Public health informatics

Emotion recognition from electroencephalogram (EEG) signals is a critical domain in biomedical research with applications ranging from mental disorder regulation to human-computer interaction. In this paper, we address two fundamental aspects of EEG emotion recognition: continuous regression of emotional states and discrete classification of emotions. While classification methods have garnered significant attention, regression methods remain relatively under-explored. To bridge this gap, we introduce MASA-TCN, a novel unified model that leverages the spatial learning capabilities of Temporal Convolutional Networks (TCNs) for EEG emotion regression and classification tasks...

BACKGROUND: Medical documentation plays a crucial role in clinical practice, facilitating accurate patient management and communication among health care professionals. However, inaccuracies in medical notes can lead to miscommunication and diagnostic errors. Additionally, the demands of documentation contribute to physician burnout. Although intermediaries like medical scribes and speech recognition software have been used to ease this burden, they have limitations in terms of accuracy and addressing provider-specific metrics...

BACKGROUND: In Japan, long-distance domestic travel was banned while the ancestral SARS-CoV-2 strain was dominant under the first declared state of emergency from March 2020 until the end of May 2020. Subsequently, the "Go To Travel" campaign travel subsidy policy was activated, allowing long-distance domestic travel, until the second state of emergency as of January 7, 2021. The effects of this long-distance domestic travel ban on SARS-CoV-2 infectivity have not been adequately evaluated...

Machine learning (ML) approaches could expand the usefulness and application of implementation science methods in clinical medicine and public health settings. The aim of this viewpoint is to introduce a roadmap for applying ML techniques to address implementation science questions, such as predicting what will work best, for whom, under what circumstances, and with what predicted level of support, and what and when adaptation or deimplementation are needed. We describe how ML approaches could be used and discuss challenges that implementation scientists and methodologists will need to consider when using ML throughout the stages of implementation...

OBJECTIVE: We applied a user experience (UX) design approach to clinical decision support (CDS) tool development for the specific use case of pediatric asthma. Our objective was to understand physicians' workflows, decision-making processes, barriers (ie, pain points), and facilitators to increase usability of the tool. MATERIALS AND METHODS: We used a mixed-methods approach with semi-structured interviews and surveys. The coded interviews were synthesized into physician-user journey maps (ie, visualization of a process to accomplish goals) and personas (ie, user types)...

Cardiovascular risk factors (CVRFs) later in life potentiate risk for late cardiovascular disease (CVD) from cardiotoxic treatment among survivors. This study evaluated the association of baseline CVRFs and CVD in the early survivorship period. Methods This analysis included patients ages 0-29 at initial diagnosis and reported in the institutional cancer registry between 2010 and 2017 (n = 1228). Patients who died within five years (n = 168), those not seen in the oncology clinic (n = 312), and those with CVD within one year of diagnosis (n = 17) were excluded...

The crisis of antibiotic resistance has become a significant global threat to human health. Understanding properties of antibiotic resistance genes (ARGs) is the first step to mitigate this issue. Although many methods have been proposed for predicting properties of ARGs, most of these methods focus only on predicting antibiotic classes, while ignoring other properties of ARGs, such as resistance mechanisms and transferability. However, acquiring all of these properties of ARGs can help researchers gain a more comprehensive understanding of the essence of antibiotic resistance, which will facilitate the development of antibiotics...

BACKGROUND: The digitalization in the healthcare sector promises a secondary use of patient data in the sense of a learning healthcare system. For this, the Medical Informatics Initiative's (MII) Consent Working Group has created an ethical and legal basis with standardized consent documents. This paper describes the systematically monitored introduction of these documents at the MII sites. METHODS: The monitoring of the introduction included regular online surveys, an in-depth analysis of the introduction processes at selected sites, and an assessment of the documents in use...

INTRODUCTION: Autosomal dominant polycystic kidney disease (ADPKD) is the most common inherited kidney disease in adults. As a social media platform, YouTube has tremendous potential to both support and hinder public health efforts. The aim of this study was to assess the reliability and quality of the most viewed English-language YouTube videos on ADPKD. METHODS: A YouTube search was conducted on 3 August 2023, using the keyword ADPKD disease and the top 200 videos were analyzed for relevance...

OBJECTIVE: Mobile health (mHealth) services suffer from high attrition rates yet represent a viable strategy for adults to improve their health. There is a need to develop evidence-based mHealth services and to constantly evaluate their feasibility. This study explored the acceptability, usability, engagement and optimisation of a co-developed mHealth service, aiming to promote healthy lifestyle behaviours. METHODS: The service LongLife Active® (LLA) is a mobile app with coaching...

OBJECTIVE: To investigate how missing data in the patient problem list may impact racial disparities in the predictive performance of a machine learning (ML) model for emergency department (ED) triage. MATERIALS AND METHODS: Racial disparities may exist in the missingness of EHR data (eg, systematic differences in access, testing, and/or treatment) that can impact model predictions across racialized patient groups. We use an ML model that predicts patients' risk for adverse events to produce triage-level recommendations, patterned after a clinical decision support tool deployed at multiple EDs...

OBJECTIVE: As the digitalization of health accelerates, the fusion of pharmacy and informatics becomes crucial. Pharmacy education must adapt to equip professionals for this evolving landscape. This study aims to compare pharmacy curricula in Brazil and the USA, focusing on health informatics, to uncover challenges and opportunities in training pharmacists for the digital era. METHODS: A cross-sectional, descriptive analysis was conducted on pharmacy curricula from leading Brazilian and American universities in early 2024...

BACKGROUND AND AIM: Conditions such as hypertension, cardiovascular diseases, and hypercholesterolemia, are a major public health challenge. This study investigates the influence of oral health indicators, including gum bleeding, active dental caries, tooth mobility, and tooth loss, on their prevalence in Hungary, considering socioeconomic, demographic, and lifestyle factors. MATERIALS AND METHODS: Data from the 2019 Hungarian European Health Interview Survey with 5,603 participants informed this analysis...

Congenital heart disease (CHD) is the most frequent birth defect and a leading cause of infant mortality, emphasizing the crucial need for its early diagnosis. Ultrasound is the primary imaging modality for prenatal CHD screening. As a complement to the four-chamber view, the three-vessel view (3VV) plays a vital role in detecting anomalies in the great vessels. However, the interpretation of fetal cardiac ultrasound images is subjective and relies heavily on operator experience, leading to variability in CHD detection rates, particularly in resource-constrained regions...

INTRODUCTION: Low birth weight (LBW) is a global issue prevalent in low-income countries. Economic assessments of interventions to reduce this burden are crucial to guide health policies. However, there is a relative scarcity of research that illustrates the magnitude of LBW by country and region to support the design of public policies. OBJECTIVE: This study aimed to analyze the temporal trend of fetal growth in newborns in Brazil between 2010 and 2020. METHODS: A time series study was conducted using data from the Live Births Information System (SINASC), which is managed by the Department of Information and Informatics of the Unified Health System (DATASUS) of the Brazilian Ministry of Health...

INTRODUCTION: Hospitals play a potentially crucial role in public health, and social media can be powerful tools to reach their target audiences but are hospitals exploiting them to their full potential? METHODS: We retrieved the institutional webpages and the social media profiles (Facebook, Instagram, X (Twitter), YouTube, LinkedIn, WhatsApp and Telegram) of all Italian public hospitals located in regional capitals ( N  = 194). From 1 March to 30 April 2022, we analysed these profiles, noting the number of followers and of posts published, the date of the last post, and the availability of a social media policy...

Recent improvements in the accessibility of mapping tools and an increased recognition of the importance of leveraging data to inform public health operations has led to enthusiasm among public health departments to rapidly evolve their ability to analyze and apply data to programs. As the COVID-19 pandemic made evident, many health department data systems have been neglected for decades and data literacy among staff low. Significant federal dollars have been allocated to local health departments to modernize health systems...

[This corrects the article DOI: 10.1093/jamiaopen/ooae003.].

OBJECTIVES: The aim of this study was to investigate the prevalence of missed nursing care and its associated factors among public hospitals in Bahir Dar City, Northwest Ethiopia. DESIGN: An institution-based cross-sectional study was conducted among 369 randomly selected nurses. SETTING: The study was conducted in primary and secondary-level public hospitals in Bahir Dar City. PARTICIPANTS: Nurses who had worked in hospitals in Bahir Dar City were included...

BACKGROUND: Technological advancement has led to the growth and rapid increase of tuberculosis (TB) medical data generated from different health care areas, including diagnosis. Prioritizing better adoption and acceptance of innovative diagnostic technology to reduce the spread of TB significantly benefits developing countries. Trained TB-detection rats are used in Tanzania and Ethiopia for operational research to complement other TB diagnostic tools. This technology has increased new TB case detection owing to its speed, cost-effectiveness, and sensitivity...