Lee, J, Rusnak, A, Garrity, A, Hirschfeld, E, Thomas, I, Wichorek, M, Lee, J, Rioles, N, Ebkozien, O, Corathers, S

Importance  A low-burden electronic health record (EHR) workflow has been devised to systematize the collection and validation of 6 key diabetes self-management habits: (1) checks glucose at least 4 times/day or uses continuous glucose monitor (CGM); (2) gives at least 3 rapid-acting insulin boluses per day; (3) uses insulin pump; (4) delivers boluses before meals; (5) reviewed glucose data since last clinic visit, and (6) has changed insulin doses since the last clinic visit.

Objective  To describe the performance of these habits and examine their association with hemoglobin A1c (HbA1c) levels and time in range (TIR).

Design, Setting, and Participants  This cross-sectional study included individuals with known type 1 diabetes who were seen in a US pediatric diabetes clinic in 2019.

Main Outcomes and Measures  Habit performance, total habit score (sum of 6 habits per person), HbA1c levels, and TIR.

Results  Of 1344 patients, 1212 (609 [50.2%] males; 66 [5.4%] non-Hispanic Black; 1030 [85.0%] non-Hispanic White; mean [SD] age, 15.5 [4.5] years) were included, of whom 654 (54.0%) were using CGM and had a TIR. Only 105 patients (8.7%) performed all 6 habits. Habit performance was lower among older vs younger patients (age ≥18 years vs ≤12 years: 17 of 411 [4.1%] vs 57 of 330 [17.3%]; P < .001), Black vs White patients (3 [4.5%] vs 95 [9.2%]; P < .001), those with public vs private insurance (14 of 271 [5.2%] vs 91 of 941 [9.7%]; P < .001), and those with lower vs higher parental education levels (<college degree vs ≥college degree: 35 of 443 [7.9%] vs 66 of 574 [11.5%]; P < .001). After adjustment for demographic characteristics and disease duration, for every 1-unit increase in total habit score, we found a mean (SE) 0.6% (0.05) decrease in HbA1c among all participants and a mean (SE) 2.86% (0.71) increase in TIR among those who used CGMs. Multiple regression models revealed that performing each habit was associated with a significantly lower HbA1c level (habit 1: –1.65% [95% CI, –1.91% to –1.37%]; habit 2: –1.01% [–1.34% to –0.69%]; habit 3: –0.71% [95% CI, –0.93% to –0.49%]; habit 4: –0.97% [95% CI, –1.21% to –0.73%]; habit 5: –0.44% [95% CI, –0.71% to –0.17%]; habit 6: –0.75% [95% CI, –0.96% to –0.53%]; all P < .001). There were differences in HbA1c according to race, insurance, and parental education, but these associations were attenuated with the inclusion of the 6 habits, which had more robust associations with HbA1c levels than the demographic characteristics.

Conclusions and Relevance  These findings suggest that a focus on increasing adherence to the 6 habits could be critical for improving disparities in glycemic outcomes; these metrics have been adopted by the Type 1 Diabetes Exchange Quality Improvement Collaborative for continuous quality improvement.

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