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J Diabetes Sci Technol. 2015 Jul;9(4):857-64. doi: 10.1177/1932296815576000. Epub 2015 Mar 9.

Translating What Works: A New Approach to Improve Diabetes Management.

Author information

1
Atlanta VA Medical Center, Decatur, GA, USA Division of Endocrinology and Metabolism, Department of Medicine, Emory University School of Medicine, Atlanta, GA medlsp@emory.edu.
2
VA Medical Center, Gainesville, FL, USA Division of Endocrinology and Metabolism, Department of Medicine, University of Florida School of Medicine, Gainesville, FL, USA.
3
Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
4
Atlanta VA Medical Center, Decatur, GA, USA Division of General Medicine and Geriatrics, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA.
5
Atlanta VA Medical Center, Decatur, GA, USA Nutrition and Health Sciences, Graduate Division of Biological and Biomedical Sciences, Emory University, Atlanta, GA, USA.
6
Atlanta VA Medical Center, Decatur, GA, USA Division of Endocrinology and Metabolism, Department of Medicine, Emory University School of Medicine, Atlanta, GA.
7
Atlanta VA Medical Center, Decatur, GA, USA.
8
Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA.

Abstract

BACKGROUND:

The most efficacious strategies to improve diabetes control include case management, health care team changes, patient education, and facilitated transmission of patient data to clinicians ("facilitated relay"), but these strategies have not been translated to permit general use in clinical practice.

METHODS:

A web-based decision support program was developed to include these features, and assessed in patients who had A1c ≥7.0% despite using metformin with/without sulfonylureas or insulin. Staff entered patients' glucose data, obtained management recommendations, reviewed the plan with a clinician, and discussed the new plan with patients.

RESULTS:

113 subjects were 96% male and 32% black, with average age 65.6 years and BMI 32.8. During prior primary care, A1c averaged 8.32 ± 0.16% (SEM). In all patients, baseline A1c was 8.18 ± 0.11%, and decreased to 7.54 ± 0.12%, 7.16 ± 0.13%, and 7.54 ± 0.16% at 3, 6, and 12 months, respectively, all P < .001. In 42 subjects who provided glucose data and made requested changes in medications, A1c was 8.12 ± 0.09% at baseline and fell to 7.29 ± 0.11%, 6.98 ± 0.10%, and 7.05 ± 0.10% at 3, 6, and 12 months, respectively, all P < .001. Chart review of 16 subjects followed for 12 months demonstrated that hypoglycemia (symptoms and/or glucose <70 mg/dl) averaged less than 1 episode/patient/month, and there was no severe hypoglycemia.

CONCLUSIONS:

A novel decision support program improved A1c with little hypoglycemia. Use of this approach should allow primary care teams to keep patients well controlled, and reduce the need for specialist referrals.

KEYWORDS:

clinical decision making; computer; decision support; hypoglycemia; management; primary care; type 2 diabetes

PMID:
25759182
PMCID:
PMC4525659
DOI:
10.1177/1932296815576000
[Indexed for MEDLINE]
Free PMC Article

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