样式: 排序: IF: - GO 导出 标记为已读
-
App-Mohedo®: A mobile app for the management of chronic pelvic pain. A design and development study Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-03-15 Esther Díaz-Mohedo, Antonio L. Carrillo-León, Andrés Calvache-Mateo, Magdalena Ptak, Natalia Romero-Franco, Juan Carlos-Fernández
Chronic Pelvic Pain (CPP) has been described as a public health priority worldwide, and it is among the most prevalent and costly healthcare problems. Graded motor imagery (GMI) is a therapeutic tool that has been successfully used to improve pain in several chronic conditions. GMI therapy is divided into three stages: laterality training (LRJT, Left Right Judgement Task), imagined movements, and mirror
-
Cybersecurity and critical care staff: A mixed methods study Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-03-13 Kevin Hore, Mong Hoi Tan, Anne Kehoe, Aidan Beegan, Sabina Mason, Nader Al Mane, Deirdre Hughes, Caroline Kelly, John Wells, Claire Magner
Cyberattacks on healthcare organisations are becoming increasingly common and represent a growing threat to patient safety. The majority of breaches in cybersecurity have been attributed to human error. Intensive care departments are particularly vulnerable to cyberattacks. The aim of this study was to investigate cybersecurity awareness, knowledge and behaviours among critical care staff. This was
-
Can I trust my fake data – A comprehensive quality assessment framework for synthetic tabular data in healthcare Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-03-12 Vibeke Binz Vallevik, Aleksandar Babic, Serena E. Marshall, Severin Elvatun, Helga M.B. Brøgger, Sharmini Alagaratnam, Bjørn Edwin, Narasimha R. Veeraragavan, Anne Kjersti Befring, Jan F. Nygård
[Display omitted]
-
Ophthalmic care may not align with patient need: An analysis on state-wide patient needs and provider density between 2008 and 2022 Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-03-11 Aidan Gilson, Qingyu Chen, Ron A. Adelman
This study aims to assess the extent to which the demand for ophthalmologic care among patients at the state level is reflected in Google Trends data, serving as an indicator of patient desire in ophthalmology. For each state, patient interest in ophthalmologic care was estimated using the Google Trends resource measuring web search and YouTube search rates for multiple ophthalmologic terms. We compared
-
Categorizing digital data collection and intervention tools in health and wellbeing living lab settings: A modified Delphi study Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-03-10 Despoina Petsani, Teemu Santonen, Beatriz Merino-Barbancho, Gorka Epelde, Panagiotis Bamidis, Evdokimos Konstantinidis
[Display omitted]
-
Is it safe to learn about vital pulp capping from YouTube™ videos? A content and quality analysis Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-03-09 Celalettin Topbaş, Tuğçe Paksoy, Ayşe Gülnihal İslamoğlu, Kemal Çağlar, Abdurrahman Kerim Kul
To evaluate YouTube videos on vital pulp capping (VPC) for content, quality, source, usefulness, and reliability. This study assessed 249 English-language videos on vital pulp therapy using the Total Content Score (TCS), Video Information and Quality Index (VIQI), Global Quality Scale (GQS), Journal of the American Medical Association (JAMA) score and modified DISCERN score. Videos were categorized
-
Evaluation of D-dimer and prothrombin time in alcohol related liver cirrhosis with comparison of machine learning analyses Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-03-08 Hyeongyu Lee, Gilsung Yoo, Daewoo Pak, Jong-Han Lee
Liver cirrhosis (LC) can be caused by obesity, alcohol consumption, viral infection, and autoimmune disease. Early diagnosis and management of LC is important for patient quality of life. Non-invasive diagnostic methods are useful for predicting the current status and mortality risk of LC. The purpose of this study is to identify relevant diagnostic factors measured in routine laboratory test of alcohol-related
-
Effects of digital parenting interventions on self-efficacy, social support, and depressive symptoms in the transition to parenthood: A systematic review and meta-analysis Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-03-08 Marianne Lin-Lewry, Cai Thi Thuy Nguyen, Mega Hasanul Huda, Shao-Yu Tsai, Roselyn Chipojola, Shu-Yu Kuo
Parenting self-efficacy is essential for the transition to parenthood. As digital parenting educational interventions are rapidly being developed, their effects have not been examined by pooling available randomized controlled trials (RCTs). To comprehensively investigate the effects of digital educational interventions on parents’ self-efficacy, social support, and depressive symptoms in the first
-
Digital Health and Health Informatics Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-03-08 Arie Hasman, John Mantas, Heimar F. Marin
-
Measuring and describing perceived quality on physiotherapy practice management software Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-03-08 Eduardo Arza-Moncunill, Rodrigo Martín-San Agustín, Francesc Medina-Mirapeix
Despite the growing trend in the use of digital technologies in physiotherapy, the overall adoption and satisfaction of both, practice management software (PMS) and electronic health records in physiotherapy clinics has been low and slow over time. Satisfaction of expectations or perceived quality (PQ) is an abstract construct based on the discrepancy between expectations and perceptions, to measure
-
GC-CDSS: Personalized gastric cancer treatment recommendations system based on knowledge graph Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-03-07 Shuchun Li, Zhiang Li, Kui Xue, Xueliang Zhou, Chengsheng Ding, Yanfei Shao, Sen Zhang, Tong Ruan, Minhua Zheng, Jing Sun
Gastric cancer (GC) is one of the most common malignant tumors in the world, posing a serious threat to human health. Currently, gastric cancer treatment strategies emphasize a multidisciplinary team (MDT) consultation approach. However, there are numerous treatment guidelines and insights from clinical trials. The application of AI-based Clinical Decision Support System (CDSS) in tumor diagnosis and
-
StresSense: Real-Time detection of stress-displaying behaviors Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-03-07 Nida Saddaf Khan, Saleeta Qadir, Gulnaz Anjum, Nasir Uddin
Wrist-worn gadgets like smartphones are ideal for unobtrusively gathering user data, in various fields such as health and fitness monitoring, communication, and productivity enhancement. They seamlessly integrate into users' daily lives, providing valuable insights and features without the need for constant attention or disruption. In sensitive domains like mental health, these devices provide user-friendly
-
Differential effects of electronic patient record systems for wound care on hospital-acquired pressure injuries: Findings from a secondary analysis of German hospital data Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-03-05 Ursula H. Hübner, Jens Hüsers
[Display omitted]
-
Evaluating the effects of mobile application-based rehabilitation on improving disability and pain in patients with disputed thoracic outlet syndrome: A randomized controlled trial Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-03-01 Saeideh Goharinejad, Mohammad Naeem Ahrari, Khadijeh Moulaei, Afshin Sarafinejad
Disputed thoracic outlet syndrome (D.TOS) stands as one of the primary global contributors to physical disability, presenting diagnostic and treatment challenges for patients and frequently resulting in prolonged periods of pain and functional impairment. Mobile applications emerge as a promising avenue in aiding patient self-management and rehabilitation for D.TOS. This study aimed to investigate
-
Investigating mobile persuasive design for mental wellness: A cross-domain analysis Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-29 Linlin Shi, Xuan Li, Khin Than Win
Global mental health issues have increased the demand for digital mental health support. Mobile apps with persuasive technology play a vital role in enhancing mental well-being. Analysing and Comparing persuasive intervention design across various app categories, this study aims to inspire innovative design approaches for improving the persuasiveness of mental wellness apps during their development
-
Development of machine-learning models using pharmacy inquiry database for predicting dose-related inquiries in a tertiary teaching hospital Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-29 Jungwon Cho, Ah Ra Lee, Dongjun Koo, Koenhee Kim, Young Mi Jeong, Ho-Young Lee, Eunkyung Euni Lee
Drug-related problems (DRPs) are a significant concern in healthcare. Pharmacists play a vital role in detecting and resolving DRPs to improve patient safety. A pharmacy inquiry program was established in a tertiary teaching hospital to document inquiries about physicians’ orders, aimed at preventing potential DRPs or providing medication information during order reviews. We aimed to develop machine-learning
-
Multidisciplinary user experience of a newly implemented electronic patient record in Ireland: An exploratory qualitative study Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-28 Anne-Marie Brady, Jennifer Fortune, Ahmed Hassan Ali, Geraldine Prizeman, Wing Ting To, Grainne Courtney, Kama Stokes, Miriam Roche
Implementation of an Electronic Patient Record (EPR) in a key milestone in the digital strategy of modern healthcare organisations. The implementation of EPR systems can be viewed as challenging and complex. The aim of the study was to investigate user perspectives and experiences of the implementation of an Electronic Medical Record in a major academic teaching hospital, with simultaneous ‘go-live’
-
Using machine learning to link electronic health records in cancer registries: On the tradeoff between linkage quality and manual effort Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-28 Philipp Röchner, Franz Rothlauf
Cancer registries link a large number of electronic health records reported by medical institutions to already registered records of the matching individual and tumor. Records are automatically linked using deterministic and probabilistic approaches; machine learning is rarely used. Records that cannot be matched automatically with sufficient accuracy are typically processed manually. For application
-
Researching big IT in the UK National Health Service: A systematic review of theory-based studies Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-27 Colin Price, Olga Suhomlinova, William Green
To identify and discuss theory-based studies of large-scale health information technology programs in the UK National Health Service. Using the PRISMA systematic review framework, we searched Scopus, PubMed and CINAHL databases from inception to March 2022 for theory-based studies of large-scale health IT implementations. We undertook detailed full-text analyses of papers meeting our inclusion criteria
-
Unlocking human-like conversations: Scoping review of automation techniques for personalized healthcare interventions using conversational agents Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-24 Ana Martins, Ana Londral, Isabel L. Nunes, Luís V. Lapão
Conversational agents (CAs) offer a sustainable approach to deliver personalized interventions and improve health outcomes. To review how human-like communication and automation techniques of CAs in personalized healthcare interventions have been implemented. It is intended for designers and developers, computational scientists, behavior scientists, and biomedical engineers who aim at developing CAs
-
Informing nursing policy: An exploration of digital health research by nurses in England Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-23 Siobhan O'Connor, Louise Cave, Natasha Philips
Digital health technologies are designed, implemented, and evaluated to support clinical practice, enable patients to self-manage illness, and further public and global health. Nursing and health policies often emphasise the importance of evidence-based digital health services to deliver better care. However, the contribution nurses make to digital health research in many countries is unknown. Hence
-
The differences between adults and adolescents using a mobile health application for menstrual complaints: A usability and qualitative study Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-23 Habibe Özcan, Nicole B. Burger, Marloes E. Derksen, Linda W. Peute, Judith A.F. Huirne, Robert A. De Leeuw
A “” application (Menstruation Education Calendar, (MEK-APP)) was developed for adults to evaluate menstrual complaints. The future aim of this app is to use it as a self-diagnostic instrument for menstrual abnormalities for both adults and adolescents. Early identification of the potential of an application for future use by both user groups would increase implementation success and adoption of the
-
Assessment of the relationship between executive Nurses’ leadership Self-Efficacy and medical artificial intelligence readiness Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-20 Ayşe Eminoğlu, Şirin Çelikkanat
This study aims to assess the relationship between management nurses' leadership self-efficacy and medical artificial intelligence readiness. The research was conducted using a descriptive-correlational design. The sample of the study consisted of 196 management nurses working in public, private, and educational research hospitals in Gaziantep, Turkey. The data collection tools included the Personal
-
AssistMED project: Transforming cardiology cohort characterisation from electronic health records through natural language processing – Algorithm design, preliminary results, and field prospects Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-19 Cezary Maciejewski, Krzysztof Ozierański, Adam Barwiołek, Mikołaj Basza, Aleksandra Bożym, Michalina Ciurla, Maciej Janusz Krajsman, Magdalena Maciejewska, Piotr Lodziński, Grzegorz Opolski, Marcin Grabowski, Andrzej Cacko, Paweł Balsam
Electronic health records (EHR) are of great value for clinical research. However, EHR consists primarily of unstructured text which must be analysed by a human and coded into a database before data analysis- a time-consuming and costly process limiting research efficiency. Natural language processing (NLP) can facilitate data retrieval from unstructured text. During AssistMED project, we developed
-
Securing the future of IoT-healthcare systems: A meta-synthesis of mandatory security requirements Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-19 Mahmoud Zahedian Nezhad, Ali Javan Jafari Bojnordi, Mohammad Mehraeen, Rouholla Bagheri, Javad Rezazadeh
Healthcare-based Internet of Things (Healthcare-IoT) is a turning point in the development of health information systems. This emerging trend significantly contributes to enhancing users' awareness of their health, ultimately leading to an extension in life expectancy. Security and privacy are among the greatest challenges for H-IoT systems. To establish complete safety and security in these systems
-
hART: Deep learning-informed lifespan heart failure risk trajectories Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-19 Harry Moroz, Yue Li, Ariane Marelli
-
Development and validation of an artificial intelligence mobile application for predicting 30-day mortality in critically ill patients with orthopaedic trauma Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-17 Tao Han, Fan Xiong, Baisheng Sun, Lixia Zhong, Zhencan Han, Mingxing Lei
-
A multinational study on artificial intelligence adoption: Clinical implementers' perspectives Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-15 Luis Marco-Ruiz, Miguel Ángel Tejedor Hernández, Phuong Dinh Ngo, Alexandra Makhlysheva, Therese Olsen Svenning, Kari Dyb, Taridzo Chomutare, Carlos Fernández Llatas, Jorge Muñoz-Gama, Maryam Tayefi
[Display omitted]
-
Effects of a home care community-dwelling intervention on cognition, mental health, loneliness and quality of life in elder people: The VERA study Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-15 Guillermo Palacios-Navarro, Rebeca Santamaría, David del Río, Pedro Ramos, Santiago Gascón-Santos
New technologies can provide practical solutions that respond to the needs of the elderly, improving their quality of life and well-being. The aim of this research was to validate a multimodal approach based on a video call system, by comparing the scores of different clinically validated tests at baseline and at the end of the intervention. A longitudinal study was conducted with 7 healthy participants
-
Use of wearables among Multiple Sclerosis patients and healthcare Professionals: A scoping review Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-13 Shemah Alsulami, Stathis Th. Konstantinidis, Heather Wharrad
Multiple sclerosis (MS) is an increasingly prevalent chronic, autoimmune, and inflammatory central nervous system illness, whose common symptoms undermine the quality of life of patients and their families. Recent technical breakthroughs potentially offer continuous, reliable, sensitive, and objective remote monitoring solutions for healthcare. Wearables can be useful for evaluating falls, fatigue
-
Comparison of evaluation methods for improving the usability of a Spanish mHealth tool Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-12 Alexandria L. Hahn, Claudia L. Michaels, Gabriella Khawly, Tyler K. Nichols, Pamela Baez, Sergio Ozoria Ramirez, Janeth Juarez Padilla, Samantha Stonbraker, Susan Olender, Rebecca Schnall
Mobile health (mHealth) technology is now widely used across health conditions and populations. The rigorous development of these tools has yielded improved health outcomes, yet the ideal approach for developing mHealth tools continues to evolve, indicating the need for rigorous usability evaluation methods. This study compares two usability evaluation methods – cognitive interviews and usability assessments
-
Trust, trustworthiness and acceptability of a machine learning adoption in data-driven clinical decision support system. Some comments Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-11 Salvatore Chirumbolo, Massimiliano Berretta, Umberto Tirelli
-
NAIF: A novel artificial intelligence-based tool for accurate diagnosis of stage F3/F4 liver fibrosis in the general adult population, validated with three external datasets Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-11 Samir Hassoun, Chiara Bruckmann, Stefano Ciardullo, Gianluca Perseghin, Fabio Marra, Armando Curto, Umberto Arena, Francesco Broccolo, Francesca Di Gaudio
-
A text analytics approach for mining public discussions in online cancer forum: Analysis of multi-intent lung cancer treatment dataset Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-11 Adnan Muhammad Shah, Kang Yoon Lee, Abdullah Hidayat, Aaron Falchook, Wazir Muhammad
Online cancer forums (OCF) are increasingly popular platforms for patients and caregivers to discuss, seek information on, and share opinions about diseases and treatments. This interaction generates a substantial amount of unstructured text data, necessitating deeper exploration. Using time series data, our study exploits topic modeling in the novel domain of online cancer forums (OCFs) to identify
-
Online information for spontaneous coronary artery dissection (SCAD) survivors and their families: A systematic appraisal of content and quality of websites Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-11 Joseph Weddell, Danielle Jawad, Thomas Buckley, Julie Redfern, Zarin Mansur, Natalie Elliott, Coral L Hanson, Robyn Gallagher
Spontaneous coronary artery dissection (SCAD) survivors often seek information online. However, the quality and content of websites for SCAD survivors is uncertain. This review aimed to systematically identify and appraise websites for SCAD survivors. A systematic review approach was adapted for websites. A comprehensive search of SCAD key-phrases was performed using an internet search engine during
-
The effect of fear on health information searching behavior during the pandemic: The case of COVID-19 Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-07 Mesut Teleş
Fear can cause people to panic, lead to erroneous decisions, and trigger inappropriate behavior. This study aims to investigate the effects of fear of COVID-19 on the perception of the reliability and the use of health information sources. This study is both a cross-sectional and explanatory study. The participants selected by convenience sampling method were 323 students attending a state university
-
A customised down-sampling machine learning approach for sepsis prediction Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-06 Qinhao Wu, Fei Ye, Qianqian Gu, Feng Shao, Xi Long, Zhuozhao Zhan, Junjie Zhang, Jun He, Yangzhou Zhang, Quan Xiao
Sepsis is a life-threatening condition in the ICU and requires treatment in time. Despite the accuracy of existing sepsis prediction models, insufficient focus on reducing alarms could worsen alarm fatigue and desensitisation in ICUs, potentially compromising patient safety. In this retrospective study, we aim to develop an accurate, robust, and readily deployable method in ICUs, only based on the
-
A semi-automatic mHealth system using wearable devices for identifying pain-related parameters in elderly individuals Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-05 Dogukan Baran Gungormus, Francisco M. Garcia-Moreno, Maria Bermudez-Edo, Laura Sánchez-Bermejo, José Luis Garrido, María José Rodríguez-Fórtiz, José Manuel Pérez-Mármol
Mobile health systems integrating wearable devices are emerging as promising tools for registering pain-related factors. However, their application in populations with chronic conditions has been underexplored. To design a semi-automatic mobile health system with wearable devices for evaluating the potential predictive relationship of pain qualities and thresholds with heart rate variability, skin
-
Exploring surgical infection prediction: A comparative study of established risk indexes and a novel model Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-05 Kjersti Mevik, Ashenafi Zebene Woldaregay, Alexander Ringdal, Karl Øyvind Mikalsen, Yuan Xu
-
Acknowledgement of reviewers 2023 Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-05
Abstract not available
-
Early detection of late-onset neonatal sepsis from noninvasive biosignals using deep learning: A multicenter prospective development and validation study Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-04 Antti Kallonen, Milla Juutinen, Alpo Värri, Guy Carrault, Patrick Pladys, Alain Beuchée
Neonatal sepsis is responsible for significant morbidity and mortality worldwide. Its accurate and timely diagnosis is hindered by vague symptoms and the urgent necessity for early antibiotic intervention. The gold standard for diagnosing the condition is the identification of a pathogenic organism from normally sterile sites via laboratory testing. However, this method is resource-intensive and cannot
-
Human factor engineering of point-of-care near infrared spectroscopy device for intracranial hemorrhage detection in Traumatic Brain Injury: A multi-center comparative study using a hybrid methodology Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-03 Jaimin Shah, Kaushik Vithalapara, Shilpa Malik, Anupam Lavania, Shailendra Solanki, Nilay S. Adhvaryu
This study assessed machine learning powered Near-infrared spectroscopy based (mNIRS) device’s usability and human factor ergonomics in four distinct healthcare provider groups. Traumatic Brain Injury (TBI) is a global concern with significant well-being implications. Timely intracranial hemorrhage (ICH) detection is crucial. mNIRS offers efficient non-invasive TBI screening. Two device utilization
-
Assessing the impact of real-time random safety audits through full propensity score matching on reliable data from the clinical information system Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-03 Maria Bodí, Manuel A. Samper, Gonzalo Sirgo, Federico Esteban, Laura Canadell, Julen Berrueta, Josep Gómez, Alejandro Rodríguez
Evidence-based care processes are not always applied at the bedside in critically ill patients. Numerous studies have assessed the impact of checklists and related strategies on the process of care and patient outcomes. We aimed to evaluate the effects of real-time random safety audits on process-of-care and outcome variables in critical care patients. This prospective study used data from the clinical
-
Methodological challenges in systematic reviews of mHealth interventions: Survey and consensus-based recommendations Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-01-29 Jesus Lopez-Alcalde, L. Susan Wieland, Jürgen Barth, Rebecca Grainger, Nancy Baxter, Neil Heron, Andreas Triantafyllidis, Carme Carrion, Eleonora M.C. Trecca, Felix Holl, Ana Maria Wägner, Sarah Edney, Yuqian Yan, Concepción Campos-Asensio, Gemma Villanueva, Rachelle R. Ramsey, Claudia M. Witt
Objective Mobile Health (mHealth) refers to using mobile devices to support health. This study aimed to identify specific methodological challenges in systematic reviews (SRs) of mHealth interventions and to develop guidance for addressing selected challenges. Study Design and Setting: Two-phase participatory research project. First, we sent an online survey to corresponding authors of SRs of mHealth
-
ARTEMIS: An alarm threshold and policy mining system for the intensive care unit Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-01-29 Jonas Chromik, Anne Rike Flint, Bert Arnrich
-
Utilizing nursing standards in electronic health records: A descriptive qualitative study Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-01-30 Lene Baagøe Laukvik, Merete Lyngstad, Ann Kristin Rotegård, Mariann Fossum
Background The electronic health record (EHR), including standardized structures and languages, represents an important data source for nurses, to continually update their individual and shared perceptual understanding of clinical situations. Registered nurses’ utilization of nursing standards, such as standardized nursing care plans and language in EHRs, has received little attention in the literature
-
-
An assessment of ten popular pregnancy applications (Apps) available for women in Australia Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-02 Sithara Wanni Arachchige Dona, Mary Rose Angeles, Dieu Nguyen, Paul Cooper, Linda Sweet, Anna Peeters
Given the growing popularity of health Apps, this study aimed to evaluate popular pregnancy Apps among Australian women. Ten popular pregnancy mobile device Apps accessible within Australia were assessed using the xxxx[blinded] Health E-technologies Assessment Lab (HEAL) framework, the Australian Privacy Principles (APP) and other context-specific criteria. Most Apps were robust in use and user-friendly
-
Data work and practices in healthcare: A scoping review Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-02 Pernille S. Bertelsen, Claus Bossen, Casper Knudsen, Asbjørn M. Pedersen
In healthcare, digitization has been widespread and profound, entailing a deluge of data. This has spurred ambitions for healthcare to become data-driven to improve efficiency and quality, and within medicine itself to improve diagnosing and treating diseases. The generation and processing of data requires human intervention and work, though this is often not acknowledged. The paper investigates who
-
The implementation of a multidisciplinary, electronic health record embedded care pathway to improve structured data recording and decrease electronic health record burden Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-02-01 Tom Ebbers, Robert P. Takes, Ludi E. Smeele, Rudolf B. Kool, Guido B. van den Broek, Richard Dirven
Theoretically, the added value of electronic health records (EHRs) is extensive. Reusable data capture in EHRs could lead to major improvements in quality measurement, scientific research, and decision support. To achieve these goals, structured and standardized recording of healthcare data is a prerequisite. However, time spent on EHRs by physicians is already high. This study evaluated the effect
-
Smartphone applications for nutrition Support: A systematic review of the target outcomes and main functionalities Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-01-28 Daniele Pala, Giorgia Petrini, Pietro Bosoni, Cristiana Larizza, Silvana Quaglini, Giordano Lanzola
Introduction A proper nutrition is essential for human life. Recently, special attention on this topic has been given in relation to three health statuses: obesity, malnutrition and specific diseases that can be related to food or treated with specific diets. Mobile technology is often used to assist users that wish to regulate their eating habits, and identifying which fields of application have been
-
Uptake and implementation of cardiac telerehabilitation: A systematic review of provider and system barriers and enablers Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-01-24 Daniel Ferrel-Yui, Dion Candelaria, Trond Røed Pettersen, Robyn Gallagher, Wendan Shi
-
Development and validation of a machine learning prediction model for perioperative red blood cell transfusions in cardiac surgery Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-01-26 Qian Li, Hong Lv, Yuye Chen, Jingjia Shen, Jia Shi, Chenghui Zhou, Fuxia Yan
-
Clinical decision support system in emergency telephone triage: A scoping review of technical design, implementation and evaluation Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-01-24 Julie Michel, Aurélia Manns, Sofia Boudersa, Côme Jaubert, Laurent Dupic, Benoit Vivien, Anita Burgun, Florence Campeotto, Rosy Tsopra
Objectives Emergency department overcrowding could be improved by upstream telephone triage. Emergency telephone triage aims at managing and orientating adequately patients as early as possible and distributing limited supply of staff and materials. This complex task could be improved with the use of Clinical decision support systems (CDSS). The aim of this scoping review was to identify literature
-
Trust and acceptability of data-driven clinical recommendations in everyday practice: A scoping review Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-01-20 Ruth P. Evans, Louise D. Bryant, Gregor Russell, Kate Absolom
Background Increasing attention is being given to the analysis of large health datasets to derive new clinical decision support systems (CDSS). However, few data-driven CDSS are being adopted into clinical practice. Trust in these tools is believed to be fundamental for acceptance and uptake but to date little attention has been given to defining or evaluating trust in clinical settings. Objectives
-
Assessing mental health from registry data: What is the best proxy? Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-01-17 Simon Gabriël Beerten, Robby De Pauw, Gijs Van Pottelbergh, Lidia Casas, Bert Vaes
Objective Medical registries frequently underestimate the prevalence of health problems compared with surveys. This study aimed to determine the registry variables that can serve as a proxy for variables studied in a mental health survey. Materials and methods Prevalences of depressive symptoms, anxiety and psychoactive medication use from the 2018 Belgian Health Interview Survey (HIS) were compared
-
Development and validation of a multimodal model in predicting severe acute pancreatitis based on radiomics and deep learning Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-01-20 Minyue Yin, Jiaxi Lin, Yu Wang, Yuanjun Liu, Rufa Zhang, Wenbin Duan, Zhirun Zhou, Shiqi Zhu, Jingwen Gao, Lu Liu, Xiaolin Liu, Chenqi Gu, Zhou Huang, Xiaodan Xu, Chunfang Xu, Jinzhou Zhu
Objective Aim to establish a multimodal model for predicting severe acute pancreatitis (SAP) using machine learning (ML) and deep learning (DL). Methods In this multicentre retrospective study, patients diagnosed with acute pancreatitis at admission were enrolled from January 2017 to December 2021. Clinical information within 24 h and CT scans within 72 h of admission were collected. First, we trained
-
Demographics and clinical features associated with rates of electronic message utilization in the primary care setting Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-01-11 Michael A. Hansen, Jacqueline Hirth, Roger Zoorob, James Langabeer
Introduction Electronic messages are growing as an important form of patient-provider communication, particularly in the primary care setting. However, adoption of healthcare technology has been under-utilized by underserved patient populations. The purpose of this study was to describe how adoption and utilization of electronic messaging occurred within a large primary care urban-based patient population
-
Application of a human-centered design for embedded machine learning model to develop data labeling software with nurses: Human-to-Artificial Intelligence (H2AI) Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-01-06 Naomi A. Kaduwela, Susan Horner, Priyansh Dadar, Renee C.B. Manworren
Background Nurses are essential for assessing and managing acute pain in hospitalized patients, especially those who are unable to self-report pain. Given their role and subject matter expertise (SME), nurses are also essential for the design and development of a supervised machine learning (ML) model for pain detection and clinical decision support software (CDSS) in a pain recognition automated monitoring
-
An artificial intelligence approach to predict infants’ health status at birth Int. J. Med. Inform. (IF 4.9) Pub Date : 2024-01-05 Tua Halomoan Harahap, Sofiene Mansouri, Omar Salim Abdullah, Herlina Uinarni, Shavan Askar, Thaer L. Jabbar, Ahmed Hussien Alawadi, Aalaa Yaseen Hassan
Background Machine learning could be used for prognosis/diagnosis of maternal and neonates’ diseases by analyzing the data sets and profiles obtained from a pregnant mother. Purpose We aimed to develop a prediction model based on machine learning algorithms to determine important maternal characteristics and neonates’ anthropometric profiles as the predictors of neonates’ health status. Methods This