Systematic Improvement of a Bolus Calculator That Is on the Market: A User-Centric Approach
Authors' conclusion
Altogether, human factor engineering and different forms of real-world data support fast and direct adaptations and improvements in products used for diabetes therapy.
Study context
- Population
- Users of a marketed bolus calculator for diabetes self-management
- Comparison
- Bolus calculator after vs before user-centric optimization
- Outcome
- Changes after bolus calculator optimization
Methodological detailshuman factor engineering, real-world glycemic data, patient-reported outcomes, machine-generated behavioral measurements
- Human factor engineering
- Real-world glycemic data
- Patient-reported outcomes
- Machine-generated behavioral measurements
Main finding
As reported in the abstract
Hypoglycemic events, change (±0.05), P < .01, n=3480
−0.52%
DTSQ treatment satisfaction, change, P < .01, n=217
+9.90
Acceptance rate of bolus calculations, change (±0.89), P < .01, n=3436
+15.73
Original publication
Systematic Improvement of a Bolus Calculator That Is on the Market: A User-Centric Approach. J Diabetes Sci Technol. Published 23 July 2024. doi:10.
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