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Diabetes Obes Metab. 2014 Feb;16(2):137-46. doi: 10.1111/dom.12186. Epub 2013 Aug 29.

Efficacy, usability and sequence of operations of a workflow-integrated algorithm for basal-bolus insulin therapy in hospitalized type 2 diabetes patients.

Author information

1
Division of Endocrinology and Metabolism, Department of Internal Medicine, Medical University of Graz, Graz, Austria.

Abstract

AIMS:

To evaluate glycaemic control and usability of a workflow-integrated algorithm for basal-bolus insulin therapy in a proof-of-concept study to develop a decision support system in hospitalized patients with type 2 diabetes.

METHODS:

In this ward-controlled study, 74 type 2 diabetes patients (24 female, age 68 ± 11 years, HbA1c 8.7 ± 2.4% and body mass index 30 ± 7) were assigned to either algorithm-based treatment with a basal-bolus insulin therapy or to standard glycaemic management. Algorithm performance was assessed by continuous glucose monitoring and staff's adherence to algorithm-calculated insulin dose.

RESULTS:

Average blood glucose levels (mmol/l) in the algorithm group were significantly reduced from 11.3 ± 3.6 (baseline) to 8.2 ± 1.8 (last 24 h) over a period of 7.5 ± 4.6 days (p < 0.001). The algorithm group had a significantly higher percentage of glucose levels in the ranges from 5.6 to 7.8 mmol/l (target range) and 3.9 to 10.0 mmol/l compared with the standard group (33 vs. 23% and 73 vs. 53%, both p < 0.001). Physicians' adherence to the algorithm-calculated total daily insulin dose was 95% and nurses' adherence to inject the algorithm-calculated basal and bolus insulin doses was high (98 and 93%, respectively). In the algorithm group, significantly more glucose values <3.9 mmol/l were detected in the afternoon relative to other times (p < 0.05), a finding mainly related to pronounced morning glucose excursions and requirements for corrective bolus insulin at lunch.

CONCLUSIONS:

The workflow-integrated algorithm for basal-bolus therapy was effective in establishing glycaemic control and was well accepted by medical staff. Our findings support the implementation of the algorithm in an electronic decision support system.

KEYWORDS:

glycaemic control; insulin analogues; insulin therapy; type 2 diabetes

PMID:
23910952
DOI:
10.1111/dom.12186
[Indexed for MEDLINE]

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