Evidence map›Paper›PMID 19862578›Full record

Trial reportJournal of general internal medicine2009

The Vermont diabetes information system: a cluster randomized trial of a population based decision support system.

Charles D Maclean, Michael Gagnon, Peter Callas, Benjamin Littenberg

Abstract readComparative StudyMulticenter StudyRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Journal of general internal medicine, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 11 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 11 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.

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

35 citing papers in PubMed, 11 syntheses or guidelines pooled it.

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  12. Trial
  13. Translating What Works: A New Approach to Improve Diabetes Management.Journal of diabetes science and technology · 2015
    Trial
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  20. Conceptual Framework for Developing a Diabetes Information Network.Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH · 2016
    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

4 authors.

Charles D MacleanDivision of General Internal Medicine, University of Vermont College of Medicine, 371 Pearl Street, Burlington, VT 05401, USA. charles.maclean@uvm.edu
Michael Gagnon
Peter Callas
Benjamin Littenberg

Funding

Vermont Diabetes Information SystemR01DK061167 · NIDDK · UNIVERSITY OF VERMONT &ST AGRIC COLLEGE · PI LITTENBERG, BENJAMIN · 2002 to 2005
$2.0M
Barriers to Optimum Diabetes OutcomesK24DK068380 · NIDDK · UNIVERSITY OF VERMONT &ST AGRIC COLLEGE · PI LITTENBERG, BENJAMIN · 2004 to 2008
$790k
NIDDK NIH HHS K24 DK068380NIDDK NIH HHS R01 DK061167NIDDK NIH HHS R01 DK61167
6 · The paper itself

Abstract

backgroundOptimal care for patients with diabetes is difficult to achieve in clinical practice.

objectiveTo evaluate the impact of a registry and decision support system on processes of care, and physiologic control.

participantsRandomized trial with clustering at the practice level, involving 7,412 adults with diabetes in 64 primary care practices in the Northeast.

interventionsProvider decision support (reminders for overdue diabetes tests, alerts regarding abnormal results, and quarterly population reports with peer comparisons) and patient decision support (reminders and alerts). MEASUREMENTS AND MAIN

resultsProcess and physiologic outcomes were evaluated in all subjects. Functional status was evaluated in a random patient sample via questionnaire. We used multiple logistic regression to quantify the effect, adjusting for clustering and potential confounders. Intervention subjects were significantly more likely to receive guideline-appropriate testing for cholesterol (OR = 1.39; [95%CI 1.07, 1.80] P = 0.012), creatinine (OR = 1.40; [95%CI 1.06, 1.84] P = 0.018), and proteinuria (OR = 1.74; [95%CI 1.13, 1.69] P = 0.012), but not A1C (OR = 1.17; [95% CI 0.80, 1.72] P = 0.43). Rates of control of A1C and LDL cholesterol were similar in the two groups. There were no differences in blood pressure, body mass index, or functional status.

conclusionsA chronic disease registry and decision support system based on easily obtainable laboratory data was feasible and acceptable to patients and providers. This system improved the process of laboratory monitoring in primary care, but not physiologic control.

Indexed as

Decision Support Systems, ClinicalAdolescentAdultAgedAged, 80 and overCluster AnalysisDiabetes MellitusFemaleFollow-Up StudiesHumansLaboratories, HospitalMaleMiddle AgedPatient Education as TopicPopulationRegistries

Identifiers

PMID19862578
PMCPMC2787948

What OpenQuestion holds

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Registered trials

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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.