| Literature DB >> 32914640 |
Katharina M Lichtenegger1, Felix Aberer1, Alexandru C Tuca2, Klaus Donsa3, Bernhard Höll3,4, Lukas Schaupp1, Johannes Plank5, Peter Beck3,4, Friedrich M Fruhwald6, Lars-Peter Kamolz2, Thomas R Pieber1,3, Julia K Mader1.
Abstract
The aim was to investigate the applicability of a clinical decision support system in a real-world inpatient setting for patients with type 2 diabetes on general hospital wards.A total of 150 patients with type 2 diabetes requiring subcutaneous insulin therapy were treated with basal-bolus insulin therapy guided by a decision support system (GlucoTab) providing automated workflow tasks and suggestions for insulin dosing to health care professionals.By using the system, a mean daily blood glucose (BG) of 159 ± 32 mg/dL was achieved. 68.8% of measurements were in the target range (70 to <180 mg/dL). The percentage of BG values <40, <70, and ≥300 mg/dL was 0.02%, 2.2%, and 2.3%, respectively. Health care professionals' adherence to suggested insulin doses and workflow tasks was high (>93% and 91%, respectively).The decision support system facilitates safe and efficacious inpatient diabetes care by standardizing treatment workflow and providing decision support for basal-bolus insulin dosing.Entities:
Keywords: algorithm; decision support; hospital; insulin therapy; mobile applications; type 2 diabetes
Year: 2020 PMID: 32914640 PMCID: PMC8256070 DOI: 10.1177/1932296820955243
Source DB: PubMed Journal: J Diabetes Sci Technol ISSN: 1932-2968