Evidence map›Paper›PMID 35265886›Full record

ReviewCardiovascular digital health journal

Rapid review: Identification of digital health interventions in atherosclerotic-related cardiovascular disease populations to address racial, ethnic, and socioeconomic health disparities.

Kelly J Thomas Craig, Nicole Fusco, Kristina Lindsley, Jane L Snowdon, Van C Willis, Yull E Arriaga, Irene Dankwa-Mullan

Abstract readReview
In one paragraph

Review in Cardiovascular digital health journal. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Using AI-generated suggestions from ChatGPT to optimize clinical decision support.Journal of the American Medical Informatics Association : JAMIA · 2023
    Article
  11. Disparities in telehealth access, not willingness to use services, likely explain rural telehealth disparities.The Journal of rural health : official journal of the American Rural Health Association and the National Rural Health Care Association · 2023
    Article
  12. The role of behavioral science in addressing cardiovascular health disparities: A narrative review of efforts, challenges, and future directions.Health psychology : official journal of the Division of Health Psychology, American Psychological Association · 2022
    Review
  13. Article
  14. Review
  15. Review
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

7 authors.

Kelly J Thomas CraigCenter for AI, Research, and Evaluation, IBM Watson Health, Cambridge, Massachusetts.
Nicole FuscoLife Sciences, IBM Watson Health, Cambridge, Massachusetts.
Kristina LindsleyLife Sciences, IBM Watson Health, Cambridge, Massachusetts.
Jane L SnowdonCenter for AI, Research, and Evaluation, IBM Watson Health, Cambridge, Massachusetts.
Van C WillisCenter for AI, Research, and Evaluation, IBM Watson Health, Cambridge, Massachusetts.
Yull E ArriagaCenter for AI, Research, and Evaluation, IBM Watson Health, Cambridge, Massachusetts.
Irene Dankwa-MullanCenter for AI, Research, and Evaluation, IBM Watson Health, Cambridge, Massachusetts.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Disparities in cardiovascular disease (CVD) and associated health and healthcare delivery outcomes have been partially attributed to differential risk factors, and to prevention and treatment inequities within racial and ethnic (including language) minority groups and low socioeconomic status (SES) populations in urban and rural settings. Digital health interventions (DHIs) show promise in promoting equitable access to high-quality care, optimal utilization, and improved outcomes; however, their potential role and impact has not been fully explored. The role of DHIs to mitigate drivers of the health disparities listed above in populations disproportionately affected by atherosclerotic-related CVD was systematically reviewed using published literature (January 2008-July 2020) from multiple databases. Study design, type and description of the technology, health disparities information, type of CVD, outcomes, and notable barriers and innovations associated with the technology utilized were abstracted. Study quality was assessed using the Oxford Levels of Evidence. Included studies described digital health technologies in a disparity population with CVD and reported outcomes. DHIs significantly improved health (eg, clinical, intermediate, and patient-reported) and healthcare delivery (eg, access, quality, and utilization of care) outcomes in populations disproportionately affected by CVD in 24 of 38 included studies identified from 2104 citations. Hypertension control was the most frequently improved clinical outcome. Telemedicine, mobile health, and clinical decision support systems were the most common types of DHIs identified. DHIs improved CVD-related health and healthcare delivery outcomes in racial/ethnic groups and low SES populations in both rural and urban geographies globally.

Indexed as

Cardiovascular diseaseClinical decision supportEHRHealth information technologymHealthPatient portalsTelemedicine

Identifiers

PMID35265886
PMCPMC8890337

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.