Frontiers in digital health最新文献

Wearable technologies mark a transition in healthcare evolution, from paternalistic (Healthcare 1.0) to reactive (Healthcare 2.0), proactive (Healthcare 3.0), and data-integrated care (Healthcare 4.0). The next stage, Healthcare 5.0, envisions the seamless integration of human and pet health data, fostering a more holistic approach to disease prevention and management. In this viewpoint, we explore the disruptive potential of integrating health monitoring between humans and pets through wearable technology, highlighting the interconnected nature of human-pet health. We examine the parallel evolution of human and pet health monitoring, assessing current technologies and their potential to enhance both fields. We discuss that wearable technologies not only improve chronic disease management but also enable early detection of zoonotic and emerging diseases. Additionally, we emphasize the potential re-usability of human wearable devices for pets, outlining the associated technical challenges. This can lower costs and accelerate adoption, offering mutual benefits for both domains. We address the need for an integrated, linked platform that enables real-time data analysis. Data integration ultimately results in better diagnostic accuracy, optimized treatment plans, and enhanced quality of life for humans and pets. Re-purposing wearables for human-pet health monitoring enables real-time data collection, predictive analytics, and prevention to accelerate the implementation of Healthcare 5.0.

Introduction: Use of digital health technology can improve patient health outcomes; however, not all patients have the knowledge and skills to download a health app and access a patient portal. Providing digital onboarding support to hospitalized patients has potential to overcome some barriers to accessing needed education in the community, including both having the time and a location to receive education. To address this, our team developed the Jefferson Digital Onboarding Taskforce (JeffDOT), a group of staff and students who approach hospitalized patients and provide one-on-one teaching on how to sign up for and use a patient portal.

Methods and materials: This descriptive study examined the implementation and preliminary outcomes of JeffDOT. We collected patient demographics and assessed health literacy, digital health readiness, and empowerment using the patient portal after patients received individualized support with portal enrollment.

Results: We enrolled 343 hospitalized patients from a large academic medical center in the U.S. in their patient portal. Almost half of the sample (49%) was older than 55 years, 56% were male, 34% were Black, and 19% spoke Spanish at home. After receiving individualized support from the JeffDOT team, the majority of patients (84%) reported that they felt empowered to use the portal and almost half reported that they would be very interested in additional basic computer skills training if offered by the hospital.

Discussion: Our findings suggest that supporting hospitalized patients with enrollment into a health portal using a primarily student, volunteer-staffed model is feasible and acceptable to patients. Future research should focus on the impact of JeffDOT on patient outcomes and health behaviors.

Background: Poor access to antenatal care (ANC), skilled delivery, and postnatal checks within 48 h of delivery are linked to adverse pregnancy outcomes. In Kenya, unequal use of these services has caused significant regional disparities, with 15 out of 47 counties being high priority.

Objectives: To evaluate the effectiveness of a digital health solution to improve maternal and newborn health (MNH) uptake.

Methods: From July 2017 to March 2019, we implemented an integrated community and hospital digital health information system, in ten health facilities and four community health units in Turkana County, Northern Kenya. We used a non-randomized before-after household survey. We assessed the proportion of mothers attending at least four antenatal visits, receiving skilled delivery, and receiving postnatal checks within 48 h at baseline and 12 months post-intervention. Statistical comparisons included p-values and 95% confidence intervals, accounting for clustering at the CHU level. These findings were compared with data from the Kenya Health Information System for the study subcounty and Turkana County.

Results: Among a catchment population of 4,300 women of reproductive age (WRA), 692 and 608 women were interviewed at baseline and endline, respectively. STONE-HMIS® led to 5%, 23%, and 16% improvements in 4th antenatal care visits, skilled delivery, and postnatal checks within 48 h, respectively. For the same period, subcounty and county data showed that 57.7% and 65.8% of WRA attended at least 4 ANC visits, 39.5% and 67.8% delivered with skilled assistance, and 23.5% and 24% had postnatal checks.

Conclusions: Integrating digital health systems at provider and community levels, aligned with health system priorities, showed marked improvements MNH indicators in an underserved, remote area.

The increasing digitalization of health systems is accelerating the transition towards a new era of data-driven, evidence-based care. This has profound implications for clinical practice, performance evaluation, policy making and biomedical research. At the heart of this transformation lies a healthcare data warehouse (DW), which functions as a critical infrastructure for aggregating, standardizing, and analyzing diverse clinical and administrative data. When well-designed and implemented, DWs provide clinicians with timely access to comprehensive, longitudinal patient data, enabling more informed decision-making, enhancing care quality, and improving outcomes. For researchers, these repositories offer opportunities for population-level analytics, predictive modeling, and large-scale health service research, enabling insights into disease patterns, healthcare utilization, and system inefficiencies. Centralizing clinical and administrative data in a DW allows for more frequent, nuanced analyses, increasing the precision and responsiveness of care. However, developing an effective DW requires careful consideration of system architecture, data governance, and interoperability. These foundational components support the robust ETL/ELT frameworks that ensure data quality, consistency, and readiness for analysis across diverse and evolving data streams. Beyond supporting individual patient care, DWs act as essential drivers of scalable research, operational efficiency, and evidence-based health policy. Their successful implementation marks a pivotal step toward achieving personalized, high-quality, and cost-effective healthcare in the digital transformation age. This paper reviews the existing literature to outline the process of building and implementing a data warehouse, introducing real-world disease-specific applications. BiotherDW connects theoretical frameworks with practical healthcare applications by demonstrating how traditional data warehouse design can be adapted for national-scale digital health infrastructures.

Background: Comparing health indicators across the European Union (EU) is a challenging endeavour. A feasibility study was conducted to explore opportunities for improvement through the contextualisation of indicators for major non-communicable diseases (NCDs). We aimed to improve the usability and transparency of indicators in the domain of NCDs by describing the contextual information about the data from which they draw and the related data processes. In particular, we sought to illustrate how semantic linkage could be achieved to facilitate interoperability with other metadata models using FAIR data principles. Finally, we aimed to provide recommendations for the implementation of the proposed metadata model at the EU level.

Methods: A number of expert group meetings were held between March 2023 and October 2024 to agree on the approach and related technologies to meet the standard requirements for the meaningful comparison of indicators across countries and regions of Europe in the domain of NCDs.

Results: The Semantic Ontology-Labelled Indicator Contextualisation Integrative Taxonomy (SOLICIT) was selected as a suitable generic metadata model for contextualising indicators. In this work, we adapted the SOLICIT generic framework to the diabetes sub-domain and extended its applicability more generally across all NCDs. As a proof of concept, we present an example of how to adapt a diabetes indicator and its related contextualisation within SOLICIT.

Conclusion: The accurate contextualisation of NCD indicators can substantially improve their use and comparability across national and regional boundaries. This study delivered a set of seven recommendations for implementation in three different areas: (a) contextualisation of common data elements and indicators (use of contextual information; common schema for semantic linkage), (b) generic contextualisation framework (adoption of the framework; use of SOLICIT), and (c) implementation at EU level (pilot test of the model on federated networks; development of European portals; implementation of a user-friendly interface for SOLICIT). The proposed concepts provide a way of validating indicator values and their comparisons, as well as their provision, including all relevant details, encouraging secondary use and potential integration with additional indicator sets. Further studies are needed to test and refine the proposed model.

Introduction: Online chat services have increased mental health care access for young people (12-25 years), yet their effectiveness remains unclear. This is partly due to a lack of consensus about primary client outcomes and clinician actions facilitating positive service outcomes. This study sought to identify (a) outcomes most important for young people accessing mental health support via online chat, and (b) clinician actions most relevant to achieving these outcomes.

Method: A comprehensive list of potential outcomes and actions was developed through literature review and consultation with youth online chat service providers. A three-round Delphi study was conducted with three panels of youth, researchers, and clinicians (n = 100; 84% retention rate), primarily from Australia and Ireland. Consensus was reached if ≥75% of participants within at least two panels rated an outcome/action as very important or essential.

Results: Eleven client outcomes reached consensus: Feeling heard and validated; Reduced distress; Increased help-seeker capacity; Feeling safe; Optimism and hope; Connection with clinician and service; Feeling better; Reduced hopelessness; Reduced overwhelm; Increased coping; and Goals, answers and direction. Fifteen clinician actions reached consensus: Manage risk; Respect diversity; Validation; Welcoming environment; Active listening; Manage distress; Compassion; Checking in; Give choice; Youth friendly; Set expectations and focus; Provide resources; Holistic approach; Highlight strengths; and Problem-solving.

Conclusions: The identified client outcomes and clinician actions offer preliminary guidance for monitoring and evaluating youth online chat support. Future research should test and refine these domains within service contexts to inform robust measurement tool development for evaluating youth online chat services.

Background: Mental health disorders have been rising globally, and social media platforms provide a unique opportunity to examine public perceptions of psychotherapy. However, little is known about how different therapeutic modalities are discussed across linguistic and cultural contexts.

Objective: To analyse how psychotherapies are discussed on X (formerly Twitter) over a 15-year period, comparing thematic content and emotional tone between English and Spanish-speaking communities' tweets.

Methods: We collected 102,946 public tweets from 2008 to 2022, including 76,878 in English (74.7%) and 26,068 in Spanish (25.3%), related to four therapies: Acceptance and Commitment Therapy (ACT), Cognitive Behavioural Therapy (CBT), Psychoanalytic/Psychodynamic Therapy (PAT), and Narrative Therapy (NT). Topic modelling was performed using BERTopic. Emotion classification was conducted using DistilRoBERTa and Robertuito pre-trained transformer-based language models based on Ekman's six basic emotions.

Results: CBT was the most frequently mentioned therapy (51,250 tweets, 49.8%), followed by ACT (18,196 tweets, 17.7%). In English tweets, the main theme was professional therapy promotion (CBT: 29,383 tweets), and fear was the most prevalent emotion. In Spanish tweets, personal experiences were more common, particularly in ACT (2,528 tweets), while anger dominated tweets about PAT (2,825 tweets), linked to a lack of understanding. Joy emerged as the dominant emotion in Spanish tweets about ACT and NT. The volume of tweets increased notably from 2020 onwards, especially in English, coinciding with the COVID-19 pandemic.

Conclusions: Clear linguistic differences shape the public discourse around psychotherapy. English tweets emphasise clinical utility and are marked by fear, whereas Spanish tweets focus on individual experiences, with emotions ranging from joy to frustration. These findings underscore the importance of culturally adapted mental health communication strategies on social media.

Objective: Mobile health technologies offer scalable opportunities to promote public health, including cognitive health, via education, engagement, and personalized health approach. This study describes the features of the Terrapino mobile application and its users to date, and provide initial evaluation of the ARA score.

Methods: Between December 2022 and December 2024, 8,395 users completed the Alzheimer's Risk Assessment survey, a comprehensive questionnaire developed to collect comprehensive, evidence-based information about Alzheimer's disease risk and protective factors including sociodemographics, health and health history information, lifestyle habits, subjective memory complaints and perceived stress. Most (95%) used the original, Czech version, but English and Spanish versions are also available.

Results: Users were 18-103 years old (mean 57.1 ± 14.5 years), with 46.4% aged 60 years or older. Most (72%) were women and nearly half held a college degree. Despite relatively high education, lifestyle and health characteristics resembled general population trends, suggesting broad accessibility and reach. In a random forest machine learning models, hypertension, going for walks, playing sports and exercising, education, depression, memory complaints, meditation, vegetable intake and the use of olive oil emerged as most influential variables predicting the overall Alzheimer's Risk Assessment score, whether estimated for the entire sample or for those aged 60 + years. The models explained upwards of 80% of variance in the risk score.

Conclusions: This initial examination suggests good feasibility to engage large numbers of individuals in cognitive health promotion through a mobile platform. The early data also suggests good validity of the Alzheimer's Risk Assessment score collected within the application. The initial findings support future efforts to test the application's capacity to contribute to efforts to cognitive health promotion which can be tested through longitudinal research in the upcoming years.

This article explores the largely uncharted intersection of neurotechnology and Internet governance on the international policy agenda. Neurotechnologies encompass a broad spectrum of functions and applications, from the direct recording or alteration of brain activity to the analysis of emotions and mental states through data collected from wearable devices, applications, and AI-based tools. Innovations such as cochlear implants, sleep optimisation technologies, and immersive educational tools are already available, and significant investments are made in the next generation of devices that blur the lines between mind, machine, and action, posing unprecedented challenges. While some international organisations have begun addressing the ethical and human rights implications of neurotechnology, there remains significant fragmentation and a lack of clarity regarding its integration into Internet governance. Critical issues related to neural infrastructure, standards, access to technologies, and protections for neural data have been overlooked in the 2024 Global Digital Compact and might remain off the agenda for the upcoming 20th review of the World Summit on the Information Society. This contribution underscores the urgent need to analyse the profound implications of neurotechnology, advocating for proactive measures that align with progress made across Internet governance fora, with respect to legal safeguards, multistakeholder consultations and institutional pillars.

Background: The increasing complexity of patient care and workforce shortages in healthcare systems necessitate improved interprofessional interaction. Digital technologies offer promising solutions to facilitate such interaction across healthcare settings.

Objectives: This scoping review aimed to identify, categorize, and assess digital technologies that support interprofessional interaction among healthcare professionals, using the NASSS framework to evaluate their implementation context and impact.

Methodology: A systematic search was conducted across five databases. The eligible studies examined digital tools enabling interaction between different professional groups in healthcare. Data from 407 studies were extracted and coded using four NASSS domains (Condition, Technology, Value Proposition, and Adopter System). Thematic analysis and visualizations were employed to synthesize findings.

Results: Seven primary technology categories were identified. Most technologies were implemented at the organizational level, primarily within hospital and intersectoral care settings, with oncology being the most common clinical focus. While many tools showed positive impacts on workflow efficiency, access to specialist expertise, and team communication, challenges relating to usability, data privacy, role ambiguity, and staff workload were also reported. Value propositions and impacts on staff varied significantly across technologies.

Conclusion: Digitally supported interprofessional interaction holds promise for enhancing communication, collaboration, and efficiency in delivering healthcare. However, successful adoption depends on aligning technological design with clinical workflows, involving end-users in development, and addressing regulatory, ethical, and organizational challenges.