Evidence map›Paper›PMID 28617628›Full record

Trial reportJournal of diabetes science and technology2017

Pilot Study of a Novel Application for Data Visualization in Type 1 Diabetes.

Jenise C Wong, Aaron B Neinstein, Howard Look, Brandon Arbiter, Nora Chokr, Cassie Ross, Saleh Adi

Open access · bronzeAbstract readClinical Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Journal of diabetes science and technology, 2017. 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
2.5field-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

5 citing papers in PubMed, 33 citations in OpenAlex.

  1. Article
  2. Article
  3. Early experiences with patient generated health data: health system and patient perspectives.Journal of the American Medical Informatics Association : JAMIA · 2019
    Article
  4. Why Download Data: The Benefits and Challenges of More Diabetes Data.Diabetes spectrum : a publication of the American Diabetes Association · 2019
    Article
  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

7 authors at 2 institutions in 1 country.

Jenise C Wong1 Division of Endocrinology, Department of Pediatrics, Madison Clinic for Pediatric Diabetes, University of California, San Francisco, San Francisco, CA, USA.
Aaron B Neinstein2 Division of Endocrinology and Metabolism, Department of Medicine, Center for Digital Health Innovation, University of California, San Francisco, San Francisco, CA, USA.
Howard Look3 Tidepool, San Francisco, CA, USA.
Brandon Arbiter3 Tidepool, San Francisco, CA, USA.
Nora Chokr1 Division of Endocrinology, Department of Pediatrics, Madison Clinic for Pediatric Diabetes, University of California, San Francisco, San Francisco, CA, USA.
Cassie Ross1 Division of Endocrinology, Department of Pediatrics, Madison Clinic for Pediatric Diabetes, University of California, San Francisco, San Francisco, CA, USA.
Saleh Adi1 Division of Endocrinology, Department of Pediatrics, Madison Clinic for Pediatric Diabetes, University of California, San Francisco, San Francisco, CA, USA.
University of California, San Francisco · USTidepool · US

Funding

Optimizing Patient Use of Devices and Data in Early Adolescents with Type 1 DiabetesK23DK107894 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WONG, JENISE C · 2015 to 2017
$586k
NIDDK NIH HHS K23 DK107894
6 · The paper itself

Abstract

backgroundA novel software application, Blip, was created to combine and display diabetes data from multiple devices in a uniform, user-friendly manner. The objective of this study was to test the usability of this application by adults and caregivers of children with type 1 diabetes (T1D).

methodsPatients (n = 35) and caregivers of children with T1D (n = 30) using an insulin pump for >1 year ± CGM were given access to the software for 3 months. Diabetes management practices and the use of diabetes data were assessed at baseline and at study end, and feedback was gathered in a concluding questionnaire.

resultsAt baseline, 97% of participants agreed it was important for patients to know how to interpret glucose data. Most felt that clinicians and patients should share the tasks of reviewing data, finding patterns, and making changes to their insulin plans. However, despite valuing shared responsibility, at baseline, 43% of participants never downloaded pump data, and only 9% did so at least once per month. At study end, 72% downloaded data at least once during the 3-month study, and 38% downloaded at least once per month. Regarding the software application, participants liked the central repository of data and the user interface. Suggestions included providing tools for understanding and interpreting glucose patterns, an easier uploading process, and access with mobile devices.

conclusionsCollaboration between developers and researchers prompted iterative, rapid development of data visualization software and improvements in the uploading process and user interface, which facilitates clinical integration and future clinical studies.

Indexed as

SoftwareAdolescentAdultBlood GlucoseBlood Glucose Self-MonitoringCaregiversChildChild, PreschoolDiabetes Mellitus, Type 1FemaleHumansHypoglycemic AgentsInsulinInsulin Infusion SystemsMalePilot ProjectsBlood GlucoseHypoglycemic AgentsInsulincontinuous glucose monitoringdata platformdata visualizationdevice interoperabilityinsulin pumpstype 1 diabetes

Identifiers

PMID28617628
PMCPMC5588832
OpenAlexW2586286000

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.