Evidence map›Paper›PMID 40718403›Full record

ReviewDigital health

Harnessing digital health technologies and real-world evidence to enhance clinical research and patient outcomes.

Shreyash Mahadik, Prerona Sen, Ekta J Shah

Abstract readReview
In one paragraph

Review in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
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

3 authors.

Shreyash MahadikCollege of Professional Studies, Northeastern University, Toronto, ON, Canada.ORCID https://orcid.org/0000-0003-4986-4208
Prerona SenCollege of Professional Studies, Northeastern University, Toronto, ON, Canada.ORCID https://orcid.org/0009-0005-7155-3037
Ekta J ShahCollege of Professional Studies, Northeastern University, Toronto, ON, Canada.ORCID https://orcid.org/0009-0006-3674-2016

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The intersection of digital health technologies (DHT) and real-world evidence (RWE) is redefining the landscape of clinical research and regulatory science, offering unique opportunities to improve drug development, patient monitoring, and evidence-based decision-making. The extensive use of digital technologies has facilitated continuous, real-time health data collection, while RWE helps bridge the gap between controlled clinical trials and real-world patient experiences. As healthcare systems progressively integrate these various data sources, they are reshaping regulatory approval processes and enhancing post-market surveillance of therapies. Furthermore, advancements in the integration of artificial intelligence and the application of pharmacogenomics results in more effective, efficient, and personalized healthcare delivery. Nonetheless, these developments are met with critical challenges, and the lack of standardized global regulatory frameworks creates disparities in how this data is utilized across jurisdictions. Addressing these limitations through robust validation frameworks, harmonized regulatory policies, and interdisciplinary collaboration is essential to realizing the complete potential of DHT and RWE in precision medicine applications. This review examines the opportunities, challenges, and future directions of merging DHT and RWE to enhance precision medicine, emphasizing the importance of collaboration among researchers, regulators, and healthcare providers.

Indexed as

artificial intelligenceDHTprecision medicineregulatory agencyRWE

Identifiers

PMID40718403
PMCPMC12290384

What OpenQuestion 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 OpenQuestion graph.