OBJECTIVES: There are unresolved procedural and medical problems in the care of diabetes, which cause high costs for health systems. Personalized diabetes management can be seen as a kind of "standard process" that provides both physicians and patients with a framework. The purpose of this experiment is to demonstrate the properties of the programs that are relevant for the choice of insulin-based therapy regimens for patients with Type II diabetes mellitus.

METHODS: A discrete choice experiment (DCE) was applied to identify preferences for a personalized diabetes management in patients with type II diabetes mellitus. Six attributes were included. The DCE was conducted in June 2017 using a fractional factorial design, and the statistical data analysis used random effect logit models.

RESULTS: N=227 patients (66.1% male) were included. The preference analysis showed dominance for the attribute "occurrence of severe hypoglycemia per year" (level difference (LD): 2,765). Preference analysis also showed that participants weight the “risk of myocardial infarction (over 10 years)” (LD: 1.854) highest among the side effects. Within the effectiveness criterion of "change in the long-term blood glucose level (HbA1c)" a change at an initial value of 9.5% (LD: 1.146) is weighted slightly higher than changes at 7.5% (LD: 1.141). Within the random parameter logit estimation, all coefficients proved to be significantly different from zero at the level p≤0.01.

CONCLUSIONS: This study identifies and weights the key decision-making criteria for optimal management of diabetes from the perspective of patients. It was shown that the effectiveness of a care program is the most important from the perspective of the patient and avoiding severe hypoglycemia has the greatest influence on the choice. The risk of myocardial infarction as a follow-up disease and the long-term adjustment of the blood glucose follow the importance.