Health Informatics Journal

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: Rates of follow-up visits, referrals and laboratory tests were higher in video visits compared to visit with medical device (OR of 1...

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 3.0), Germany's legally mandated oncological data standard. RESULTS: The analysis revealed that 42...

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 YouTube videos and selected the top 100 most viewed videos. The number of views, video length, upload date, content, and uploaders of each video were recorded...

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 result in clinical practice, limiting the adaption of the ML models into a daily clinical routine. In this study, we developed Bayesian Network (BN) models to enable explainable assessment within 24 h of admission for risk of HA-UTI...

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, we conducted sentiment analysis and topic modeling to investigate vaccine perception using 338,465 COVID-19 vaccine-related comments collected from January 2020 to May 2021 on Reddit...

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 custom CDS alerts from an academic medical center that were recorded and monitored in a longitudinal fashion and the data warehouses where this information was stored...

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 and analysed using content analysis with an inductive approach. The analysis indicated mainly unconscious changes in the roles of professional groups...

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 uncertainty in resource availability. A CHP is a standardized tool that details multiple steps of a healthcare-related service and the required resources for each step...

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 - Google, Bing, and Yahoo - to identify websites related to endometriosis-associated dyspareunia. Two independent reviewers screened the search results against inclusion and exclusion criteria...

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 as their characteristics. Five machine learning algorithms were used, namely Random forest, Extra tree, Xgboost, Naive bayes and K-nearest neighbor...

Although mobile mental health apps have the unique potential to increase access to care, evidence reveals engagement is low unless coupled with coaching. However, most coaching protocols are limited in their scalability. This study assesses how human support and guidance from a Digital Navigator (DN), a scalable coach, can impact mental health app engagement and effectiveness on anxiety and depressive symptoms. This study aims to detach components of coaching, specifically personalized recommendations versus general support, to inform scalability of coaching models for mental health apps...

The objective was to assess risk of hospitalization and mortality of comorbidities using divisive hierarchical risk clustering to advice clinical interventions. Subjects and Methods : Data from the EHR of a general population, 3799885 adults, followed by 5 years. Model were performed using Spark and Scikit-learn and accuracy for the models was analyzed. Results : The number of models generated depends in part on the number of chronic diseases included (ex testing a sample of six diseases, a total number of 397 models for all-cause mortality and 431 models for hospitalization)...

In modern hospitals, monitoring patients' vital signs and other biomedical signals is standard practice. With the advent of data-driven healthcare, Internet of medical things, wearable technologies, and machine learning, we expect this to accelerate and to be used in new and promising ways, including early warning systems and precision diagnostics. Hence, we see an ever-increasing need for retrieving, storing, and managing the large amount of biomedical signal data generated. The popularity of standards, such as HL7 FHIR for interoperability and data transfer, have also resulted in their use as a data storage model, which is inefficient...

Participation of main users in identifying key performance indicators (KPIs) for management dashboards contributes to their success. The aim of this study was to identify and prioritize the KPIs of hospital management dashboards from the viewpoint of hospital managers. This study was conducted on managers of public hospitals at a national level in Iran in 2020. Data were collected using a self-administrated questionnaire. The KPIs were classified into five categories, namely financial, operational, human resources, safety and quality of care, services provided to patients...

The paediatric orthopaedic expert system analyses and predicts the healing time of limb fractures in children using machine learning. As far we know, no published research on the paediatric orthopaedic expert system that predicts paediatric fracture healing time using machine learning has been published. The University Malaya Medical Centre (UMMC) offers paediatric orthopaedic data, comprises children under the age of 12 radiographs limb fractures with ages recorded from the date and time of initial trauma...

Despite large-scale adoption during COVID-19, patient perceptions on the benefits and potential risks with receiving care through digital technologies have remained largely unexplored. A quantitative content analysis of responses to a questionnaire ( N = 6766) conducted at a multi-site acute trust in London (UK), was adopted to identify commonly reported benefits and concerns. Patients reported a range of promising benefits beyond immediate usage during COVID-19, including ease of access; support for disease and care management; improved timeliness of access and treatment; and better prioritisation of healthcare resources...

We constructed a preventive social behaviours (PSB) Index using survey questions that were aligned with WHO recommendations, and used linear regression to assess the impact of reported COVID-19 deaths (RCD), people's confidence of government handling of the pandemic (CGH) and government stringency (GS) in the United Kingdom (UK) over time on the PSB index. We used repeated, nationally representative, cross-sectional surveys in the UK over the course of 41 weeks from 1st April 2020 to January 28th, 2021, including a total of 38,092 participants...

This study aimed to provide an understanding of nursing students' self-reported eHealth literacy in Sweden and Poland. This cross-sectional multicentre study collected data via a questionnaire in three universities in Sweden and Poland. Descriptive statistics, the Spearman's Rank Correlation Coefficient, Mann-Whitney U, and Kruskal-Wallis tests were used to analyse different data types. Age (in the Polish sample), semester, perceived computer or laptop skills, and frequency of health-related Internet searches were associated with eHealth literacy...

Vitamin D is among the vitamins necessary for both adults' and children's health. It plays a significant role in calcium absorption, the immune system, cell proliferation and differentiation, bone protection, skeletal health, rickets, muscle health, heart health, disease pathogenesis and severity, glucose metabolism, glucose intolerance, varying insulin secretion, and diabetes. Because the 25-hydroxyvitamin D (25OHD) test, which is used to measure vitamin D is expensive and may not be covered in healthcare benefits in many countries, this study aims to predict vitamin D deficiency in diabetic patients...

Determining the factors that contribute to making a reliable prediction of the metabolic syndrome will provide a deeper understanding of the medical indices involved in the prediction and assist in early diagnosis and treatment of patients. The study examined the optimal number of National cholesterol education program adult treatment panel (NCEP ATP) III indices needed to make a reliable prediction of the syndrome, whether each of the five NCEP ATP III indices for predicting the syndrome is equally important and whether a reliable prediction can be made using calculated blood pressure indices - estimated mean arterial pressure and pulse pressure - instead of NCEP ATP III blood pressure indices...