Evidence map›Paper›PMID 32607489›Full record

ArticleJAMIA open2020

Use of patient-generated health data across healthcare settings: implications for health systems.

Elizabeth Austin, Jenney R Lee, Dagmar Amtmann, Rich Bloch, Sarah O Lawrence, Debbe McCall, Sean Munson, Danielle C Lavallee

Abstract read
In one paragraph

Article in JAMIA open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Observational
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Unleashing the Potential for Patient-Generated Health Data (PGHD).Journal of general internal medicine · 2024
    Article
  16. Article
  17. Article
  18. The Association of Learning Health System Practicing Hospitals and other Health Information Interested Hospitals with Patient-Generated Health Data Uptake.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023
    Article
  19. Article
  20. 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

8 authors.

Elizabeth AustinDepartment of Surgery, University of Washington, Seattle, Washington, USA.
Jenney R LeeDepartment of Surgery, University of Washington, Seattle, Washington, USA.ORCID 0000-0003-4667-6148
Dagmar AmtmannDepartment of Rehabilitation Medicine, University of Washington, Seattle, Washington, USA.
Rich BlochDigital Healthcare I/O, Snohomish, Washington, USA.
Sarah O LawrenceDepartment of Surgery, University of Washington, Seattle, Washington, USA.
Debbe McCallRowan Tree Perspectives, LLC, Murietta, California, USA.
Sean MunsonDepartment of Human Centered Design & Engineering, University of Washington, Seattle, Washington, USA.
Danielle C LavalleeDepartment of Surgery, University of Washington, Seattle, Washington, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe growing prevalence of chronic conditions requiring changes in lifestyle and at-home self-management has increased interest in and need for supplementing clinic visits with data generated by patients outside the clinic. Patient-generated health data (PGHD) support the ability to diagnose and manage chronic conditions, to improve health outcomes, and have the potential to facilitate more "connected health" between patients and their care teams; however, health systems have been slow to adopt PGHD use in clinical care. MATERIALS AND

methodsWe surveyed current and potential users of PGHD to catalog how PGHD is integrated into clinical care at an academic health center. The survey included questions about data type, method of collection, and clinical uses of PGHD. Current users were asked to provide detailed case studies of PGHD use in research and care delivery.

resultsThirty-one respondents completed the survey. Seventeen individuals contributed detailed case studies of PGHD use across diverse areas of care, including behavioral health, metabolic and gastrointestinal conditions, musculoskeletal/progressive functional conditions, cognitive symptoms, and pain management. Sensor devices and mobile technologies were the most commonly reported platforms for collection. Clinicians and researchers involved in PGHD use cited the potential for PGHD to enhance care delivery and outcomes, but also indicated substantial barriers to more widespread PGHD adoption across healthcare systems.

conclusionThe results of our survey illustrate how PGHD is used in targeted areas of one healthcare system and provide meaningful insights that can guide health systems in supporting the widespread use of PGHD in care delivery.

Indexed as

data integrationdigital healthelectronic health datapatient health data

Identifiers

PMID32607489
PMCPMC7309248

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.