Settings Associated with Optimal Glycemic Outcomes with the Omnipod® 5 Automated Insulin Delivery System: Evidence from Real-World Users with Type 1 Diabetes

Objective: Identifying programmable device settings and user behaviors associated with achieving glycemic targets is critical for informing clinical practice and improving outcomes with automated insulin delivery (AID) systems. This real-world analysis aimed to identify predictors of achieving optimal glycemic outcomes for people with type 1 diabetes (T1D) using the Omnipod ® 5 AID System. Methods: This retrospective analysis included real-world data from Omnipod 5 users aged ≥ 2 years with T1D in the United States and Europe who had sufficient continuous glucose monitor data (≥30 days with ≥1 reading; ≥75% of days with ≥220 readings) available in Insulet’s device and person-reported datasets between January 1 and March 31, 2025. Logistic regression was used to identify programmable settings and user behaviors associated with achieving >70% time in range (TIR; 70–180 mg/dL [3.9–10.0 mmol/L]). Optimal thresholds for the top modifiable predictors were determined using Youden’s J statistic, and their impact on glycemic outcomes was explored. Results: Data from 176,405 users were analyzed. Predictors of achieving >70% TIR included the following: a higher number of user-initiated boluses/day, greater time in Automated Mode, use of lower glucose targets, and a more aggressive correction factor (CF) and insulin-to-carbohydrate (I:C) ratio (all P < 0.001). Use of optimized device settings (110 mg/dL [6.1 mmol/L] target, I:C ratio ≤350/total daily insulin dose [TDD], and CF ≤1500/TDD [mg/dL] or ≤83/TDD [mmol/L]) with user behaviors that reflect expected system use (≥90% time in Automated Mode, ≥3 boluses/day), used by 7.9% and 1.4% of adult and pediatric users, respectively, resulted in a higher median TIR compared with users overall (77% vs. 66% in adult and 78% vs. 62% in pediatric users, respectively), and time spent in hypoglycemia remained low across age groups. Findings were consistent across geographic regions and prior insulin regimen. Conclusions: These results provide actionable guidance for clinicians to optimize outcomes for people with T1D using the Omnipod 5 System.

Authors

Institutions

Publication Details

Journal
Diabetes Technology & Therapeutics
Published
2026-06-24
DOI
https://doi.org/10.1177/15209156261456826
Primary Topic
Diabetes Management and Research
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Settings Associated with Optimal Glycemic Outcomes with the Omnipod® 5 Automated Insulin Delivery System: Evidence from Real-World Users with Type 1 Diabetes

Kellee M. Miller, Trang T. Ly, Alexandra Sawyer, Gregory P. Forlenza et al.
Diabetes Technology & Therapeutics
Diabetes Management and Research
article

Settings Associated with Optimal Glycemic Outcomes with the Omnipod® 5 Automated Insulin Delivery System: Evidence from Real-World Users with Type 1 Diabetes

Kellee M. Miller, Trang T. Ly, Alexandra Sawyer, Gregory P. Forlenza, D Do, Emma G. Wilmot
article en

Abstract

Objective: Identifying programmable device settings and user behaviors associated with achieving glycemic targets is critical for informing clinical practice and improving outcomes with automated insulin delivery (AID) systems. This real-world analysis aimed to identify predictors of achieving optimal glycemic outcomes for people with type 1 diabetes (T1D) using the Omnipod ® 5 AID System. Methods: This retrospective analysis included real-world data from Omnipod 5 users aged ≥ 2 years with T1D in the United States and Europe who had sufficient continuous glucose monitor data (≥30 days with ≥1 reading; ≥75% of days with ≥220 readings) available in Insulet’s device and person-reported datasets between January 1 and March 31, 2025. Logistic regression was used to identify programmable settings and user behaviors associated with achieving >70% time in range (TIR; 70–180 mg/dL [3.9–10.0 mmol/L]). Optimal thresholds for the top modifiable predictors were determined using Youden’s J statistic, and their impact on glycemic outcomes was explored. Results: Data from 176,405 users were analyzed. Predictors of achieving >70% TIR included the following: a higher number of user-initiated boluses/day, greater time in Automated Mode, use of lower glucose targets, and a more aggressive correction factor (CF) and insulin-to-carbohydrate (I:C) ratio (all P < 0.001). Use of optimized device settings (110 mg/dL [6.1 mmol/L] target, I:C ratio ≤350/total daily insulin dose [TDD], and CF ≤1500/TDD [mg/dL] or ≤83/TDD [mmol/L]) with user behaviors that reflect expected system use (≥90% time in Automated Mode, ≥3 boluses/day), used by 7.9% and 1.4% of adult and pediatric users, respectively, resulted in a higher median TIR compared with users overall (77% vs. 66% in adult and 78% vs. 62% in pediatric users, respectively), and time spent in hypoglycemia remained low across age groups. Findings were consistent across geographic regions and prior insulin regimen. Conclusions: These results provide actionable guidance for clinicians to optimize outcomes for people with T1D using the Omnipod 5 System.

Diabetes Technology & Therapeutics
University of Nottingham (GB), Royal Derby Hospital (GB), Insulet (United States) (US), University of Colorado Anschutz Medical Campus (US)
Insulet Corporation
Quality Education
Openalex Percentile: Top 8%
Diabetes Management and Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.