Products & Solutions

GlucoTab@Home

Algorithm-Based Insulin Therapies for Patient Self-Management

Background

Conventional forms of insulin therapies often fail to provide the needed ‘almost’ daily guidance for therapy safety. This can lead to inadequate metabolic control, non-achievement of target values, and even blood glucose derailments. In order to support patients in their blood glucose management at home, the GlucoTab® system, which has been tried and tested in clinical inpatient use, has been adapted for patient self-management. It supports in the continuous adjustment of short- and long-acting insulins, dosage suggestions for meal and correction insulin, and provides intelligent, immediate protective measures.

Project content

Care Concept GlucoTab@Home. General practitioners and diabetes specialists are supported in insulin therapy initialisation, patients and caregivers are supported in adjusting their insulin dose according to medical algorithms. The coordination with the physicians takes place via telephone or telemedicine.

The necessary adaptations to the current GlucoTab® Basal Bolus insulin dosing algorithm were identified using a detailed requirements analysis within the framework of a co-creation process. This included user surveys, a structured literature review, and analysis of existing data. The specification, prototypical development and technical documentation were carried out according to the standards of IEC 62304 within the ISO EN 13485 quality management system.

 

The new care concept potentially results in the following benefits for patients:

  • More frequent therapy feedback
  • Increased sense of safety
  • Lowering of the HbA1c value
  • Reduction of blood glucose variability
  • Avoidance of hypoglycemia
  • Avoidance of medication errors
Project key facts
  • Duration: 2019 - 2020
  • Project lead: DI Dr. Klaus Donsa
  • Status: Prototype (developed in compliance with standards for the development of medical devices)
  • Funding: Province of Styria
  • Co-Creation development process with Medical University of Graz and decide Clinical Software GmbH
Publications
  • Nitsche, P; (2020) Development of an in silico simulation test environment for the design of algorithms used in software as a medical device (Master’s thesis)