Evidence map›Paper›PMID 38252246›Full record

ArticleJournal of general internal medicine2024

Unleashing the Potential for Patient-Generated Health Data (PGHD).

Kim M Nazi, Terry Newton, Christina M Armstrong

Open access · hybridAbstract readEditorial
In one paragraph

Article in Journal of general internal medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
9.2field-weighted citation impact, top 2% of its field
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

11 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Exploring approaches to computational representation and classification of user-generated meal logs.Journal of the American Medical Informatics Association : JAMIA · 2026
    Article
  5. Article
  6. Factors impacting electronic patient-generated data use in safety-net systems: a qualitative study.Journal of the American Medical Informatics Association : JAMIA · 2025
    Article
  7. Article
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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

3 authors at 2 institutions in 2 countries.

Kim M NaziTrilogy Federal, LLC, Arlington, VA, USA. Kim.Nazi@trilogyfederal.com.ORCID 0000-0002-0966-5602
Terry NewtonOffice of Connected Care, US Department of Veterans Affairs, Washington, DC, USA.
Christina M ArmstrongOffice of Connected Care, US Department of Veterans Affairs, Washington, DC, USA.
United States Department of Veterans Affairs · USClinical Trial and Consulting · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patient-generated health data (PGHD) is data created, captured, or recorded by patients in between healthcare appointments, and is an important supplement to data generated during periodic clinical encounters. PGHD has potential to improve diagnosis and management of chronic conditions, improve health outcomes, and facilitate more "connected health" between patients and their care teams. Electronic PGHD is rapidly accelerating due to the proliferation of consumer health technologies, remote patient monitoring systems, and personal health platforms. Despite this tremendous growth in PGHD and anticipated benefits, broadscale use of PGHD has been challenging to implement with significant gaps in current knowledge about how PGHD can best be employed in the service of high-quality, patient-centered care. While the role of PGHD in patient self-management continues to grow organically, we need a deeper understanding of how data collection and sharing translate into actionable information that supports shared decision-making and informs clinical care in real-world settings. This, in turn, will foster both clinical adoption and patient engagement with PGHD. We propose an agenda for PGHD-related research in the Veterans Health Administration that emphasizes this clinical value to enhance our understanding of its potential and limitations in supporting shared decision-making and informing clinical care.

Indexed as

Patient-Centered CarePatient ParticipationChronic DiseaseData CollectionHumans

Identifiers

PMID38252246
PMCPMC10937868
OpenAlexW4391109384

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.