Evidence mapPaperPMID 30338403Full record

SynthesisCurrent diabetes reports2018

Effect of Health Information Technologies on Glycemic Control Among Patients with Type 2 Diabetes.

Yilin Yoshida, Suzanne A Boren, Jesus Soares, Mihail Popescu, Stephen D Nielson, Eduardo J Simoes

Open access · hybridAbstract readMeta-AnalysisReview
In one paragraph

Synthesis in Current diabetes reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 2 pooled it
2.9field-weighted citation impact, top 8% 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

15 citing papers in PubMed, 2 syntheses or guidelines pooled it, 27 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Could Online Education Replace Face-to-Face Education in Diabetes? A Systematic Review.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2024
    Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Therapeutic Inertia: Still a Long Way to Go That Cannot Be Postponed.Diabetes spectrum : a publication of the American Diabetes Association · 2020
    Article
  11. Review
  12. Review
  13. Article
  14. Article
  15. Review
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

6 authors at 3 institutions in 1 country.

Yilin YoshidaDepartment of Health Management and Informatics, School of Medicine, University of Missouri-Columbia, CE707 CS&E Bldg., One Hospital Drive, Columbia, MO, USA.
Suzanne A BorenDepartment of Health Management and Informatics, School of Medicine, University of Missouri-Columbia, CE707 CS&E Bldg., One Hospital Drive, Columbia, MO, USA.
Jesus SoaresCenters for Disease Control and Prevention, Division of High-Consequences Pathogens and Pathology, Prion and Public Health Office, Atlanta, GA, USA.
Mihail PopescuDepartment of Health Management and Informatics, School of Medicine, University of Missouri-Columbia, CE707 CS&E Bldg., One Hospital Drive, Columbia, MO, USA.
Stephen D NielsonMercy Medical Center, Sioux City, IA, USA.
Eduardo J SimoesDepartment of Health Management and Informatics, School of Medicine, University of Missouri-Columbia, CE707 CS&E Bldg., One Hospital Drive, Columbia, MO, USA. simoese@health.missouri.edu.
University of Missouri · USCenters for Disease Control and Prevention · USMercy Medical Center Sioux City · US

Funding

The Washington University Center for Diabetes Translation ResearchP30DK092950 · WASHINGTON UNIVERSITY · 2025 to 2025
$850k
NIDDK NIH HHS P30 DK092950
6 · The paper itself

Abstract

purpose of reviewThis study was to present meta-analysis findings across selected clinical trials for the effect of health information technologies (HITs) on glycemic control among patients with type 2 diabetes. RECENT

findingsHITs may be promising in diabetes management. However, findings on effect size of glycated hemoglobin level (HbA1c) yielded from HITs varied across previous studies. This is likely due to heterogeneity in sample size, adherence to standard quantitative method, and/or searching criteria (e.g., type of HITs, type of diabetes, specification of patient population, randomized vs. nonrandomized trials). We systematically searched Medline, Cumulative Index of Nursing and Allied Health Literature (CINAHL), and the Cochrane Library for peer-reviewed randomized control trials that studied the effect of HITs on HbA1c reduction. We also used Google Scholar and a hand search to identify additional studies. Thirty-four studies (40 estimates) met the criteria and were included in the analysis. Overall, introduction of HITs to standard diabetes treatment resulted in a statistically and clinically reduced HbA1c. The bias adjusted HbA1c reduction due to the combined HIT interventions was - 0.56 [Hedges' g = - 0.56 (- 0.70, - 0.43)]. The reduction was significant across each of the four types of HIT intervention under review, with mobile phone-based approaches generating the largest effects [Hedges' g was - 0.67 (- 0.90, - 0.45)]. HITs can be an effective tool for glycemic control among patients with type 2 diabetes. Future studies should examine long-term effects of HITs and explore factors that influence their effectiveness.

Indexed as

Medical InformaticsBlood GlucoseCell PhoneDiabetes Mellitus, Type 2Glycated HemoglobinHumansPublication BiasBlood GlucoseGlycated HemoglobinGlycated hemoglobin levelGlycemic controlHealth information technologiesType 2 diabetes

Identifiers

PMID30338403
PMCPMC6209028
OpenAlexW2897520591

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.