of physiotherapists. Additionally, a User Experience (UX) evaluation, involving a group of physiotherapists and patients, is presented. This evaluation showed that the inclusion of PlayTherapy in physical rehabilitation treatments may increase patient motivation.
Motivational Factors for User Engagement with mHealth Apps
Authors: Woldaregay Ashenafi Zebene  , Issom David-Zacharie  , Henriksen André  , Marttila Henna  , Mikalsen Martin  , Pfuhl Gerit  , Sato Keiichi  , Lovis Christian  , Hartvigsen Gunnar
Published: February 2025

The widespread adoption of smartphones creates an enormous potential to improve healthcare services. Numerous apps, sensors, and devices are developed for health self-management purposes. However, adoption rates remain low and long-term user engagement is a major issue. The goal of this study is to identify major motivational factors that can facilitate prolonged use of mobile health systems. To this end, we conducted 16 interviews with representatives of various cultural backgrounds, disease history, age, and gender. Participants' experiences indicated that existing systems were unable to answer their self-management needs properly. People with a disease history favored learning from data, as well as from others via social media integration. People without chronic disease felt more reserved about social media integration. In conclusion, systems that collect and share personal data should have a clear opt-in or opt-out option to motivate usage. Additionally, researchers and mobile health system developers could achieve long-term adoption by giving clear answers to privacy and trust issues, while offering people strong added value according to their individual needs.
A Model for Calculated Privacy and Trust in pHealth Ecosystems
Authors: Ruotsalainen Pekka  , Blobel Bernd
Published: February 2025

A pHealth ecosystem is a community of service users and providers. It is also a dynamic socio-technical system. One of its main goals is to help users to maintain their personal health status. Another goal is to give economic benefit to stakeholders which use personal health information existing in the ecosystem. In pHealth ecosystems, a huge amount of health related data is collected and used by service providers such as data extracted from the regulated health record and information related to personal characteristics, genetics, lifestyle and environment. In pHealth ecosystems, there are different kinds of service providers such as regulated health care service providers, unregulated health service providers, ICT service providers, researchers and industrial organizations. This fact together with the multidimensional personal health data used raises serious privacy concerns.
Robotic Implementation of the Necessary Mechanism for the Human Characteristics Simulation: Approach from Self-Care Conceptual Modeling
Authors: Gonzalo de Diego B.  , Herrero Jaén S.  , Monsalvo San Macario E.  , Madariaga Casquero L.  , Jiménez Rodríguez M.L.  , Santamaría García J.M.  , Ramírez Sánchez S.C.  , Vialart Vidal N.  , Condor Camara D.F.
Published: February 2025

The vertiginous development of robotics, as part of the Artificial Intelligence, is currently raising its potential from the point of view of care. The purpose of the present article is the robotic implementation of a logical sequence model of the phases that happen in proper care. This requires approaching the representation and formalization of knowledge about care, what and how the care is: starting with the conceptual dissertation between life, and human characteristics, and also consider this care with the aim to lay the groundwork for Robots based on care..
Construction of Nursing Quality Control Information System in Large Hospitals
Authors: Xiao Shuang  , Xiao Ming-zhao  , Zhao Qing-hua  , Xie Li-ling
Published: February 2025

Based on the process and framework of nursing quality management in the “Third-level General Ho Accreditation Criteria”, with the help of computer and mobile information technology, development of nursing quality control informatics system computer operation and mobile operating. The system has implanted PDCA several scientific management tools into the mobile applications, insteads of replace traditional paper methods, improve working efficiency in process control and Data Operation.
Nursing Leaders' Satisfaction with Information Systems in the Day-to-Day Operations Management in Hospital Units
Authors: Peltonen Laura-Maria  , Junttila Kristiina  , Salanterä Sanna
Published: February 2025

Information usage in the day-to-day operations management of hospital units is complex due to numerous information systems in use. The aim of this study was to describe and compare nurse leaders' satisfaction with information systems used in the day-to-day operations management in hospital units. The design was a cross-sectional survey with five questions rated from one (disagree) to five (fully agree). The response rate was 65 % (n = 453). Respondents reported fair satisfaction with how information systems support decision-making (median 4, IQR 3–4) and improve ease of access to information (median 4, IQR 3–4). However, respondents were less satisfied with how systems improve speed of access to information (median 3, IQR 3–4). Nor did respondents think that systems were developed for them (median 3, IQR 2–4). Respondents further reported needing numerous systems daily to support decision-making (median 4, IQR 3–5). A clear need for one system, which would gather important information for display was stated (median 5, IQR 4–5). Work experience, gender and time when overseeing the unit were associated with some aspects related to satisfaction. In conclusion, information system improvements are needed to better support the day-to-day operations management in hospital units.
Design of an Observation Support System to Improve Pain Management
Authors: Seto Ryoma  , Inoue Toshitaka  , Yasoshima Takahiro
Published: February 2025

We were challenged to design an obeservation support system. To improve evidence-based observations, we anylysed nursing records from electronic medical records (EMR) and patient experiences (from blogs) regarding pain symptoms using text mining methods. As a result, it was found that the view point of pain differed between the patient and nurse. It is reccomended that an observation advice message should be inplemented into EMR to improve nurses' observations on pain management.
Identifying How Patient Portals May Be Effectively Used Among Mental Health Populations to Support Digital Inclusion: A Study Protocol
Authors: Strudwick Gillian  , Booth Richard  , Strauss John
Published: February 2025

Patient portals are secure online websites that allow patients access to their medical information from a particular healthcare organization. Currently, it is unknown how this technology can best be used to support patients with mental illness, and what types of indicators of portal adoption are meaningful to these patients. This study addresses this gap in our knowledge by obtaining the perspectives on this topic from patients, family members and Peer Support Workers.
Emerging Professional's View of the Landscape: Nursing Informatics Curriculum, Competencies, and Career Opportunities
Authors: Lewis Adrienne  , Block Lorraine  , Peltonen Laura  , Pruinelli Lisiane  , Topaz Maxim  , Lozada Perezmitre Erika
Published: February 2025

The curriculum associated with nursing informatics (NI) education is not standardized, therefore the perspectives of new and emerging nurse informaticians is important. How these curricula differences affect career opportunities of new nursing informaticians, and in turn influenced current career choices will be explored. Synthesizing opinions with themes extracted from a 2014 international study—Advancing nursi informatics in the next decade: Recommendations from an international survey will be summarized.
Learning Clinical Assessment and Interdisciplinary Team Collaboration in Primary Care. MOOC for Healthcare Practitioners and Students
Authors: Lunde Lene  , Moen Anne  , Rosvold Elin O.
Published: February 2025

Novel ways to build sufficient capacity to meet the need for competent healthcare providers in primary care are in strong demand. We developed a massive, open, online course (MOOC) to introduce and promote clinical skills development for healthcare workers (physicians, nurse practitioners, nurses, and nurse aids) and students in healthcare education (medical students and master and bachelor students in nursing) focusing on systematic health assessment and strengthening clinical decision making in primary care. Results from the pilot supports that the MOOC was relevant and highly useful for the participants, and has potential to contribute to interdisciplinary collaboration and discussions.
Clinical Simulation in Nursing: A Scale to Evaluate Satisfaction and Self-Confidence in Learning
Authors: Jara Jara Vanessa  , Sambuceti Núñez Carolina
Published: February 2025

The clinical simulation is a university educational proposal that exposes the student to contexts similar to real situations, using technological innovation. The objective of this project is to translate and validate the Spanish version of the Satisfaction and Self-confidence in Learning Scale of the National League for Nursing (NLN). The method proposed is rigorous and academic translation, validation by expert judges in nursing and statistical validation of this scale. It is expected to obtain a validated instrument that will effectively and systematically measure satisfaction and self-confidence in the learning of nursing students, by using simulation technologies.
The Development of Health Information Website: Construction, Content, and Service
Authors: Choi Hanna  , Jin Meiling
Published: February 2025

This study explored the development of health portal in keeping with the rapidly changing web environment and consumer needs. 17 representative health portals (US, UK, Australia, Korea) in services and content characteristics compared with three years ago. As a result, it is noticeable that ‘mobile application utility’ increases for services method, ‘PHR’ provision in public health website increases for the contents, ‘the moving contents’ increase for the service, and the updating ‘renewal date’ increases for the structural characteristics.
Using Predictive Model for Screening Bacterial Meningitis in National Surveillance System in Iran
Authors: Mirkhani Atieh  , Nabavi Mahmood  , Roshan Poor Arash  , Tavakkoli Mohammad
Published: February 2025

Bacterial meningitis is a dangerous infectious disease that the entire community can be influenced by its epidemics. The objective of this study is to develop a predictive model as a screening tool to accelerate distinguishing between patients with acute bacterial meningitis and non-bacterial ones to prevent bacterial meningitis epidemics in Iran. This study was conducted on Iranian meningitis registry, which consists of 7,945 suspected cases of the disease between 2009 and 2011. Each sample has 8 predictive and a target variables. The predictive model was developed by decision tree algorithm and, the overall accuracy was 78%, with a sensitivity of 87%, and a specificity of 70%, respectively. This model can help health policymakers and epidemiologists to identify bacterial meningitis outbreaks and support them to make a decision in infection dynamics. In conclusion, we developed and validated a predictive model that can be used in meningitis surveillance system in Iran. However, further research is needed to use the model in practice with different pathogen types of bacterial meningitis in order to proper antimicrobial therapy planning.
Oncology Information System Data – Implications for ‘Big Data’
Authors: Miller Alexis Andrew
Published: February 2025

Our Oncology Information Systems (OIS) with local User Documentation manages the medical data explored in this 26 item report of a minimal medical dataset. Over 10 years to 2016, 12906 diagnoses were registered (ICD10: C00-C80), with 18.84% of cases, and 63.9% of data points complete. Two sites were quality assured with high completion rates (H&N – 97.4% [4.26% of total cases], RECTUM – 88.74% [4.06%]). Sites lacking clinician attention varied from poor (eg, LUNG – 23.23% [13.24%]) to largely incomplete (eg, BRAIN – 2.01% [0.38%]).This disappointing medical data completion rate makes its use in a ‘Big Data’ effort suspect. Data extrapolation is compromised by variable natural history. Extrapolation techniques are unlikely to cope with only 18.84% complete data. Data mining requires input from domain experts. The 4 requirements of Big Data are not evident in oncological data.
Augmented Reality Glasses and Head-Mounted Display Devices in Healthcare
Authors: Gallos Parisis  , Georgiadis Charalabos  , Liaskos Joseph  , Mantas John
Published: February 2025

Augmented Realty (AR) technology has a significant contribution in healthcare sector by offering valuable solutions the last two decades. The aim of this paper is to investigate the implementations of Augmented Reality technologies in healthcare, which include wearable devices such as AR Glasses and Optical Head-Mounted Display Devices (OHMD), by searching the international scientific literature. Relevant studies were retrieved online from scientific databases using keywords related to Augmented Reality in healthcare. The results indicate the numerous applications of these technologies in healthcare procedures, like diagnosis, treatment, and rehabilitation, as well as in the education of healthcare professionals. The international scientific community encourages the usage of the AR wearable technologies like AR glasses in Healthcare.
Pending Laboratory Test Results at the Time of Discharge: A 3-Year Retrospective Comparison of Paper Versus Electronic Test Ordering in Three Emergency Departments
Authors: Wabe Nasir  , Li Ling  , Sezgin Gorkem  , Dahm Maria  , Vecellio Elia  , Lindeman Robert  , Westbrook Johanna  , Georgiou Andrew
Published: February 2025

Pending laboratory test results at discharge can have major adverse health outcomes. The availability of test results at discharge may depend on whether the tests were ordered electronically or by using a paper-based system. The aim of this study was to determine the rate of pending test results at time of discharge from Emergency Departments (ED), and compare the rate for paper-based and electronic orders across three EDs in New South Wales, Australia. This retrospective study described 71,466 ED presentations with 357,476 laboratory tests across three years (2014–2016). Only patients who were treated in ED and eventually discharged from ED were included. Most tests were ordered using the electronic system (97.2%, n=347,469). The rate of pending test results was significantly lower for electronic orders (6.6%, n=22,928) than for paper orders (9.7%, n=966): a difference of 3.1%. Similar differences were observed when analysis was done by year of ED presentation. Moreover, in a subgroup analysis that included the top five high volume tests, four of the five tests had significantly lower rates of pending test results for electronic orders than for paper-based orders. The study highlighted an important benefit of ordering tests via electronic system which can potentially improve patient outcomes.
Partnering in Digital Health Design: Engaging the Multidisciplinary Team in a Needs Analysis
Authors: Woods Leanna  , Cummings Elizabeth  , Duff Jed  , Walker Kim
Published: February 2025

Using participatory co-design methods and in partnership with consumers we have developed a mHealth application to support heart failure self-management. In the first phase of the research we conducted a needs analysis with clinicians. The objectives were to define the features to perceivably support self-management and the clinical requirements in preparation for its implementation as an adjunct to existing multidisciplinary care. Interviews were conducted using the ‘Rose, Thorn, Bud’ technique from Design Thinking together with a brainstorming session with post-it notes. Six sixty-minute interviews and one email exchange with seven clinicians produced 154 data points in total; 97 relating to self-management support and 57 to clinical relevance. Analysis of these data points resulted in design implications articulated in a design brief for use in subsequent co-design workshops. Our discussion focuses on a critique of the technique, which appears to be useful for this stakeholder group although concerns of adequately representing complexity emerged. This method was considered inadequately comprehensive for use in the needs analysis with patients and family. The authors encourage further research evaluating in-hospital processes for co-designed health technologies.
Does Point-of-Care Testing Impact Length of Stay in Emergency Departments (EDs)?: A Before and After Study of 26 Rural and Remote EDs
Authors: Li Ling  , McCaughey Euan  , Iles-Mann Juliana  , Sargeant Andrew  , Westbrook Johanna I.  , Georgiou Andrew
Published: February 2025

The implementation of Point-of-Care Testing (PoCT) services across rural and remote emergency departments (EDs) by NSW Health Pathology has the potential to significantly improve timely access to results for certain types of pathology laboratory tests and help to deliver timely patient care. The aim of this study was to examine the impact of the implementation of PoCT on the length of stay (LOS) of patients in rural and remote EDs. A total of 3808 patients with a circulatory system illness were treated and discharged at any one of 22 rural and remote EDs during the study period. Generalised Estimating Equation (GEE) modelling was applied to examine whether the implementation of PoCT impacted the ED LOS with adjustment for a range of clinical variables. More patients were treated and discharged from these rural and remote EDs within 4-hours after the PoCT implementation (post-PoCT 86.8% versus pre-PoCT 84.3%). Although average ED LOS was 11 minutes shorter in the post-PoCT period, the impact of PoCT on ED LOS was not conclusive after considering other important clinical factors (p=0.07). This study is the one of the few to examine changes in LOS following the introduction of PoCT in EDs in Australia. The study also identified areas where more robust methods could be applied in the future as the quality of PoCT data improves to further assess the potential effects of this technology on practice and outcomes.
Analyzing the Readability of Health Information Booklets on Cardiovascular Diseases
Authors: Zowalla Richard  , Pobiruchin Monika  , Wiesner Martin
Published: February 2025

A low level of patient health literacy represents a major reason for worse prognosis or reduced therapy adherence. Health information booklets are a major tool for improving patient's health literacy. This paper presents a computer-based readability analysis of patient information booklets from the cardiovascular domain. The study relies on 34 English booklets mostly on heart disease, prevention and procedures. It compares five different, well-established readability instruments. On average, readers of the assessed booklets have to visit school at least until the 9th U.S. school grade when applying the Flesch-Kincaid formula. According to the Gunning-Fog metric, readers would have to attend school until the 11th grade. The presented study demonstrates the feasibility of a fully automated text processing tool-chain for patient information booklets. The results reveal that readability metrics should be carefully interpreted and only be interchanged with caution.
Protecting Record Linkage Identifiers Using a Language Model for Patient Names
Authors: Schnell Rainer  , Borgs Christian
Published: February 2025

Linking information across databases fosters new research in the medical sciences. Recent European privacy regulations recommend encrypting personal identifiers used for linking. Bloom filter based methods are an increasingly popular Record Linkage method. However, basic Bloom filter encodings are prone to cryptographic attacks. Therefore, hardening methods against these attacks are required. In this paper, a new method for such a hardening method for Privacy-preserving Record Linkage (PPRL) technique is presented. By using a Markov chain-based language model of bigrams of identifiers during the encryption, protection against attacks is increased. Based on real-world mortality data, we compare unencrypted and state of the art PPRL methods with the results of the proposed hardening method.
Measuring the Availability of Electronic Patient Data Across the Hospital and Throughout Selected Clinical Workflows
Authors: Liebe Jan-David  , Esdar Moritz  , Hübner Ursula
Published: February 2025

The workflow-oriented dissemination of electronic patient data is a central goal of IT deployment in hospitals. Against this background, the present study examines two research questions: (1.) Are there differences in the availability of electronic patient data (AEPD) between different clinical workflows and data types and (2.) which structural and organizational factors determine AEPD? Based on a Germany wide hospital survey, AEPD was assessed along six clinical workflows. While AEPD was lowest for ward rounds, discharge showed the highest AEPD with pre- and post-surgery processes ranging in between. With regard to the data types analyzed, patient demographics and observation findings obtained the highest AEPD scores. Electrophysiological results, checklists and warnings were less common electronically and received lower AEPD scores. Multiple linear regression analysis resulted in a significant model that explained 34.4% of the variance of AEPD. Large hospitals and those with a professional information management, a high health IT related innovation culture and a nursing informatics officer possess higher AEPD scores and thus have better clinical information logistics mechanisms at their command.
Genetic Programming with Multi-Layered Population Structure for Software Evolution
Authors: Hasegawa Taku  , Mori Naoki  , Matsumoto Keinosuke
Published: February 2025

Genetic Programmings (GPs) is one of the most powerful evolutionary computation (EC) for software evolution. In ECs, it is difficult to maintain efficient building blocks. In particular, the control of building blocks in the population of genetic programming (GP) is relatively difficult because of tree-shaped individuals and also because of bloat, which is the uncontrolled growth of ineffective code segments in GP. For a variety of reasons, reliable techniques to remove bloat are highly desirable. This paper introduces a novel approach of removing bloat, by proposing a novel GP called “Genetic Programming with Multi-Layered Population Structure (MLPS-GP)” that employs multi-layered population and searches solutions using local search and crossover. The MLPS-GP has no mutation-like operator because such kinds of operators are the source of bloats. We showed that diversity can be maintained well only controlling the tree structures by a well-structured multi-layered population. To confirm the effectiveness of the proposed method, the computational experiments were carried out taking several classical Boolean problems as examples.
Risk Management in Agile Software Project Iteration Scheduling Using Bayesian Networks
Authors: Ngoc-Tuan Nguyen  , Quyet-Thang Huynh
Published: February 2025

Agile Software Development methods have been largely adopted in the last ten years since they have certain advantages over the traditional approaches. However, industrial software development processes are getting more and more complex and dynamic. As a consequence, optimization of software project scheduling has always been big challenges in both practice and academia, even with Agile methods. There is always uncertainty as well as a need for a probabilistic method that better model and predict uncertainty in software projects. This paper proposes Bayesian Networks to model risk factors in Agile software projects as well as managing risks in Agile iteration scheduling. The paper also addresses 19 common risk factors that affect iteration scheduling. Based on the method, a software was developed as a support tool for managers to control their project schedules as it can assess the possibility of each schedule.
Evaluation of Dataset Metamodel for Describing the Structure of Datasets
Authors: Rosli Marshima Mohd
Published: February 2025

Datasets basically contains data and metadata. Data are often misinterpreted due to insufficient metadata and gives rise to quality issues associated with the datasets such as failure to clearly identify the entity being measured and inability to clarify how the metrics were generated. We believe creating common agreement about the terminology and concepts in datasets is important to ensure the meaning of data able to be interpreted correctly. We developed dataset metamodel that describes the structure and concepts in a dataset, and the relationships between each concept to gain a shared understanding of the content of datasets. As a preliminary evaluation, we conducted a user study to evaluate the effectiveness of dataset metamodel. We used an online survey as our user study method. The survey aims to study how well participants understand the definitions of dataset category elements in the dataset metamodel and able to apply them to a range of data sets. We found that participants who had relevant background knowledge and experience in research, particularly in analysing data sets able to answer more questions correctly than participants who had less relevant background knowledge and experience in research. The results of our survey provide evidence that our dataset metamodel is effective to be used by researchers to model datasets for analysis in software engineering. Future work, we need to reproduce the results with more appropriately sized samples of researchers in the relevant areas.
An Embeddings Based Fuzzy Linguistics Supported Model to Measure the Contextual Bias in Sentiment Polarity
Authors: Bernabé-Moreno Juan  , Tejeda-Lorente Alvaro  , Herce-Zelaya Julio  , Porcel Carlos  , Herrera-Viedma Enrique
Published: February 2025

Polarity detection plays a pivotal role in the modern cognitive research field. Common approaches to compute the polarity of a given word rely on experimental dictionaries providing always the same value, no matter where the word is used and lacking therefore adaptivity to particular contexts. In a previous article, we proposed a method supported by fuzzy linguistic modelling to quantify this contextual bias and to enable the bias-aware sentiment analysis. In this work, we implement the bias contextualization based on a word embeddings technique to capture a larger portion of the contextual bias. To show how our approach works, we measure the bias of common concepts in two different domains and discuss the results compared with our previous attempt based on document contextualization.
Equipping Sequent-Based Argumentation with Defeasible Assumptions
Authors: Borg Anne Marie
Published: February 2025

In many expert and everyday reasoning contexts it is very useful to reason on the basis of defeasible assumptions. For instance, if the information at hand is incomplete we often use plausible assumptions, or if the information is conflicting we interpret it as consistent as possible. In this paper sequent-based argumentation, a form of logical argumentation in which arguments are represented by a sequent, is extended to incorporate assumptions. The resulting assumptive framework is general, in that some other approaches to reasoning with assumptions can adequately be represented in it. To exemplify this, we show that assumption-based argumentation can be expressed in assumptive sequent-based argumentation.