Evidence map›Paper›PMID 31335195›Full record

ArticleDiabetes technology & therapeutics2019

Challenges with Patient Adoption of Automated Integration of Blood Glucose Meter Data in the Electronic Health Record.

Jake Weatherly, Saniya Kishnani, Tandy Aye

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Diabetes technology & therapeutics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. 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.

Jake WeatherlyPediatric Endocrinology and Diabetes, Stanford University School of Medicine, Stanford, California.
Saniya KishnaniPediatric Endocrinology and Diabetes, Stanford University School of Medicine, Stanford, California.
Tandy AyePediatric Endocrinology and Diabetes, Stanford University School of Medicine, Stanford, California.

Funding

Stanford Center for Clinical & Translational Education and Research (Spectrum)UL1TR003142 · NCATS · STANFORD UNIVERSITY · PI O'HARA, RUTH M · 2019 to 2023
$45.0M
Stanford Center for Clinical and Translational Education and Research (SCCTER)UL1UL1RR025744 · NCRR · STANFORD UNIVERSITY · PI GREENBERG, HARRY BERNARD · 2008 to 2011
$22.4M
NCATS NIH HHS UL1 TR003142NCRR NIH HHS UL1 RR025744
6 · The paper itself

Abstract

Providers often encourage patients with type 1 diabetes (T1D) to contact them with blood glucose (BG) values between visits. However, patients and families find it cumbersome to share their BG values with clinical providers, creating a barrier to communication. Although many phone applications exist to help patients track BG values, most do not integrate with the electronic health record (EHR). Recent advances in technology can integrate the glucose meter (GM) data into the EHR. This pilot and feasibility study aimed to understand how an automated integration system of GM data into the EHR and remote monitoring by health care providers would impact patient-provider communication. Patients or parents of patients with T1D (

Indexed as

Blood Glucose Self-MonitoringElectronic Health RecordsAdolescentBlood GlucoseChildDiabetes Mellitus, Type 1Feasibility StudiesFemaleGlycated HemoglobinHumansMalePatient Acceptance of Health CarePatient SatisfactionPilot ProjectsSelf CareYoung AdultBlood GlucoseGlycated Hemoglobinhemoglobin A1c protein, humanElectronic health recordGlucose meterPediatricSelf-monitoring of blood glucoseType 1 diabetes

Identifiers

PMID31335195
PMCPMC6812727

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.