ArticleSensors (Basel, Switzerland)2023
Using the Non-Adoption, Abandonment, Scale-Up, Spread, and Sustainability (NASSS) Framework to Identify Barriers and Facilitators for the Implementation of Digital Twins in Cardiovascular Medicine.
Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 42 citations in OpenAlex.
- Exploring Professionals' Perceptions of the Potential of Digital Twins in Homecare-A Focus Group Study in Sweden.Healthcare (Basel, Switzerland) · 2026Article
- Adoption of an Electronic Decision Support Tool for Capacity Building of Community Health Workers: Mixed Methods Study.JMIR formative research · 2026Article
- Realising the digital twin: a thematic review and analysis of the ethical, legal, and social issues for digital twins in healthcare.AI & society · 2026Article
- A perspective on improving the teaching quality of aerospace cardiovascular medicine courses.Frontiers in medicine · 2026Article
- AI digital-twin ecosystem translating gut-microbiome-neuroimmune signals into precision sleep-mood interventions.Frontiers in psychiatry · 2026Review
- Towards Differentiated Management: The Role of Organizational Type and Work Position in Shaping Employee Engagement Among Slovak Healthcare Professionals.Healthcare (Basel, Switzerland) · 2025Article
- Digital Twins for Personalized Medicine Require Epidemiological Data and Mathematical Modeling: Viewpoint.Journal of medical Internet research · 2025Article
- Evaluating CFIR 2.0 in identifying digital twin implementation challenges in healthcare: bridging the dichotomy between engineering and healthcare communities.Frontiers in digital health · 2025Article
- Voices from the field: healthcare professionals' insights on sustaining telemedicine for diabetes management in Hong Kong primary care.Frontiers in digital health · 2025Article
- Allied Health Professionals' Perceptions of Artificial Intelligence in the Clinical Setting: Cross-Sectional Survey.JMIR formative research · 2024Article
- From theoretical models to practical deployment: A perspective and case study of opportunities and challenges in AI-driven cardiac auscultation research for low-income settings.PLOS digital health · 2024Article
- Cardiovascular care with digital twin technology in the era of generative artificial intelligence.European heart journal · 2024Review
- Immune digital twins for complex human pathologies: applications, limitations, and challenges.NPJ systems biology and applications · 2024Review
- Recent Advances in Artificial Intelligence to Improve Immunotherapy and the Use of Digital Twins to Identify Prognosis of Patients with Solid Tumors.International journal of molecular sciences · 2024Review
- Digital twins: a new paradigm in oncology in the era of big data.ESMO real world data and digital oncology · 2024Review
- Human Factors and Organizational Issues in Health Informatics: Review of Recent Developments and Advances.Yearbook of medical informatics · 2024Review
- Insights into implementation planning for point-of-care testing to guide treatment of chronic obstructive pulmonary disease exacerbation: a mixed methods feasibility study.Frontiers in health services · 2023Article
- Overcoming barriers and enabling artificial intelligence adoption in allied health clinical practice: A qualitative study.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
A digital twin is a computer-based "virtual" representation of a complex system, updated using data from the "real" twin. Digital twins are established in product manufacturing, aviation, and infrastructure and are attracting significant attention in medicine. In medicine, digital twins hold great promise to improve prevention of cardiovascular diseases and enable personalised health care through a range of Internet of Things (IoT) devices which collect patient data in real-time. However, the promise of such new technology is often met with many technical, scientific, social, and ethical challenges that need to be overcome-if these challenges are not met, the technology is therefore less likely on balance to be adopted by stakeholders. The purpose of this work is to identify the facilitators and barriers to the implementation of digital twins in cardiovascular medicine. Using, the Non-adoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework, we conducted a document analysis of policy reports, industry websites, online magazines, and academic publications on digital twins in cardiovascular medicine, identifying potential facilitators and barriers to adoption. Our results show key facilitating factors for implementation: preventing cardiovascular disease, in silico simulation and experimentation, and personalised care. Key barriers to implementation included: establishing real-time data exchange, perceived specialist skills required, high demand for patient data, and ethical risks related to privacy and surveillance. Furthermore, the lack of empirical research on the attributes of digital twins by different research groups, the characteristics and behaviour of adopters, and the nature and extent of social, regulatory, economic, and political contexts in the planning and development process of these technologies is perceived as a major hindering factor to future implementation.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.