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Automated breast imaging report generation based on the integration of multiple image features in a metadata format for shared decision-making Health Inform. J. (IF 2.2) Pub Date : 2024-09-21 Chung-Ming Lo, Hui-Ru Chen
Importance: Medical imaging increases the workload involved in writing reports. Given the lack of a standardized format for reports, reports are not easily used as communication tools. Objective: During medical team–patient communication, the descriptions in reports also need to be understood. Automatically generated imaging reports with rich and understandable information can improve medical quality
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The use of the e-SUS Território mobile application in the work of community health workers in Brazil Health Inform. J. (IF 2.2) Pub Date : 2024-09-21 IC Celuppi, RLC Prado, ETB Mohr, F Mioto, JMD Oliveira, M Felisberto, JF Hammes, RS Wazlawick, EM Dalmarco
Objective: Community health workers work directly in the communities and are the intermediaries between the population’s needs and the primary health care teams. Their work focuses on health education and preventing diseases and disorders, accompanying citizens, families, and households in a particular neighborhood. This study sought to analyze the use of the e-SUS Território application in the work
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Demonstrating the data integrity of routinely collected healthcare systems data for clinical trials (DEDICaTe): A proof-of-concept study Health Inform. J. (IF 2.2) Pub Date : 2024-09-19 Macey L Murray, Laura Sato, Jaspal Panesar, Sharon B Love, Rebecca Lee, James R Carpenter, Marion Mafham, Mahesh KB Parmar, Heather Pinches, Matthew R Sydes
Introduction/aims: Healthcare systems data (also known as real-world or routinely collected health data) could transform the conduct of clinical trials. Demonstrating integrity and provenance of these data is critical for clinical trials, to enable their use where appropriate and avoid duplication using scarce trial resources. Building on previous work, this proof-of-concept study used a data intelligence
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AI and disability: A systematic scoping review Health Inform. J. (IF 2.2) Pub Date : 2024-09-18 Christo El Morr, Bushra Kundi, Fariah Mobeen, Sarah Taleghani, Yahya El-Lahib, Rachel Gorman
Background: Artificial intelligence (AI) can enhance life experiences and present challenges for people with disabilities. Objectives: This study aims to investigate the relationship between AI and disability, exploring the potential benefits and challenges of using AI for people with disabilities. Methods: A systematic scoping review was conducted using eight online databases; 45 scholarly articles
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Comparative analysis of machine learning algorithms for predicting diarrhea among under-five children in Ethiopia: Evidence from 2016 EDHS Health Inform. J. (IF 2.2) Pub Date : 2024-09-14 Alemu Birara Zemariam, Wondosen Abey, Abdulaziz Kebede Kassaw, Ali Yimer
Background: Diarrhea is a major cause of mortality and morbidity in under-5 children globally, especially in developing countries like Ethiopia. Limited research has used machine learning to predict childhood diarrhea. This study aimed to compare the predictive performance of ML algorithms for diarrhea in under-5 children in Ethiopia. Methods: The study utilized a dataset of 9501 under-5 children from
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Machine learning approaches for asthma disease prediction among adults in Sri Lanka Health Inform. J. (IF 2.2) Pub Date : 2024-09-14 JRNA Gunawardana, SD Viswakula, Ravindra P Rannan-Eliya, Nilmini Wijemunige
Objectives: Addressing the challenge of cost-effective asthma diagnosis amidst diverse symptom patterns among patients, this study aims to develop a machine learning-based asthma prediction tool for self-detection of asthma. Methods: Data from 6,665 participants in the Sri Lanka Health and Ageing Study (2018-2019) are used for this research. Thirteen machine learning algorithms, including Logistic
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Artificial intelligence and health information: A bibliometric analysis of three decades of research Health Inform. J. (IF 2.2) Pub Date : 2024-09-12 Elham Aldousari, Dennis Kithinji
Information on the application of artificial intelligence (AI) in healthcare is needed to align healthcare transformation efforts. This bibliometric analysis aims to establish the patterns of publication activities on the application of AI in health. A total of 1083 scholarly papers published between 1993 and 2023 were retrieved from the Web of Science and Scopus databases. R Studio and VOSviewer were
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Systematic review of subjective validation methods for computerized colonoscopy simulators Health Inform. J. (IF 2.2) Pub Date : 2024-09-10 Adrián Lugilde-López, Manuel Caeiro-Rodríguez, Fernando A. Mikic-Fonte, Martín Llamas-Nistal
Introduction: In recent years, different approaches have been used to conduct a subjective assessment of colonoscopy simulators. The purpose of this paper is to review these different approaches, specifically the ones used for computerized simulators, as the first step for the design of a standard validation procedure for this type of simulators. Methods: A systematic review was conducted by searching
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Epid data explorer: A visualization tool for exploring and comparing spatio-temporal epidemiological data Health Inform. J. (IF 2.2) Pub Date : 2024-09-04 Laetitia Viau, Jérôme Azé, Fati Chen, Pierre Pompidor, Pascal Poncelet, Vincent Raveneau, Nancy Rodriguez, Arnaud Sallaberry
The analysis of large sets of spatio-temporal data is a fundamental challenge in epidemiological research. As the quantity and the complexity of such kind of data increases, automatic analysis approaches, such as statistics, data mining, machine learning, etc., can be used to extract useful information. While these approaches have proven effective, they require a priori knowledge of the information
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AI-based epidemic and pandemic early warning systems: A systematic scoping review Health Inform. J. (IF 2.2) Pub Date : 2024-08-22 Christo El Morr, Deniz Ozdemir, Yasmeen Asdaah, Antoine Saab, Yahya El-Lahib, Elie Salem Sokhn
Background: Timely detection of disease outbreaks is critical in public health. Artificial Intelligence (AI) can identify patterns in data that signal the onset of epidemics and pandemics. This scoping review examines the effectiveness of AI in epidemic and pandemic early warning systems (EWS). Objective: To assess the capability of AI-based systems in predicting epidemics and pandemics and to identify
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Digital access among a national sample of currently and formerly homeless veterans in 2022 Health Inform. J. (IF 2.2) Pub Date : 2024-08-21 Jack Tsai, Austin Lampros, Jessica Blue-Howells
Background: Digital technologies are essential for connecting to the Internet and communicating with others. Methods: This study used data from the 2022 Project Community Homelessness Assessment, Local Education and Networking Groups (CHALENG) survey, which surveyed a national sample of 1992 homeless-experienced veterans (HEV) about use of cell phones, smart phones, computers, laptops, and the Internet
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‘Humans think outside the pixels’ – Radiologists’ perceptions of using artificial intelligence for breast cancer detection in mammography screening in a clinical setting Health Inform. J. (IF 2.2) Pub Date : 2024-08-19 Jennifer Viberg Johansson, Emma Engström
ObjectiveThis study aimed to explore radiologists’ views on using an artificial intelligence (AI) tool named ScreenTrustCAD with Philips equipment) as a diagnostic decision support tool in mammography screening during a clinical trial at Capio Sankt Göran Hospital, Sweden.MethodsWe conducted semi-structured interviews with seven breast imaging radiologists, evaluated using inductive thematic content
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Putting patients at the center of health information exchange design: An exploration of patient preferences for data sharing Health Inform. J. (IF 2.2) Pub Date : 2024-08-14 Abdulrahman M Jabour
Background: Despite the many benefits of Health Information Exchange (HIE), Studies reported patients concerns about the privacy and security of sharing their health information. To address these concerns, it is important to understand their needs, preferences, and priorities in the design and implementing HIE systems. Objective: The aim of this study is to investigate patients’ preferences for HIE
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Development of a home visit solution with a route- and appointment planning tool for patients with severe spasticity: A participatory design study Health Inform. J. (IF 2.2) Pub Date : 2024-08-14 Lena Skovgård Petersen, Anne Dichmann Sorknæs, Helle Hvilsted Nielsen, Charlotte Nielsen
Objectives: This article describes how a home visit solution was developed in a co-design process between patients in treatment for severe spasticity, their caregivers and hospital nurses. The solution was developed using a participatory design approach and was based on the identified needs of the participants. Methods: We developed a home visit solution through an iterative process and a collective
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Evaluation of treatment information quality on hypertension and diabetes on WeChat and TikTok: A cross-sectional content analysis Health Inform. J. (IF 2.2) Pub Date : 2024-08-14 Minxia Wu, Yongmei Yang, Yanxing Chen
Objective: This study aimed to assess the quality of the information in WeChat and TikTok videos related to hypertension and diabetes treatment. Methods: A sample of 120 Chinese videos was collected based on specific inclusion and exclusion criteria. The quality was evaluated using DISCERN, JAMA and the latest edition of Chinese guidelines for hypertension and diabetes prevention and treatment, and
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Current status and future prospects of Chinese mobile apps for hypertension management Health Inform. J. (IF 2.2) Pub Date : 2024-08-10 Tiantian Song, Jia Tang, Ming Kuang, Hongying Liu
ObjectiveThis study aimed to evaluate the current situation of Chinese mobile apps for hypertension management and explore patients’ real requirements for app use, providing a theoretical basis for the future improvement of hypertension apps.MethodsWe reviewed hypertension management apps from mobile app platforms, and summarized their functional characteristics. In addition, we conducted an online
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Research on entity relation extraction for Chinese medical text Health Inform. J. (IF 2.2) Pub Date : 2024-08-10 Yonghe Lu, Hongyu Chen, Yueyun Zhang, Jiahui Peng, Dingcheng Xiang, Jinxia Zhang
Currently, the primary challenges in entity relation extraction are the existence of overlapping relations and cascading errors. In addressing these issues, both CasRel and TPLinker have demonstrated their competitiveness. This study aims to explore the application of these two models in the context of entity relation extraction from Chinese medical text. We evaluate the performance of these models
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The concept of AI-assisted self-monitoring for skeletal malocclusion Health Inform. J. (IF 2.2) Pub Date : 2024-08-09 Hexian Zhang, Chao Liu, Pingzhu Yang, Sen Yang, Qing Yu, Rui Liu
Background: Skeletal malocclusion is common among populations. Its severity often increases during adolescence, yet it is frequently overlooked. The introduction of deep learning in stomatology has opened a new avenue for self-health management. Methods: In this study, networks were trained using lateral photographs of 2109 newly diagnosed patients. The performance of the models was thoroughly evaluated
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A review of incidents related to health information technology in Swedish healthcare to characterise system issues as a basis for improvement in clinical practice Health Inform. J. (IF 2.2) Pub Date : 2024-08-08 Ding Pan, Evalill Nilsson, Md Shafiqur Rahman Jabin
This study examined health information technology-related incidents to characterise system issues as a basis for improvement in Swedish clinical practice. Incident reports were collected through interviews together with retrospectively collected incidents from voluntary incident databases, which were analysed using deductive and inductive approaches. Most themes pertained to system issues, such as
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Using process model to define the legislative framework of electronic prescription in the Czech Republic Health Inform. J. (IF 2.2) Pub Date : 2024-08-08 Jiří Berger, Jan Bruthans, Adam Vojtěch, Jiří Kofránek
Defining legislation for electronic prescription systems (EPS) is inherently challenging due to conflicting interests and requirements. The study aimed to develop a comprehensive EPS within the Czech healthcare framework, integrating legislative, process, and technical aspects to ensure security, user acceptability, and compliance with health regulations. A process modeling tool based on hierarchical
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Improving the academic resilience of hospital nursing interns through a hybrid multi-criteria decision analysis model Health Inform. J. (IF 2.2) Pub Date : 2024-08-08 Mao Ye, Weifang Xu, Lili Feng, Siqi Liu, Jianhong Yang, Yen-Ching Chuang, Fuqin Tang
Purpose: To identify the main variables affecting the academic adaptability of hospital nursing interns and key areas for improvement in preparing for future unpredictable epidemics. Methods: The importance of academic resilience-related variables for all nursing interns was analyzed using the random forest method, and key variables were further identified. An importance-performance analysis was used
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Machine learning model for osteoporosis diagnosis based on bone turnover markers Health Inform. J. (IF 2.2) Pub Date : 2024-08-08 Seung Min Baik, Hi Jeong Kwon, Yeongsic Kim, Jehoon Lee, Young Hoon Park, Dong Jin Park
To assess the diagnostic utility of bone turnover markers (BTMs) and demographic variables for identifying individuals with osteoporosis. A cross-sectional study involving 280 participants was conducted. Serum BTM values were obtained from 88 patients with osteoporosis and 192 controls without osteoporosis. Six machine learning models, including extreme gradient boosting (XGBoost), light gradient boosting
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Predicting mortality amongst Jordanian men with heart attacks using the chi-square automatic interaction detection model Health Inform. J. (IF 2.2) Pub Date : 2024-08-08 Salam Bani Hani, Muayyad Ahmad
Background: One of the most complicated cardiovascular diseases in the world is heart attack. Since men are the most likely to develop cardiac diseases, accurate prediction of these conditions can help save lives in this population. This study proposed the Chi-Squared Automated Interactive Detection (CHAID) model as a prediction algorithm to forecast death versus life among men who might experience
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Improving uptake of population health management through scalable analysis of linked electronic health data Health Inform. J. (IF 2.2) Pub Date : 2024-08-03 Andras B Varady, Richard M Wood
Population Health Management – often abbreviated to PHM – is a relatively new approach for healthcare planning, requiring the application of analytical techniques to linked patient level data. Despite expectations for greater uptake of PHM, there is a deficit of available solutions to help health services embed it into routine use. This paper concerns the development, application and use of an interactive
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Mixed reality technology for older adults: Evaluating the impact of a novel virtual humanoid coach in a community-based physical exercise program in the Philippines Health Inform. J. (IF 2.2) Pub Date : 2024-08-03 Michael Joseph S. Dino, Kenneth W. Dion, Peter M. Abadir, Chakra Budhathoki, Chien-Ming Huang, Irvin Ong, Joseph Carlo Vital, Valerie T. Cotter, Cheryl R. Dennison Himmelfarb, Patricia M. Davidson
Physical inactivity among older adults remains a global burden, leading to a variety of health challenges and even mortality. This study evaluated the impact of a novel virtual humanoid coach-driven physical exercise program among older adults. A non-randomized (quasi) experimental research was conducted in two community senior centers. The recruited participants ( n = 130) were primarily female older
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A novel technology for harmonizing and analyzing cancer data. Observations from integrating health connect in Newfoundland and Labrador, Canada Health Inform. J. (IF 2.2) Pub Date : 2024-07-26 Jeffrey J Dowden, Ryan W Pretty, Jennifer M Shea, Matthew Dermody, Gregory Doyle, Scott Antle, Dan Bond
Objective: This article aims to describe the implementation of a new health information technology system called Health Connect that is harmonizing cancer data in the Canadian province of Newfoundland and Labrador; explain high-level technical details of this technology; provide concrete examples of how this technology is helping to improve cancer care in the province, and to discuss its future expansion
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Recommended target audience, course content and learning arrangements for teaching health informatics competencies: A scoping review Health Inform. J. (IF 2.2) Pub Date : 2024-07-25 Pauleen Mannevaara, Kaija Saranto, Ulla-Mari Kinnunen, Ursula Hübner
Background: As healthcare depends on health information technology, there is a growing need for Health Informatics competencies in daily practice. This review aimed to explore how the teaching of education in HI has been arranged. 28 publications, published in English between 2016 and 2020 and obtained from selected bibliographic databases, were reviewed. The data was analyzed using deductive content
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The digital divide between primary and secondary care: An analysis using SARS-CoV-2 hospital admissions Health Inform. J. (IF 2.2) Pub Date : 2024-07-25 Amit Sagi, Vipin Asopa, Benjamin Mitchell, Mahalingam Shiyamasundaran, Caleb Koch, Fanuelle Getachew, Irrum Afzal, David Sochart, Richard Field
Using data from two ED. departments of 773 patients admitted with SARS-CoV-2, ICD-10 codes derived from the General Practitioner - Summary Care Record (GP-SCR) and Emergency Department (ED.) records were analysed for code discrepancies and whether this related to increased mortality. The average number of ICD-10 codes in both GP-SCR and ED. records was higher for patients who died than patients who
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Continuously monitoring the human machine? – A cross-sectional study to assess the acceptance of wearables in Germany Health Inform. J. (IF 2.2) Pub Date : 2024-06-20 Michael Hindelang, Hannah Wecker, Tilo Biedermann, Alexander Zink
Background: Wearables have the potential to transform healthcare by enabling early detection and monitoring of chronic diseases. This study aimed to assess wearables’ acceptance, usage, and reasons for non-use. Methods: Anonymous questionnaires were used to collect data in Germany on wearable ownership, usage behaviour, acceptance of health monitoring, and willingness to share data. Results: Out of
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Digital home-based post-treatment exercise interventions for female cancer survivors: A systematic review and meta-analysis Health Inform. J. (IF 2.2) Pub Date : 2024-06-20 Huyen Thi Hoa Nguyen, Nguyen Thi Khanh Huyen, Linh Khanh Bui, Ha Thi Thuy Dinh, Andrew W Taylor-Robinson
Background: Although exercise benefits female cancer survivors, clinical decision-making regarding timing, frequency, duration, and intensity is lacking. Optimizing exercise interventions in this population is necessary. This study aimed to describe existing digital home-based exercises and to assess their effectiveness at improving physical health in female cancer survivors upon completion of therapy
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Override rate of drug-drug interaction alerts in clinical decision support systems: A brief systematic review and meta-analysis Health Inform. J. (IF 2.2) Pub Date : 2024-06-20 Mariano Felisberto, Geovana dos Santos Lima, Ianka Cristina Celuppi, Miliane dos Santos Fantonelli, Wagner Luiz Zanotto, Júlia Meller Dias de Oliveira, Eduarda Talita Bramorski Mohr, Ranieri Alves dos Santos, Daniel Henrique Scandolara, Célio Luiz Cunha, Jades Fernando Hammes, Júlia Salvan da Rosa, Izabel Galhardo Demarchi, Raul Sidnei Wazlawick, Eduardo Monguilhott Dalmarco
Primary studies have demonstrated that despite being useful, most of the drug-drug interaction (DDI) alerts generated by clinical decision support systems are overridden by prescribers. To provide more information about this issue, we conducted a systematic review and meta-analysis on the prevalence of DDI alerts generated by CDSS and alert overrides by physicians. The search strategy was implemented
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Attitudes of patients and mental health professionals towards hypothetical use of serious games in psychotherapy Health Inform. J. (IF 2.2) Pub Date : 2024-06-20 Georgina Spies, Jessica Huss, Oscar Motswage, Soraya Seedat, Christiane Eichenberg
Serious games are increasingly being applied within healthcare, but their integration in psychotherapeutic settings is less documented. Objectives: The present study sought to identify the attitudes of psychotherapists and patients towards the hypothetical use of serious games in psychotherapy in the South African context. Methods: Online surveys assessed acceptance, experience, and requirements for
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Evaluating health information systems-related errors using the human, organization, process, technology-fit (HOPT-fit) framework Health Inform. J. (IF 2.2) Pub Date : 2024-05-28 Maryati Mohd Yusof, Toshihiro Takeda, Yoshie Shimai, Naoki Mihara, Yasuhsi Matsumura
Complex socio-technical health information systems (HIS) issues can create new error risks. Therefore, we evaluated the management of HIS-related errors using the proposed human, organization, process, and technology-fit framework to identify the lessons learned. Qualitative case study methodology through observation, interview, and document analysis was conducted at a 1000-bed Japanese specialist
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Identification of mycoplasma pneumonia in children based on fusion of multi-modal clinical free-text description and structured test data Health Inform. J. (IF 2.2) Pub Date : 2024-05-23 Jingna Xie, Yingshuo Wang, Qiuyang Sheng, Xiaoqing Liu, Jing Li, Fenglei Sun, Yuqi Wang, Shuxian Li, Yiming Li, Yizhou Yu, Gang Yu
Mycoplasma pneumonia may lead to hospitalizations and pose life-threatening risks in children. The automated identification of mycoplasma pneumonia from electronic medical records holds significant potential for improving the efficiency of hospital resource allocation. In this study, we proposed a novel method for identifying mycoplasma pneumonia by integrating multi-modal features derived from both
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A novel deep learning technique for medical image analysis using improved optimizer Health Inform. J. (IF 2.2) Pub Date : 2024-05-17 Vertika Agarwal, MC Lohani, Ankur Singh Bist
Application of Convolutional neural network in spectrum of Medical image analysis are providing benchmark outputs which converges the interest of many researchers to explore it in depth. Latest preprocessing technique Real ESRGAN (Enhanced super resolution generative adversarial network) and GFPGAN (Generative facial prior GAN) are proving their efficacy in providing high resolution dataset. Objective:
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Paving the way for COVID survivors’ psychosocial rehabilitation: Mining topics, sentiments, and their trajectories over time from Reddit Health Inform. J. (IF 2.2) Pub Date : 2024-05-13 Moez Farokhnia Hamedani, Mostafa Esmaeili, Yao Sun, Ehsan Sheybani, Giti Javidi
Objective: This study examined major themes and sentiments and their trajectories and interactions over time using subcategories of Reddit data. The aim was to facilitate decision-making for psychosocial rehabilitation. Materials and Methods: We utilized natural language processing techniques, including topic modeling and sentiment analysis, on a dataset consisting of more than 38,000 topics, comments
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Determining pre-procedure fasting alert time using procedural and scheduling data Health Inform. J. (IF 2.2) Pub Date : 2024-05-09 Litong Zheng, J Christopher Beck, Sebastian Mafeld, Matteo Parotto, Amanda Matthews, Sheryl Alexandre, Aaron Conway
Before a medical procedure requiring anesthesia, patients are required to not eat or drink non-clear fluids for 6 h and not drink clear fluids for 2 h. Fasting durations in standard practice far exceed these minimum thresholds due to uncertainties in procedure start time. The aim of this retrospective, observational study was to compare fasting durations arising from standard practice with different
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REDCap to Epic interfaces create an efficient hybrid software solution for a public health registry Health Inform. J. (IF 2.2) Pub Date : 2024-05-08 Marty Crawford, Nicole Jones, Jonathan Babbage, Morgan Edwards, Casey Bryson, Mona Hanna-Attisha
A public health registry and intervention was created in response to the Flint water crisis to identify and refer exposed individuals to public health services to ameliorate the deleterious impact of lead exposure. Traditional technology architecture domains, funded scope of work, as well as community input were considered when defining the requirements of the selected solutions. A hybrid software
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Impact of Remote Medical Devices on Utilization of Medical Services in Pediatric Patients with Upper Respiratory Infections: A Retrospective Study Health Inform. J. (IF 2.2) Pub Date : 2024-04-08 Inbal Mozes, Orna Baron-Epel, Anthony Heymann
Background: Remote mobile examination devices in telemedicine are a new technology in healthcare. Objective: To assess the utilization of visits using remote medical devices. Methods: A retrospective analysis of follow-up visits, referrals, laboratory testing and antibiotic prescriptions of 470,845 children’s video visits with and without remote medical examination device and in-clinic visits. Results:
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How can current oncological datasets be adjusted to support the automated patient recruitment in clinical trials? Health Inform. J. (IF 2.2) Pub Date : 2024-03-16 Maria-Luisa Marino, Lara Kazmaier, Antonia Krendelsberger, Silvia Müller, Sabine Kesting, Theres Fey, Daniel Nasseh
Objectives: This study aims to identify necessary adjustments required in existing oncological datasets to effectively support automated patient recruitment. Methods: We extracted and categorized the inclusion and exclusion criteria from 115 oncological trials registered on ClinicalTrials.gov in 2022. These criteria were then compared with the content of the oBDS (Oncological Base Dataset version 3
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Characteristics of the most viewed Hybrid Assistive Limb-related videos on YouTube Health Inform. J. (IF 2.2) Pub Date : 2024-02-29 Makoto Nagasawa, Sho Nakamura, Hiroto Narimatsu
Objectives. YouTube is one of the most popular video-sharing tools and is used as a forum for sharing information about experiences with new technology-based exercise programs, such as the wearable cyborg Hybrid Assistive Limb (HAL). This study aimed to analyze the content and quality of HAL-related videos viewed by people to clarify the content required by YouTube viewers. Methods. We searched HAL-related
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A study on the risk stratification for patients within 24 hours of admission for risk of hospital-acquired urinary tract infection using Bayesian network models Health Inform. J. (IF 2.2) Pub Date : 2024-02-29 Rune Sejer Jakobsen, Thomas Dyhre Nielsen, Peter Leutscher, Kristoffer Koch
Early identification of patients at risk of hospital-acquired urinary tract infections (HA-UTI) enables the initiation of timely targeted preventive and therapeutic strategies. Machine learning (ML) models have shown great potential for this purpose. However, existing ML models in infection control have demonstrated poor ability to support explainability, which challenges the interpretation of the
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Sentiment analysis of the COVID-19 vaccine perception Health Inform. J. (IF 2.2) Pub Date : 2024-02-26 Byeonghwa Park, In Suk Jang, Daehan Kwak
The sharp rise in coronavirus cases in the United States, as well as other countries, is driven by variants such as the Omicron substrain, BA4 and BA5. Keeping up to date with COVID-19 vaccination and wearing masks are essential tools for mitigating the pandemic. Social media plays a vital role in sharing and exchanging information, but it also affects perceptions of social phenomena. In this study
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Detecting atypical alert behavior through statistical process control: Clinical decision support alert frequency visualizations Health Inform. J. (IF 2.2) Pub Date : 2024-02-17 Kevin E Kindler, Peter J Martinson
Clinical decision support (CDS) alerts are designed to work according to a set of clearly defined criteria and have the potential to improve clinical care. To efficiently and proactively review abnormally functioning CDS alerts, we postulate that the introduction of a dashboard with statistical process control (SPC) charting will lead to effective detection of erratic alert behavior. We identified
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Nurses’ and physicians’ perceptions of the impact of eHealth and information systems on the roles of health care professionals: A qualitative descriptive study Health Inform. J. (IF 2.2) Pub Date : 2024-02-16 Taija Lottonen, Anu-Marja Kaihlanen, Janna Nadav, Pirjo Hilama, Tarja Heponiemi
The increased use of eHealth and information systems impacts health care work broadly, including cultural and social aspects of work such as the roles of health care professionals. This qualitative descriptive study examined the perceptions of health care professionals in terms of how eHealth and information systems have changed their roles. The data was collected via 15 semi-structured thematic interviews
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Community health pathways modeling and scheduling under uncertainty Health Inform. J. (IF 2.2) Pub Date : 2024-02-06 Jiangyue Gong, Lewis Ntaimo
Scheduling and coordinating constrained resources in community healthcare settings at a centralized Pathways Community HUB is challenging due to limited resources and the inherent dynamics of the processes and the organizational structures. In this work, we introduce a stochastic programming (SP) approach for connected community health for optimally scheduling community health pathways (CHPs) under
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The quality, suitability, and readability of web-based resources on endometriosis-associated dyspareunia: A systematic review Health Inform. J. (IF 2.2) Pub Date : 2024-02-03 Abdul-Fatawu Abdulai, A.Fuchsia Howard, Gurkiran Parmar, Heather Noga, Abdul Aziz Abdul- Ghafoor, Michelle Lisonek, Paul J Yong
People commonly and increasingly rely on the internet to search for health information, including those related to endometriosis-associated dyspareunia. Yet the content of such websites may be of variable accuracy and quality. This review aims to evaluate the quality, readability, and suitability of web-based resources on endometriosis-associated dyspareunia for patients. We searched 3 databases –
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Identification of high-risk beneficiaries in private healthcare insurance Health Inform. J. (IF 2.2) Pub Date : 2024-02-01 Adauto Santos, Gislaine Camila Lapasini Leal, Renato Balancieri
The objective of this study was to apply the Knowledge Discovery in Databases process to find out if beneficiaries of a private healthcare insurance would belong, at least once, to the ‘very high cost’ and ‘complex cases’ groups throughout the 12 months after the month when algorithms were applied. Datasets were built containing information on beneficiaries’ effective use of their health plan, as well
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Anatomically Integrated In-Place Visualization of Patient Data for Cooperative Tasks with a Case Study on a Neurosurgical Ward Health Inform. J. (IF 2.2) Pub Date : 2023-05-03 Dmitri Presnov, Julia Kurz, Judith Willkomm, Johannes Dillmann, Daniel Alt, Robert Zilke, Veit Braun, Cornelius Schubert, Andreas Kolb
The workflow in modern hospitals entails that the medical treatment of a patient is distributed between several physicians and nurses. This leads to intensive cooperation, which takes place under p...
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A multimodal fusion enabled ensemble approach for human activity recognition in smart homes Health Inform. J. (IF 2.2) Pub Date : 2023-04-28 Weimin Ding, Shengli Wu, Chris Nugent
How to deal with multi-modality data from different types of devices is a challenging issue for accurate recognition of human activities in a smart environment. In this paper, we propose a multimod...
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Technology-based interprofessional collaboration in primary care for home rehabilitation of the older adults: A dutch exploratory study Health Inform. J. (IF 2.2) Pub Date : 2023-04-21 Laurence Alpay, Ybranda Koster, Joan Dallinga, Petra Siemonsma, John Verhoef, Erzy Kassens, Pieter Flaton, Koen Baars, Floor van Kessel
Primary healthcare professionals face an increasing number of geriatrics patients, and patient care often involves different disciplines. eHealth offers opportunities to support interprofessional c...
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Telemedicine technologies and applications in the era of COVID-19 pandemic: A systematic review Health Inform. J. (IF 2.2) Pub Date : 2023-04-19 Esmaeil Mehraeen, SeyedAhmad SeyedAlinaghi, Mohammad Heydari, Amirali Karimi, Abdollah Mahdavi, Mehrnaz Mashoufi, Arezoo Sarmad, Peyman Mirghaderi, Ahmadreza Shamsabadi, Kowsar Qaderi, Pegah Mirzapour, Amirata Fakhfouri, Hadiseh Azadi Cheshmekabodi, Kimia Azad, SeyedAli Bagheri Zargande, Shahram Oliaei, Parisa Yousefi Konjdar, Farzin Vahedi, Tayebeh Noori
IntroductionTelemedicine services saw substantial surges in their use during the COVID-19 pandemic due to the lockdowns and characteristics of the pandemic. Therefore, the authors aimed to systemat...
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Acuity-based rotational patient-to-physician assignment in an emergency department using electronic health records in triage Health Inform. J. (IF 2.2) Pub Date : 2023-04-17 Marta Cildoz, Amaia Ibarra, Fermin Mallor
Emergency department (ED) operational metrics generated by a new acuity-based rotational patient-to-physician assignment (ARPA) algorithm are compared with those obtained with a simple rotational p...
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Programming techniques for improving rule readability for rule-based information extraction natural language processing pipelines of unstructured and semi-structured medical texts Health Inform. J. (IF 2.2) Pub Date : 2023-04-17 Nektarios Ladas, Florian Borchert, Stefan Franz, Alina Rehberg, Natalia Strauch, Kim Katrin Sommer, Michael Marschollek, Matthias Gietzelt
BackgroundExtraction of medical terms and their corresponding values from semi-structured and unstructured texts of medical reports can be a time-consuming and error-prone process. Methods of natur...
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Evaluating robustness of a generalized linear model when applied to electronic health record data accessed using an Open API Health Inform. J. (IF 2.2) Pub Date : 2023-04-17 Priya Sharma, Perry Haaland, Ashok Krishnamurthy, Bo Lan, Patrick L Schmitt, Meghamala Sinha, Hao Xu, Karamarie Fecho
The Integrated Clinical and Environmental Exposures Service (ICEES) provides open regulatory-compliant access to clinical data, including electronic health record data, that have been integrated wi...
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Prevalence and patterns of mobile device usage among physicians in clinical practice: A systematic review Health Inform. J. (IF 2.2) Pub Date : 2023-04-17 Judith Kraushaar, Sabine Bohnet-Joschko
Mobile devices and corresponding applications (apps) offer a unique potential for clinical work improvement. Healthcare employees already use them for a variety of clinical purposes. Even though th...
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Predicting opioid use disorder before and after the opioid prescribing peak in the United States: A machine learning tool using electronic healthcare records Health Inform. J. (IF 2.2) Pub Date : 2023-04-12 Tyler J Banks, Tung D Nguyen, Jeffery K Uhlmann, Satish S Nair, Jeffrey F Scherrer
Existing predictive models of opioid use disorder (OUD) may change as the rate of opioid prescribing decreases. Using Veterans Administration’s EHR data, we developed machine-learning predictive mo...
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Quality and readability of online information on hand osteoarthritis Health Inform. J. (IF 2.2) Pub Date : 2023-03-30 Seok Woo Hong, Jeong-Hyun Kang, Jun Hyoung Park, Hee Jin Park, Eugene Kim
Objectives: This study aimed to evaluate the quality and readability of web pages providing information about hand osteoarthritis using several authorized methods.Methods: A web page exploration wa...
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Suicide in services for mental health and substance use: A national hybrid registry surveillance system Health Inform. J. (IF 2.2) Pub Date : 2023-03-29 Martin Ø Myhre, Anine T Kildahl, Helene Astrup, Dagfinn Bergsager, Fredrik A Walby
Suicide is strongly associated with mental health and substance use disorders, which makes mental health- and substance misuse services important areas for suicide prevention. The aim of The Norweg...
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Prescreening in oncology trials using medical records. Natural language processing applied on lung cancer multidisciplinary team meeting reports Health Inform. J. (IF 2.2) Pub Date : 2023-03-24 Marie Ansoborlo, Christophe Gaborit, Leslie Grammatico-Guillon, Marc Cuggia, Guillaume Bouzille
Defining profiles of patients that could benefit from relevant anti-cancer treatments is essential. An increasing number of specific criteria are necessary to be eligible to specific anti-cancer th...