Evidence map›Paper›PMID 23171659›Full record

Trial reportJournal of the American Medical Informatics Association : JAMIA2013

Online disease management of diabetes: engaging and motivating patients online with enhanced resources-diabetes (EMPOWER-D), a randomized controlled trial.

Paul C Tang, J Marc Overhage, Albert Solomon Chan, Nancy L Brown, Bahar Aghighi, Martin P Entwistle, Siu Lui Hui, Shauna M Hyde, Linda H Klieman, Charlotte J Mitchell and 5 more

3 registry-linked trialsAbstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Journal of the American Medical Informatics Association : JAMIA, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 3 registered trials, which are not on this map. Cited by 117 papers, 35 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
117citing papers in PubMed, 35 pooled it
–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.

NCT00542204 nacompletednot on this map

Patient-Centered Online Disease Management Using a Personal Health Record System

TypeinterventionalSponsorPalo Alto Medical FoundationRan2008 to 2011Enrolled415ConditionsDiabetes MellitusArmsOnline disease management
NCT05541120 nawithdrawnnot on this mapstarted 2022, after this paper: background citation

Effect of Remote Patient Monitoring and Patient Education on Patient Activation and Glycemic Control in Individuals With Type 2 Diabetes

TypeinterventionalSponsorTracy Jalbuena MDRan2022 to 2026Enrolled0ConditionsDiabetes Mellitus, Type 2ArmsRemote Patient Monitoring
NCT06178094 nacompletednot on this mapstarted 2022, after this paper: background citation

The Effects of Video Training Given to Individuals With Type 2 Diabetes Through Smartphones on Self-Care and Metabolic Control

TypeinterventionalSponsorKırklareli UniversityRan2022 to 2022Enrolled112ConditionsDiabetes Mellitus, Type 2, TrainingArmsVideo Training
3 · Its place in the literature

Who cites it

117 citing papers in PubMed, 35 syntheses or guidelines pooled it.

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  16. Adult patient access to electronic health records.The Cochrane database of systematic reviews · 2021
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57 more citing papers are in PubMed but not listed here.

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

15 authors.

Paul C TangInnovation Center, Palo Alto Medical Foundation, Palo Alto, CA 94040, USA. tangp@pamf.org
J Marc Overhage
Albert Solomon Chan
Nancy L Brown
Bahar Aghighi
Martin P Entwistle
Siu Lui Hui
Shauna M Hyde
Linda H Klieman
Charlotte J Mitchell
Anthony J Perkins
Lubna S Qureshi
Tanya A Waltimyer
Leigha J Winters
Charles Y Young

Funding

Patient-Centered Online Disease Management Using a Personal Health Record SystemR18HS017179 · AHRQ · PALO ALTO MEDICAL FOUNDATION RES INST · PI TANG, PAUL C. · 2007 to 2009
$1.2M
AHRQ HHS 1R18HS017179-01AHRQ HHS R18 HS017179
6 · The paper itself

Abstract

objectiveTo evaluate an online disease management system supporting patients with uncontrolled type 2 diabetes. MATERIALS AND

methodsEngaging and Motivating Patients Online With Enhanced Resources for Diabetes was a 12-month parallel randomized controlled trial of 415 patients with type 2 diabetes with baseline glycosylated hemoglobin (A1C) values ≥7.5% from primary care sites sharing an electronic health record. The intervention included: (1) wirelessly uploaded home glucometer readings with graphical feedback; (2) comprehensive patient-specific diabetes summary status report; (3) nutrition and exercise logs; (4) insulin record; (5) online messaging with the patient's health team; (6) nurse care manager and dietitian providing advice and medication management; and (7) personalized text and video educational 'nuggets' dispensed electronically by the care team. A1C was the primary outcome variable.

resultsCompared with usual care (UC, n=189), patients in the intervention (INT, n=193) group had significantly reduced A1C at 6 months (-1.32% INT vs -0.66% UC; p<0.001). At 12 months, the differences were not significant (-1.14% INT vs -0.95% UC; p=0.133). In post hoc analysis, significantly more INT patients had improved diabetes control (>0.5% reduction in A1C) than UC patients at 12 months (69.9 (95% CI 63.2 to 76.5) vs 55.4 (95% CI 48.4 to 62.5); p=0.006).

conclusionsA nurse-led, multidisciplinary health team can manage a population of diabetic patients in an online disease management program. INT patients achieved greater decreases in A1C at 6 months than UC patients, but the differences were not sustained at 12 months. More INT than UC patients achieved improvement in A1C (>0.5% decrease). Trial registered in clinical trials.gov: #NCT00542204.

Indexed as

Self CareTelemedicineAdultAgedAged, 80 and overDiabetes Mellitus, Type 2Disease ManagementFemaleGlycated HemoglobinHealth BehaviorHumansInternetMaleMiddle AgedPatient Care TeamYoung AdultGlycated Hemoglobinhemoglobin A1c protein, human

Identifiers

PMID23171659
PMCPMC3628059

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.