ArticleJournal of diabetes science and technology2013
The impact of a decision support tool linked to an electronic medical record on glycemic control in people with type 2 diabetes.
Article in Journal of diabetes science and technology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.
What it found
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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.
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.
Who cites it
6 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Design, effectiveness, and economic outcomes of contemporary chronic disease clinical decision support systems: a systematic review and meta-analysis.Journal of the American Medical Informatics Association : JAMIA · 2022Pooled it
- A systematic review of the effects of implementing clinical pathways supported by health information technologies.Journal of the American Medical Informatics Association : JAMIA · 2019Pooled it
- Benefits of Clinical Decision Support Systems for the Management of Noncommunicable Chronic Diseases: Targeted Literature Review.Interactive journal of medical research · 2024Review
- Applications of Clinical Decision Support Systems in Diabetes Care: Scoping Review.Journal of medical Internet research · 2023Article
- Guiding Glucose Management Discussions Among Adults With Type 2 Diabetes in General Practice: Development and Pretesting of a Clinical Decision Support Tool Prototype Embedded in an Electronic Medical Record.JMIR formative research · 2020Article
- The effect of using a shared electronic health record on quality of care in people with type 2 diabetes.Journal of diabetes science and technology · 2014Observational
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimsWe retrospectively compared glycemic control and glycemic burden in type 2 diabetes patients treated by general physicians with access to decision support with those treated by general physicians without access to decision support.
methodsA total of 875 patients [471 (53.8%) males] aged 54.3 [standard deviation (SD) 13.1] years followed up over 84 months. A total of 342 patients (39%) were managed with decision support, and effects on glycosylated hemoglobin (HbA1c) were assessed.
resultsThere was no difference between groups in starting HbA1c [7.6 (SD 1.8) versus 7.5 (SD 1.5); p = not significant] at baseline. Patients treated with decision support were more likely to have planned review of HbA1c, adjustment of medication, prescription of statins, dietetic and nurse educator inputs (71.3% versus 58.5%; Chi squared = 14.7; p = .001). The mean HbA1c in the group treated with decision support was not significantly reduced within the first year [7.5% (SD 1.8) versus 7.6% (SD 1.5); p = not significant; 95% confidence interval (CI) -0.33 to 0.17], but statistically significant differences were apparent at year 2 [7.2% (SD 2.0) versus 8% (SD 3.4); p = .0001; 95% CI -1.3 to -0.5] and sustained through year 3 [7.2% (SD 2.0) versus 8.0% (SD 2.0); p = .0001; 95% CI -1.2 to -0.6], year 4 [7.2% (SD 2.3) versus 8.2% (SD 2.5); p = .0001; 95% CI -1.2 to -0.6], year 5 [7.0% (SD 2.3) versus 8.3% (SD 2.6); p = .001; 95% CI -1.5 to -0.8], year 6 [7.0% (SD 2.0) versus 8.2% (SD 2.4); p = .001; 95% CI -1.5 to -0.9], and year 7 [6.9% (SD 1.2) versus 8% (SD 1.8); p = .001; 95% CI -1.4 to -1.0].
conclusionUse of a decision support system showed benefits in adherence to clinical care pathways and achieving significant improvements in glycemic control.
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