Evidence map›Paper›PMID 40670723›Full record

ReviewNature reviews. Cardiology2026

Access to digital health technologies: personalized framework and global perspectives.

Sanjiv M Narayan, Mina K Chung, Demilade Adedinsewo, Luisa C C Brant, Leslie L Davis, David Duncker, Jennifer L Hall, Janet K Han, Carolyn S P Lam, Eldrin Lewis and 10 more

Abstract readReview
In one paragraph

Review in Nature reviews. Cardiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Digital health technology burden and frustration among patients with multimorbidity.Journal of the American Medical Informatics Association : JAMIA · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors.

Sanjiv M NarayanDepartment of Medicine, Cardiovascular Institute (CVI), Institute for Computational and Mathematical Engineering (ICME), Stanford University, Palo Alto, CA, USA. sanjiv1@stanford.edu.ORCID 0000-0001-7552-5053
Mina K ChungDepartment of Cardiovascular Medicine, Heart, Vascular & Thoracic Institute, Cleveland Clinic, Cleveland, Ohio, USA.
Demilade AdedinsewoDepartment of Cardiovascular Medicine, Mayo Clinic, Jacksonville, FL, USA.
Luisa C C BrantFaculty of Medicine, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.ORCID 0000-0002-7317-1367
Leslie L DavisUniversity of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
David DunckerHannover Heart Rhythm Center, Department of Cardiology and Angiology, Hannover Medical School, Hannover, Germany.
Jennifer L HallAmerican Heart Association, Data Science and Analytics, Dallas, TX, USA.
Janet K HanDavid Geffen School of Medicine at the University of Los Angeles California, Los Angeles, CA, USA.
Carolyn S P LamNational Heart Centre Singapore, Singapore, Singapore.ORCID 0000-0003-1903-0018
Eldrin LewisDepartment of Medicine, Cardiovascular Institute (CVI), Institute for Computational and Mathematical Engineering (ICME), Stanford University, Palo Alto, CA, USA.
Joseph LoscalzoDivision of Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Manlio F MárquezDepartment of Electrocardiology, National Institute of Cardiology Ignacio Chávez, Mexico City, Mexico.ORCID 0000-0001-7294-7330
Vasiliki RahimzadehCenter for Medical Ethics & Health Policy, Baylor College of Medicine, Houston, TX, USA.
Fatima RodriguezDepartment of Medicine, Cardiovascular Institute (CVI), Institute for Computational and Mathematical Engineering (ICME), Stanford University, Palo Alto, CA, USA.
Prashanthan SandersCentre for Heart Rhythm Disorders, University of Adelaide and Royal Adelaide Hospital, Adelaide, South Australia, Australia.ORCID 0000-0003-3803-8429
Emma SvennbergKarolinska Institutet, Department of Medicine (MedH), Karolinska University Hospital, Stockholm, Sweden.
Kenneth SteinBoston Scientific, Marlborough, MA, USA.
Mintu TurakhiaDepartment of Medicine, Cardiovascular Institute (CVI), Institute for Computational and Mathematical Engineering (ICME), Stanford University, Palo Alto, CA, USA.
Clyde YancyNorthwestern University Medical Center, Chicago, IL, USA.
Antonis A ArmoundasCardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA. armoundas.antonis@mgh.harvard.edu.ORCID 0000-0001-5006-1547

Funding

Machine Learning in Atrial FibrillationR01HL149134 · NHLBI · STANFORD UNIVERSITY · PI NARAYAN, SANJIV M · 2020 to 2024
$3.8M
Machine Learning for Ventricular ArrhythmiasR01HL162260 · NHLBI · STANFORD UNIVERSITY · PI Sanjiv M Narayan · 2023 to 2026
$2.5M
Adherence Determinants in the Health Electronic Record Evaluation of Statins (ADHERES)R01HL168188 · NHLBI · STANFORD UNIVERSITY · PI Fatima Rodriguez · 2024 to 2026
$2.1M
Mayo Clinic Building Interdisciplinary Research Careers in Women’s HealthK12AR084222 · NIAMS · MAYO CLINIC ROCHESTER · PI KANTARCI, KEJAL · 2023 to 2024
$733k
NHLBI NIH HHS R01 HL149134NHLBI NIH HHS R01 HL162260NHLBI NIH HHS R01 HL168188NIAMS NIH HHS K12 AR084222
6 · The paper itself

Abstract

The emergence and rapid adoption of digital health technologies (DHT) present unprecedented opportunities to democratize and reduce disparities in health care by monitoring health and disease at the point of care in all patients. However, limited access to DHT is becoming a major obstacle to realizing these goals. Access to DHT is influenced not only by well-recognized social determinants of health, but also by digital determinants of health, such as digital literacy and the need for broad access to digital infrastructure, as well as commercial and economic factors. Addressing these challenges and designing unbiased systems of care are essential to enable broad access to DHT and to benefit diverse and under-represented communities. Doing so will fill gaps in the clinical evidence base and avoid perpetuating historical biases. In this Review, we propose a personalized framework to improve access to DHT, addressing determinants of access at the individual, interpersonal, community, society, government and industry levels. We frame these issues globally, highlighting how the challenges to DHT access and potential solutions might differ between continents while also emphasizing common themes. We provide perspectives from partners across the spectrum of health care, including clinicians, clinical trialists, and experts from digital health and industry.

Indexed as

Biomedical TechnologyDigital TechnologyGlobal HealthHealth Services AccessibilityTelemedicineDigital HealthHealthcare DisparitiesHumansSocial Determinants of Health

Identifiers

PMID40670723
PMCPMC13064571

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.