Estrella Paterson, Satyan Chari, Linda McCormack, Penelope Sanderson
Over the past decade, healthcare systems have started to establish control centres to manage patient flow, with a view to removing delays and increasing the quality of care. Such centres-here dubbed Healthcare Capacity Command/Coordination Centres (HCCCs)-are a challenge to design and operate. Broad-ranging surveys of HCCCs have been lacking, and design for their human users is only starting to be addressed. In this review we identified 73 papers describing different kinds of HCCCs, classifying them according to whether they describe virtual or physical control centres, the kinds of situations they handle, and the different levels of Rasmussen's [1] risk management framework that they integrate...
June 18, 2024: Journal of Medical Systems
Nikola Kirilov, E Bischoff
The rapid development of the digital healthcare and the electronic health records (EHR) requires smooth networking infrastructure to access data using Hypertext Transfer Protocol (HTTP)-based applications. The new HTTP/3 standard should provide performance and security improvements over HTTP/2. The goal of our work was to test the performance of HTTP/2 and HTTP/3 in the context of the EHRs. We used 45,000 test FHIR Patient resources downloaded and uploaded using 20, 50, 100 and 200 resources per Bundle, which resulted in 2251, 901, 451 and 226 HTTP GET and POST requests respectively...
June 15, 2024: Journal of Medical Systems
Jacob C Clifton, Holly B Ende, Chandramouli Rathnam, Robert E Freundlich, Warren S Sandberg, Jonathan P Wanderer
Transition to the postanesthesia care unit (PACU) requires timely order placement by anesthesia providers. Computerized ordering enables automated order reminder systems, but their value is not fully understood. We performed a single-center, retrospective cohort study to estimate the association between automated PACU order reminders and primary outcomes (1) on-time order placement and (2) the degree of delay in placement. As a secondary post-hoc analysis, we studied the association between late order placement and PACU outcomes...
June 10, 2024: Journal of Medical Systems
Shiavax J Rao, Ameesh Isath, Parvathy Krishnan, Jonathan A Tangsrivimol, Hafeez Ul Hassan Virk, Zhen Wang, Benjamin S Glicksberg, Chayakrit Krittanawong
Artificial Intelligence, specifically advanced language models such as ChatGPT, have the potential to revolutionize various aspects of healthcare, medical education, and research. In this narrative review, we evaluate the myriad applications of ChatGPT in diverse healthcare domains. We discuss its potential role in clinical decision-making, exploring how it can assist physicians by providing rapid, data-driven insights for diagnosis and treatment. We review the benefits of ChatGPT in personalized patient care, particularly in geriatric care, medication management, weight loss and nutrition, and physical activity guidance...
June 5, 2024: Journal of Medical Systems
Pei-Fu Chen, Franklin Dexter
Modern anesthetic drugs ensure the efficacy of general anesthesia. Goals include reducing variability in surgical, tracheal extubation, post-anesthesia care unit, or intraoperative response recovery times. Generalized confidence intervals based on the log-normal distribution compare variability between groups, specifically ratios of standard deviations. The alternative statistical approaches, performing robust variance comparison tests, give P-values, not point estimates nor confidence intervals for the ratios of the standard deviations...
June 1, 2024: Journal of Medical Systems
Luca Neri, Ivan Corazza, Matt T Oberdier, Jessica Lago, Ilaria Gallelli, Arrigo F G Cicero, Igor Diemberger, Alessandro Orro, Amir Beker, Nazareno Paolocci, Henry R Halperin, Claudio Borghi
Wearable electronics are increasingly common and useful as health monitoring devices, many of which feature the ability to record a single-lead electrocardiogram (ECG). However, recording the ECG commonly requires the user to touch the device to complete the lead circuit, which prevents continuous data acquisition. An alternative approach to enable continuous monitoring without user initiation is to embed the leads in a garment. This study assessed ECG data obtained from the YouCare device (a novel sensorized garment) via comparison with a conventional Holter monitor...
May 27, 2024: Journal of Medical Systems
Yang Cao, Guochao Zhang, You Wu, Hang Yi
The rapid growth of internet users in China presents opportunities for advancing the "Healthy China 2030" initiative through online health education. Platforms like "Shanghai Health Cloud" and "National Health Information Platform" improve health literacy and management, enhancing overall public health. However, challenges such as the digital divide and the spread of unverified health information hinder progress. Addressing these issues requires enhancing digital infrastructure, employing advanced technologies for information validation, and setting high standards for online health services...
May 27, 2024: Journal of Medical Systems
Mohamad-Hani Temsah, Abdullah N Alhuzaimi, Mohammed Almansour, Fadi Aljamaan, Khalid Alhasan, Munirah A Batarfi, Ibraheem Altamimi, Amani Alharbi, Adel Abdulaziz Alsuhaibani, Leena Alwakeel, Abdulrahman Abdulkhaliq Alzahrani, Khaled B Alsulaim, Amr Jamal, Afnan Khayat, Mohammed Hussien Alghamdi, Rabih Halwani, Muhammad Khurram Khan, Ayman Al-Eyadhy, Rakan Nazer
Artificial Intelligence (AI), particularly AI-Generated Imagery, has the potential to impact medical and patient education. This research explores the use of AI-generated imagery, from text-to-images, in medical education, focusing on congenital heart diseases (CHD). Utilizing ChatGPT's DALL·E 3, the research aims to assess the accuracy and educational value of AI-created images for 20 common CHDs. In this study, we utilized DALL·E 3 to generate a comprehensive set of 110 images, comprising ten images depicting the normal human heart and five images for each of the 20 common CHDs...
May 23, 2024: Journal of Medical Systems
Jianning Li, David G Ellis, Antonio Pepe, Christina Gsaxner, Michele R Aizenberg, Jens Kleesiek, Jan Egger
Designing implants for large and complex cranial defects is a challenging task, even for professional designers. Current efforts on automating the design process focused mainly on convolutional neural networks (CNN), which have produced state-of-the-art results on reconstructing synthetic defects. However, existing CNN-based methods have been difficult to translate to clinical practice in cranioplasty, as their performance on large and complex cranial defects remains unsatisfactory. In this paper, we present a statistical shape model (SSM) built directly on the segmentation masks of the skulls represented as binary voxel occupancy grids and evaluate it on several cranial implant design datasets...
May 23, 2024: Journal of Medical Systems
Mohammad Saiduzzaman Sayed, Mohammad Abu Tareq Rony, Mohammad Shariful Islam, Ali Raza, Sawsan Tabassum, Mohammad Sh Daoud, Hazem Migdady, Laith Abualigah
Myocardial Infarction (MI) commonly referred to as a heart attack, results from the abrupt obstruction of blood supply to a section of the heart muscle, leading to the deterioration or death of the affected tissue due to a lack of oxygen. MI, poses a significant public health concern worldwide, particularly affecting the citizens of the Chittagong Metropolitan Area. The challenges lie in both prevention and treatment, as the emergence of MI has inflicted considerable suffering among residents. Early warning systems are crucial for managing epidemics promptly, especially given the escalating disease burden in older populations and the complexities of assessing present and future demands...
May 22, 2024: Journal of Medical Systems
Zhi-Qiang Li, Xue-Feng Wang, Jian-Ping Liu
This study aimed to analyze the current landscape of ChatGPT application in the medical field, assessing the current collaboration patterns and research topic hotspots to understand the impact and trends. By conducting a search in the Web of Science, we collected literature related to the applications of ChatGPT in medicine, covering the period from January 1, 2000 up to January 16, 2024. Bibliometric analyses were performed using CiteSpace (V6.2., Drexel University, PA, USA) and Microsoft Excel (Microsoft Corp...
May 18, 2024: Journal of Medical Systems
H Abedian Kalkhoran, J Zwaveling, F van Hunsel, A Kant
Reports from spontaneous reporting systems (SRS) are hypothesis generating. Additional evidence such as more reports is required to determine whether the generated drug-event associations are in fact safety signals. However, underreporting of adverse drug reactions (ADRs) delays signal detection. Through the use of natural language processing, different sources of real-world data can be used to proactively collect additional evidence for potential safety signals. This study aims to explore the feasibility of using Electronic Health Records (EHRs) to identify additional cases based on initial indications from spontaneous ADR reports, with the goal of strengthening the evidence base for potential safety signals...
May 16, 2024: Journal of Medical Systems
Roberto Trevi, Stefania Chiappinotto, Alvisa Palese, Alessandro Galazzi
INTRODUCTION: Virtual reality (VR) is becoming increasingly popular to train health-care professionals (HCPs) to acquire and/or maintain cardiopulmonary resuscitation (CPR) basic or advanced skills. AIM: To understand whether VR in CPR training or retraining courses can have benefits for patients (neonatal, pediatric, and adult), HCPs and health-care organizations as compared to traditional CPR training. METHODS: A systematic review (PROSPERO: CRD42023431768) following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines...
May 15, 2024: Journal of Medical Systems
Widana Kankanamge Darsha Jayamini, Farhaan Mirza, M Asif Naeem, Amy Hai Yan Chan
Asthma, a common chronic respiratory disease among children and adults, affects more than 200 million people worldwide and causes about 450,000 deaths each year. Machine learning is increasingly applied in healthcare to assist health practitioners in decision-making. In asthma management, machine learning excels in performing well-defined tasks, such as diagnosis, prediction, medication, and management. However, there remain uncertainties about how machine learning can be applied to predict asthma exacerbation...
May 13, 2024: Journal of Medical Systems
Benjamin Friedrichson, Markus Ketomaeki, Thomas Jasny, Oliver Old, Lea Grebe, Elina Nürenberg-Goloub, Elisabeth H Adam, Kai Zacharowski, Jan Andreas Kloka
In Germany, a comprehensive reimbursement policy for extracorporeal membrane oxygenation (ECMO) results in the highest per capita use worldwide, although benefits remain controversial. Public ECMO data is unstructured and poorly accessible to healthcare professionals, researchers, and policymakers. In addition, there are no uniform policies for ECMO allocation which confronts medical personnel with ethical considerations during health crises such as respiratory virus outbreaks.Retrospective information on adult and pediatric ECMO support performed in German hospitals was extracted from publicly available reimbursement data and hospital quality reports and processed to create the web-based ECMO Dashboard built on Open-Source software...
May 10, 2024: Journal of Medical Systems
Fatimah Altuhaifa, Dalal Al Tuhaifa
Ontologies serve as comprehensive frameworks for organizing domain-specific knowledge, offering significant benefits for managing clinical data. This study presents the development of the Fall Risk Management Ontology (FRMO), designed to enhance clinical text mining, facilitate integration and interoperability between disparate data sources, and streamline clinical data analysis. By representing major entities within the fall risk management domain, the FRMO supports the unification of clinical language and decision-making processes, ultimately contributing to the prevention of falls among older adults...
April 25, 2024: Journal of Medical Systems
J A Poppe, R S Smorenburg, T G Goos, H R Taal, I K M Reiss, S H P Simons
BACKGROUND: Preterm neonates are extensively monitored to require strict oxygen target attainment for optimal outcomes. In daily practice, detailed oxygenation data are hardly used and crucial patterns may be missed due to the snapshot presentations and subjective observations. This study aimed to develop a web-based dashboard with both detailed and summarized oxygenation data in real-time and to test its feasibility to support clinical decision making. METHODS: Data from pulse oximeters and ventilators were synchronized and stored to enable real-time and retrospective trend visualizations in a web-based viewer...
April 24, 2024: Journal of Medical Systems
Thiago C Moulin
In medical and biomedical education, traditional teaching methods often struggle to engage students and promote critical thinking. The use of AI language models has the potential to transform teaching and learning practices by offering an innovative, active learning approach that promotes intellectual curiosity and deeper understanding. To effectively integrate AI language models into biomedical education, it is essential for educators to understand the benefits and limitations of these tools and how they can be employed to achieve high-level learning outcomes...
April 23, 2024: Journal of Medical Systems
Joelle Yan Xin Chua, Enci Mary Kan, Phin Peng Lee, Shefaly Shorey
The Stanford Biodesign needs-centric framework can guide healthcare innovators to successfully adopt the 'Identify, Invent and Implement' framework and develop new healthcare innovations products to address patients' needs. This scoping review explored the application of the Stanford Biodesign framework for healthcare innovation training and the development of novel healthcare innovative products. Seven electronic databases were searched from their respective inception dates till April 2023: PubMed, Embase, CINAHL, PsycINFO, Web of Science, Scopus, ProQuest Dissertations, and Theses Global...
April 22, 2024: Journal of Medical Systems
Arya Rao, John Kim, Winston Lie, Michael Pang, Lanting Fuh, Keith J Dreyer, Marc D Succi
Polypharmacy remains an important challenge for patients with extensive medical complexity. Given the primary care shortage and the increasing aging population, effective polypharmacy management is crucial to manage the increasing burden of care. The capacity of large language model (LLM)-based artificial intelligence to aid in polypharmacy management has yet to be evaluated. Here, we evaluate ChatGPT's performance in polypharmacy management via its deprescribing decisions in standardized clinical vignettes...
April 18, 2024: Journal of Medical Systems
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