Evidence mapPaperPMID 30322839Full record

ArticleJMIR mHealth and uHealth2018

An mHealth Diabetes Intervention for Glucose Control: Health Care Utilization Analysis.

Charlene C Quinn, Krystal K Swasey, Jamila M Torain, Michelle D Shardell, Michael L Terrin, Erik A Barr, Ann L Gruber-Baldini

Registry-linked trialAbstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01107015 (Mobile Diabetes Management), which is not on this 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.

NCT01107015 nacompletednot on this map

Mobile Diabetes Management

TypeinterventionalSponsorUniversity of Maryland, BaltimoreRan2008 to 2011Enrolled213ConditionsDiabetesArmsTailored Patient Intervention, Patient-physician intervention, Patient and PCP intervention with analyzed data
3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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.

Charlene C QuinnDepartment of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, United States.ORCID http://orcid.org/0000-0002-6066-2984
Krystal K SwaseyDepartment of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, United States.ORCID http://orcid.org/0000-0003-3241-901X
Jamila M TorainDepartment of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, United States.ORCID http://orcid.org/0000-0002-5174-4865
Michelle D ShardellTranslational Gerontology Branch, National Institutes on Aging, Baltimore, MD, United States.ORCID http://orcid.org/0000-0002-5283-2082
Michael L TerrinDepartment of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, United States.ORCID http://orcid.org/0000-0002-6342-2900
Erik A BarrDepartment of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, United States.ORCID http://orcid.org/0000-0002-4253-9376
Ann L Gruber-BaldiniDepartment of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, United States.ORCID http://orcid.org/0000-0002-0190-1973

Funding

EXPAND PARTICIPATION BY MINORITIES IN BIOMEDICAL SCIENCER25GM055036 · UNIVERSITY OF MARYLAND BALT CO CAMPUS · 1996 to 2005
$3.6M
University of Maryland Claude D. Pepper Older Americans Independence Center (OAIC)P30AG028747 · UNIVERSITY OF MARYLAND BALTIMORE · 2025 to 2025
$1.2M
NIA NIH HHS P30 AG028747NIGMS NIH HHS R25 GM055036
6 · The paper itself

Abstract

backgroundType 2 diabetes (T2D) is a major chronic condition requiring management through lifestyle changes and recommended health service visits. Mobile health (mHealth) is a promising tool to encourage self-management, but few studies have investigated the impact of mHealth on health care utilization.

objectiveThe objective of this analysis was to determine the change in 2-year health service utilization and whether utilization explained a 1.9% absolute decrease in glycated hemoglobin (HbA

methodsWe used commercial claims data from 2006 to 2010 linked to enrolled patients' medical chart data in 26 primary care practices in Maryland, USA. Secondary claims data analyses were available for 56% (92/163) of participants. In the primary MDIS study, physician practices were recruited and randomized to usual care and 1 of 3 increasingly complex interventions. Patients followed physician randomization assignment. The main variables in the analysis included health service utilization by type of service and change in HbA

resultsA significant group by time effect was observed in physician office visits, general practitioner visits, other outpatient services, prescription medications, and podiatrist visits. Physician office visits (P=.01) and general practitioner visits (P=.02) both decreased for all intervention groups during the study period, whereas prescription claims (P<.001) increased. The frequency of other outpatient services (P=.001) and podiatrist visits (P=.04) decreased for the control group and least complex intervention group but increased for the 2 most complex intervention groups. No significant effects of utilization were observed to explain the clinically significant change in HbA

conclusionsClaims data analyses identified patterns of utilization relevant to mHealth interventions. Findings may encourage patients and health providers to discuss the utilization of treatment-recommended services, lab tests, and prescribed medications.

trial registrationClinicalTrials.gov NCT01107015; https://clinicaltrials.gov/ct2/show/NCT01107015 (Archived by Webcite at http://www.webcitation.org/72XgTaxIj).

Indexed as

cluster randomized clinical trialhealth carehealth service utilizationmHealthtype 2 diabetes

Identifiers

PMID30322839
PMCPMC6231737

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.