Background The rapid dissemination of smart devices within the internet of things (IoT) is developing toward automatic emergency alerts which are transmitted from machine to machine without human interaction. However, apart from individual projects concentrating on single types of accidents, there is no general methodology of connecting the standalone information and communication technology (ICT)

Background While electronic health records have been collected for many years in Taiwan, their interoperability across different health care providers has not been entirely achieved yet. The exchange of clinical data is still inefficient and time consuming. Objectives This study proposes an efficient patient-centric framework based on the blockchain technology that makes clinical data accessible to

Objectives Artificial intelligence (AI), including predictive analytics, has great potential to improve the care of common chronic conditions with high morbidity and mortality. However, there are still many challenges to achieving this vision. The goal of this project was to develop and apply methods for enhancing chronic disease care using AI. Methods Using a dataset of 27,904 patients with diabetes

Background As a major public health crisis, the novel coronavirus disease 2019 (COVID-19) pandemic demonstrates the urgent need for safe, effective, and evidence-based implementations of digital health. The urgency stems from the frequent tendency to focus attention on seemingly high promising digital health interventions despite being poorly validated in times of crisis. Aim In this paper, we describe

Background The adherence to inhaled controller medications is of critical importance for achieving good clinical results in patients with chronic respiratory diseases. Self-management strategies can result in improved health outcomes and reduce unscheduled care and improve disease control. However, adherence assessment suffers from difficulties on attaining a high grade of trustworthiness given that

Background Higher enrolment rates of cancer patients into clinical trials are necessary to increase cancer survival. As a prerequisite, an improved semiautomated matching of patient characteristics with clinical trial eligibility criteria is needed. This is based on the computer interpretability, i.e., structurability of eligibility criteria texts. To increase structurability, the common content, phrasing

Background Patient registries are an established methodology in health services research. Since more than 150 years, registries collect information concerning groups of similar patients to answer research questions. Elaborated recommendations about an appropriate development and an efficient operation of registries are available. However, the scene changes rapidly. Objectives The aim of the study is

Background Tuberculosis (TB) is an infectious disease and is among the top 10 causes of death in the world, and Brazil is part of the top 30 high TB burden countries. Data collection is an essential practice in health studies, and the adoption of electronic data capture (EDC) systems can positively increase the experience of data acquisition and analysis. Also, data-sharing capabilities are crucial

Background Restrictions on social interaction and movement were implemented by the German government in March 2020 to reduce the transmission of coronavirus disease 2019 (COVID-19). Apple's “Mobility Trends” (AMT) data details levels of community mobility; it is a novel resource of potential use to epidemiologists. Objective The aim of the study is to use AMT data to examine the relationship between

Background An adequate sample size calculation is essential for designing a successful clinical trial. One way to tackle planning difficulties regarding parameter assumptions required for sample size calculation is to adapt the sample size during the ongoing trial. This can be attained by adaptive group sequential study designs. At a predefined timepoint, the interim effect is tested for significance

Background Patients may seek health care services from various providers during treatment. These providers could serve in a network (affiliated) or practice separately (unaffiliated). Thus, using secure and reliable health information exchange (HIE) mechanisms would be critical to transfer sensitive personal health information (PHI) across distances. Studying patients' perceptions and opinions about

Background An accurate and reproducible method to delineate tumor margins is of great importance in clinical diagnosis and treatment. In nasopharyngeal carcinoma (NPC), due to limitations such as high variability, low contrast, and discontinuous boundaries in presenting soft tissues, tumor margin can be extremely difficult to identify in magnetic resonance imaging (MRI), increasing the challenge of

Background Neonates are highly vulnerable to preventable medication errors due to their extensive exposure to medications in the neonatal intensive care units (NICUs). These errors, which can be made by medical, nursing, or pharmacy personnel, are costly and can be life-threatening. This study aimed to investigate the newly developed computerized neonatal pharmaceutical health care system (NPHCS) in

Background Many countries adopt eHealth applications to support patient-centered care. Through information exchange, these eHealth applications may overcome institutional data silos and support holistic and ubiquitous (regional or national) information logistics. Available eHealth indicators mostly describe usage and acceptance of eHealth in a country. The eHealth indicators focusing on the cross-institutional

Objective In this study, we aimed to evaluate the capability of the Unified Medical Language System (UMLS) as one data standard to support data normalization and harmonization of datasets that have been developed for rare diseases. Through analysis of data mappings between multiple rare disease resources and the UMLS, we propose suggested extensions of the UMLS that will enable its adoption as a global

Background Physical rehabilitation exergames (PREGs) are suitable for motivating patients toward completing treatments. Leap Motion (LM) is a motion sensor that may be useful for developing PREGs targeted at hands and fingers rehabilitation. Therefore, knowing the advantages and limitations of LM is relevant to understand under which conditions this sensor may be suitable. Objective In this article

Background Integration of health data systems is an open problem. Most of the active initiatives are based on the use of standards. However, achieving a widely and generalized compliment of such standards still seems a costly task that will take a long time to be completed. Even more, most of the standards are proposed for a specific use, without integrating other needs. Objectives We propose an alternative

Background Telepresence robots used to deliver a point-of-care (POC) consultation system that may provide value to enable effective decision making by healthcare providers at care sites. Objectives This study aimed to evaluate usability of teleconsultation robots, based on endusers' needs, that can improve acceptance in future robot applications. Methods This is a single group postdesign study using

Abstract Objectives To develop and present the methods utilized for the Dental, Oral, Medical Epidemiological (DOME) study. Methods The DOME is an electronic record-based cross-sectional study, that was conducted to measure the dental, periodontal, and oral morbidities and their associations with systemic morbidities, among a nationally representative sample of young to middle-aged adults military

Abstract Background Merging disparate and heterogeneous datasets from clinical routine in a standardized and semantically enriched format to enable a multiple use of data also means incorporating unstructured data such as medical free texts. Although the extraction of structured data from texts, known as natural language processing (NLP), has been researched at least for the English language extensively

Abstract Background This article describes the development and evaluation of a distributed user interface (DUI) application to assess visuomotor organization ability. This application enables therapists to evaluate the acquired brain injury (ABI) on patients, and patients, to perform the assessment on a touch screen while therapists can observe the assessment process in real time on a separated monitor

Abstract Background The clinical research data lifecycle, from data collection to analysis results, functions in silos that restrict traceability. Traceability is a requirement for regulated clinical research studies and an important attribute of nonregulated studies. Current clinical research software tools provide limited metadata traceability capabilities and are unable to query variables across

Background Methods of Information in Medicine (Methods) is the “longest running journal devoted to information in biomedicine and health care.”[1] Since its foundation in 1962, Methods has stressed the methodology and scientific fundamentals of organizing, representing, and analyzing data, information, and knowledge in biomedicine and health care. Publications covered a broad spectrum in the fields

Introduction Physical rehabilitation is generally perceived as a face-to-face interaction between therapist and patient. However, thanks to technology developments, this picture has been changed. The massive innovation of information and communication technologies (ICTs) has brought a revolution to the view of health, people, and work.[1] Especially, the application of virtual reality (VR) and augmented

Abstract Background The majority of new cancer cases are expected to be diagnosed in low- and middle-income countries (LMICs) by 2025, and 65% of cancer deaths currently occur in LMICs. Treatment adherence, patient monitoring, and follow-up are essential to cancer care but are often not possible in these settings. Out Patient (OP) Care, a smartphone application (app) developed to fill this gap, texts

Abstract Background and Objectives The penetration rate of physical examinations in China is substantially lower than that in developed countries. Therefore, an auxiliary approach that does not depend on hospital health checks for the diagnosis of metabolic syndrome (MetS) is needed. Methods In this study, we proposed an augmented method with inferred blood features that uses self-care inputs available

Abstract Background After discharge from a rehabilitation center the continuation of therapy is necessary to secure already achieved healing progress and sustain (re-)integration into working life. To this end, home-based exercise programs are frequently prescribed. However, many patients do not perform their exercises as frequently as prescribed or even with incorrect movements. The telerehabilitation

Abstract Background Scientific publications are meant to exchange knowledge among researchers but the inability to properly reproduce computational experiments limits the quality of scientific research. Furthermore, bibliography shows that irreproducible preclinical research exceeds 50%, which produces a huge waste of resources on nonprofitable research at Life Sciences field. As a consequence, scientific

Abstract Objectives This study analyzed patient factors in medication persistence after discharge from the first hospitalization for cardiovascular disease (CVD) with the aim of predicting persistence to lipid-lowering therapy for 1 to 2 years. Methods A subcohort having a first CVD hospitalization was selected from 313,207 patients for proportional hazard model analysis. Logistic regression, support

Abstract Background Many elderly people suffer from chronic health conditions and mobility limitations. Therefore, they may benefit from traditional rehabilitation or telerehabilitation interventions as an alternative for this type of services. Objective The purpose of this study was to compare the effectiveness of telerehabilitation interventions with traditional rehabilitation services for therapeutic

Abstract Background FAIR (findability, accessibility, interoperability, and reusability) guiding principles seek the reuse of data and other digital research input, output, and objects (algorithms, tools, and workflows that led to that data) making them findable, accessible, interoperable, and reusable. GO FAIR - a bottom-up, stakeholder driven and self-governed initiative - defined a seven-step FAIRification

Abstract Background Due to the ongoing increase and importance of the sustainable reusability of data, the findable, accessible, interoperable, reusable or FAIR principles were developed which are also relevant in translational research. Objectives The study aims at identification of platforms by literature search that are suitable for implementation in translational research, in particular with regard

Abstract Background Against the background of a steadily increasing degree of digitalization in health care, a professional information management (IM) is required to successfully plan, implement, and evaluate information technology (IT). At its core, IM has to ensure a high quality of health data and health information systems to support patient care. Objectives The goal of the present study was to

Abstract Unsupervised home exercise is a major component of physical therapy (PT). This study proposes an inexpensive, inertial measurement unit-based wearable device to capture kinematic data to facilitate exercise. However, conveying and interpreting kinematic data to non-experts poses a challenge due to the complexity and background knowledge required that most patients lack. Objectives The objectives

Abstract Background There is a recognized need to improve how scholarly data are managed and accessed. The scientific community has proposed the findable, accessible, interoperable, and reusable (FAIR) data principles to address this issue. Objective The objective of this case study was to develop a system for improving the FAIRness of Healthcare Cost and Utilization Project's State Emergency Department

Abstract Background The Asbest chrysotile cohort was set up in Asbest town, Sverdlovsk oblast, Russian Federation, among the current and former workforce of the world's largest operating chrysotile mine and its processing mills, to investigate cancer risk in relation to occupational exposure to chrysotile. Objectives The cohort of 35,837 people was followed-up for mortality using cause-of-death information

Abstract Background Although advances in prediction accuracy have been made with new machine learning methods, such as support vector machines and deep neural networks, these methods make nonlinear machine learning models and thus lack the ability to explain the basis of their predictions. Improving their explanatory capabilities would increase the reliability of their predictions. Objective Our objective

It was with great interest that I read the recent article by Al-Rayes et al. Within the authors' institution, not all inpatient physicians have adopted a recently implemented electronic health record (EHR) system. This pilot cross-sectional quantitative study investigated the factors limiting adoption of EHR systems among physicians at King Fahd Military Medical Complex in Saudi Arabia. Using the theoretical

Abstract Background Managing research data in biomedical informatics research requires solid data governance rules to guarantee sustainable operation, as it generally involves several professions and multiple sites. As every discipline involved in biomedical research applies its own set of tools and methods, research data as well as applied methods tend to branch out into numerous intermediate and

Abstract Objectives The current study sought to evaluate whether nursing narratives can be used to predict postoperative length of hospital stay (LOS) following curative surgery for ovarian cancer. Methods A total of 33 patients, aged over 65 years, underwent curative surgery for newly diagnosed ovarian cancer between 2008 and 2012. Based on the median postoperative LOS, patients were divided into

Abstract Objectives This article aims to determine possible improvements made by feature extraction methods to the machine learning prediction methods for predicting 30-day hospital readmissions. Methods The study evaluates five feature extraction methods including principal component analysis (PCA), kernel principal component analysis (KPCA), isomap, Laplacian eigenmaps, and locality preserving projections

Abstract Background The acute graft-versus-host disease (aGvHD) is the most important cause of mortality in patients receiving allogeneic hematopoietic stem cell transplantation. Given that it occurs at the stage of severe tissue damage, its diagnosis is late. With the advancement of machine learning (ML), promising real-time models to predict aGvHD have emerged. Objective This article aims to synthesize

Abstract Background Development of ontologies in traditional medicine can be a foundation for other applications of informatics in this field. Despite the importance of the development of ontologies in traditional medicine, there are few review studies in this area. This study aims to review different methods for ontology development and evaluation in traditional medicine. Methods This review study

Abstract Background Health dialog systems have seen increased adoption by patients, hospitals, and universities due to the confluence of advancements in machine learning and the ubiquity of high-performance hardware that supports real-time speech recognition, high-fidelity text-to-speech, and semantic understanding of natural language. Objectives This review seeks to enumerate opportunities to apply

We are enormously saddened by the death of our friend and colleague, Donald A.B. Lindberg, MD, on August 17, 2019. Throughout his long career, Don was a visionary leader who, earlier than most, saw the potential of technology to improve health care. He was a founder of our field, and he was a steadfast supporter of Methods. Beginning in 1970, when the journal was still a relatively new journal edited

BACKGROUND Secondary use of routine medical data relies on a shared understanding of given information. This understanding is achieved through metadata and their interconnections, which can be stored in metadata repositories (MDRs). The necessity of an MDR is well understood, but the local work on metadata is a time-consuming and challenging process for domain experts. OBJECTIVE To support the identification

BACKGROUND The use of receiver operating characteristic curves, or "ROC analysis," has become quite common in biomedical research to support decisions. However, sensitivity, specificity, and misclassification rates are still often estimated using the training sample, overlooking the risk of overrating the test performance. METHODS A simulation study was performed to highlight the inferential implications

BACKGROUND Understanding a physician's behavior toward learning order sets is important as it is a key information to design order sets with optimized contents. OBJECTIVE The objective of this article is to test a hypothesis: for a physician using a new order set repeatedly, the utilization rate of order set contents has a pattern of either increase or decrease. METHODS To test the hypothesis, we retrieved

BACKGROUND In the neonatal intensive care unit (NICU), predefined acuity-based team care models are restricted to core roles and neglect interactions with providers outside of the team, such as interactions that transpire via electronic health record (EHR) systems. These unaccounted interactions may be related to the efficiency of resource allocation, information flow, communication, and thus impact

BACKGROUND Evaluating potential data losses from mapping proprietary medical data formats to standards is essential for decision making. The article implements a method to evaluate the preliminary content overlap of proprietary medical formats, including national terminologies and Fast Healthcare Interoperability Resources (FHIR)-international medical standard. METHODS Three types of mappings were

BACKGROUND Despite recent advances in the field of medical sciences, children's developmental motor disorders (DMDs) are considered as one of the challenges in this area. Establishment of electronic systems for recording and monitoring children's DMDs can play an effective role in identifying patients and reducing the costs and consequences of the disease management. The aim of this study was to identify

BACKGROUND Students with complex health care services process face constant challenges with regard to health education. The mobile devices are an important tool that can install various applications for using information such as clinical guidelines, drug resources, clinical calculations, and the latest scientific evidence without any time and place limitations. And this happens only when students accept

BACKGROUND Modeling human cardiac diseases with induced pluripotent stem cells not only enables to study disease pathophysiology and develop therapies but also, as we have previously showed, it can offer a tool for disease diagnostics. We previously observed that a few genetic cardiac diseases can be separated from each other and healthy controls by applying machine learning to Ca2+ transient signals

BACKGROUND The interest in information extraction from clinical reports for secondary data use is increasing. But experience with the productive use of information extraction processes over time is scarce. A clinical data warehouse has been in use at our university hospital for several years, which also provides an information extraction of echocardiography reports developed for general use. OBJECTIVES