Evidence map›Paper›PMID 29354642›Full record

ArticlemHealth2017

Use of My Health

Steven S Coughlin, Laura D Carbone, Vahé Heboyan, Lovoria B Williams, Christos Hatzigeorgiou, Pavani Rangachari, Gianluca De Leo

Open access · hybridAbstract read
In one paragraph

Article in mHealth, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
2.1field-weighted citation impact, top 10% 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. 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

7 authors at 3 institutions in 2 countries.

Steven S CoughlinDepartment of Clinical and Digital Health Sciences, College of Allied Health Sciences, Augusta University, Augusta, GA, USA.
Laura D CarboneCharlie Norwood Veterans Affairs Medical Center, Augusta, GA, USA.
Vahé HeboyanDepartment of Clinical and Digital Health Sciences, College of Allied Health Sciences, Augusta University, Augusta, GA, USA.
Lovoria B WilliamsDepartment of Biobehavioral Nursing, College of Nursing, Augusta University, Augusta, GA, USA.
Christos HatzigeorgiouDivision of General Internal Medicine, Medical College of Georgia, Augusta University, Augusta, GA, USA.
Pavani RangachariOffice of the Associate Dean for Practice and Community Health, College of Allied Health Sciences, Augusta University, Augusta, GA, USA.
Gianluca De LeoDepartment of Clinical and Digital Health Sciences, College of Allied Health Sciences, Augusta University, Augusta, GA, USA.
Augusta University · USAugusta University Health · USCharlie Norwood VA Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAn increasing number of studies have examined the use of information technology to improve diabetes care and patient self-management. The goal of the current study was to determine the number of veterans seen for diabetes at a large medical center in the southeastern region of the U.S. and to examine whether they had registered for VA's My Health

methodsExisting patient records were reviewed including My Health

resultsA total of 49,341 veterans receive care at the Charlie Norwood VAMC. Of those patients, 10,950 have been seen for diabetes. Of the 49,341 patients, 21,372 patients (43.3%) are using My Health

conclusionsA low percentage of Veterans with diabetes are active users of My Health

Indexed as

Diabeteselectronic health recordglycemic controlhealth information technologypatient web portalsveterans

Identifiers

PMID29354642
PMCPMC5762985
OpenAlexW2767746730

What OpenQuestion holds

Textmetadata
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.