Evidence map›Paper›PMID 31852707›Full record

ArticleBMJ open2019

Patient-generated health data and electronic health record integration: protocol for a scoping review.

Victoria L Tiase, William Hull, Mary M McFarland, Katherine A Sward, Guilherme Del Fiol, Catherine Staes, Charlene Weir, Mollie R Cummins

Abstract read
In one paragraph

Article in BMJ open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Observational
  2. Review
  3. Article
  4. Article
  5. Article
  6. The role of artificial intelligence for the application of integrating electronic health records and patient-generated data in clinical decision support.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024
    Article
  7. Article
  8. 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.

Victoria L TiaseCollege of Nursing, University of Utah, Salt Lake City, Utah, USA victoria.tiase@utah.edu.ORCID 0000-0001-5653-2282
William HullCollege of Nursing, University of Utah, Salt Lake City, Utah, USA.
Mary M McFarlandEccles Health Sciences Library, University of Utah, Salt Lake City, Utah, USA.
Katherine A SwardCollege of Nursing, University of Utah, Salt Lake City, Utah, USA.
Guilherme Del FiolDepartment of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA.ORCID 0000-0001-9954-6799
Catherine StaesCollege of Nursing, University of Utah, Salt Lake City, Utah, USA.
Charlene WeirDepartment of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA.
Mollie R CumminsCollege of Nursing, University of Utah, Salt Lake City, Utah, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe objective of this study is to determine the extent and describe the nature of patient-generated health data (PGHD) integration into electronic health records (EHRs) using systematic scoping methods to review the available literature. PGHD have the potential to enhance decision making by providing the valuable information that may not be ordinarily captured during a routine care visit. These data which are captured from mobile devices, such as smartphones, activity trackers and other sensors, should be integrated into clinical workflows to allow for optimal use by clinicians. METHODS AND ANALYSIS: This study aims to conduct a rigorous scoping review to explore evidence related to the integration of PGHD into EHRs. Using the framework developed by Arksey and O'Malley, we will create a systematic search strategy, chart data from the relevant articles, and use a qualitative, thematic approach to analyse the data. This review will enable the identification of types of integration and describe challenges and barriers to integrating PGHD. ETHICS AND DISSEMINATION: Database searches will be initiated in June 2019. The review is expected to be completed by October 2019. As the content of the full-text articles emerges, the authors will summarise the characteristics related to the integration of PGHD. The findings of this scoping review will identify research gaps and present implications for future research.

Indexed as

Systems IntegrationElectronic Health RecordsHumansMedical InformaticsPatient Generated Health DataResearch DesignScoping Reviews as TopicHealth informaticsInformation managementInformation technology

Identifiers

PMID31852707
PMCPMC6937018

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.