ReviewMethodist DeBakey cardiovascular journal
Digital Health: Opportunities and Challenges to Develop the Next-Generation Technology-Enabled Models of Cardiovascular Care.
Review in Methodist DeBakey cardiovascular journal. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed.
- Acceptability of digital health solutions and AI: qualitative interviews with perimenopausal women experiencing health inequalities.BMJ innovations · 2026Article
- Barriers and Enablers in Implementing Technology-Enabled Care for Older Adults in Rural and Remote Settings: A Scoping Review.International journal of environmental research and public health · 2026Article
- Quantitative evaluation of computational fluid dynamics application development in the cardiovascular field through literature retrieval and bibliometric analysis.Biomedical engineering online · 2026Review
- Tailoring remote patient management to optimise cardiovascular risk management in primary care: a mixed-methods implementation study informing large-scale implementation.BMC primary care · 2025Article
- Optimizing Acute Coronary Syndrome Patient Treatment: Leveraging Gated Transformer Models for Precise Risk Prediction and Management.Bioengineering (Basel, Switzerland) · 2024Article
- Amplifying Older Aboriginal and Torres Strait Islander Women's Perspectives to Promote Digital Health Equity: Co-Designed Qualitative Study.Journal of medical Internet research · 2023Article
- Article
- The evolution of digital health technologies in cardiovascular disease research.NPJ digital medicine · 2023Review
- "Digital biomarkers" in preclinical heart failure models - a further step towards improved translational research.Heart failure reviews · 2023Review
- Large-scale real-life implementation of technology-enabled care to maximize hospitals' medical surge preparedness during future infectious disease outbreaks and winter seasons: a viewpoint.Frontiers in public health · 2023Article
- The role of digital health in the cardiovascular learning healthcare system.Frontiers in cardiovascular medicine · 2022Review
- Highlights of Cardiovascular Disease Studies Presented at the 2021 American Heart Association Scientific Sessions.Current atherosclerosis reports · 2022Review
- Change Management and Digital Innovations in Hospitals of Five European Countries.Healthcare (Basel, Switzerland) · 2021Article
- Implementation of Telehealth Services at the US Department of Veterans Affairs During the COVID-19 Pandemic: Mixed Methods Study.JMIR formative research · 2021Article
- The Way Ahead: Life After COVID-19.Methodist DeBakey cardiovascular journal · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The wide gap between the development of new healthcare technologies and their integration into clinical practice argues for a deeper understanding of how effective quality improvement can be designed to meet the needs of patients and their clinical teams. The COVID-19 pandemic has forced us to address this gap and create long-term strategies to bridge it. On the one hand, it has enabled the rapid implementation of telehealth. On the other hand, it has raised important questions about our preparedness to adopt and employ new digital tools as part of a new process of care. While healthcare organizations are seeking to improve the quality of care by integrating innovations in digital health, they must also address key issues such as patient experience, develop clinical decision support systems that analyze digital health data trends, and create efficient clinical workflows. Given the breadth of such requirements, embracing new technologies as a core competency of a modern healthcare system introduces a host of questions, such as "How best do patients participate in digital health programs that promote behavioral changes and mitigate risk?" and "What type of data analytics are required that enable a deeper understanding of disease phenotypes and corresponding treatment decisions?" This review presents the challenges in implementing digital health technology and discusses how patient-centered digital health programs are designed within real-world models of remote monitoring. It also provides a framework for developing new devices and wearables for the next generation of data-driven, technology-enabled cardiovascular care.
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What OpenQuestion 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 OpenQuestion graph.