Predictors of Insulin Pump Initiation Among People with Type 2 Diabetes from a US Claims Database Using Machine Learning
Author(s)
Hankosky ER1, Katz M1, Fan L1, Brnabic A2, Liu D1, Chinthammit C1, Eby E1
1Eli Lilly and Company, Indianapolis, IN, USA, 2Eli Lilly and Company, Croydon, NSW, Australia
OBJECTIVES: Insulin pump use among people with type 2 diabetes (T2D) is increasing. This work aims to identify predictors of insulin pump initiation among people with T2D. METHODS: This was a retrospective, nested case-control study using the IBM® Marketscan® Commercial Database (2015-2020). People with T2D (18-64 years) with first prescription for bolus insulin (index date) on or after 1 January 2016 and no prior pump claims were included. From this cohort, cases (pump initiators) were identified and matched (1:4, with replacement) with controls using incidence density sampling for time at risk (time from index to the lookback date, which was set to pump initiation for cases) and index date (±6 months). Conditional logistic regression (CLR) and penalized CLR models assessed predictors of pump initiation and model choice was evaluated using the Akaike information criterion. A sensitivity analysis implemented matching without replacement. RESULTS: From the cohort (N=32,104; mean age (standard deviation), 51.8 (9.5); 49.1% female), 726 cases were identified and matched to controls (n=2,904). In the 6 months prior to lookback, the top 5 predictors were CGM/FGM use (vs. BGM only; odds ratio, 5.4; 95% confidence interval, [3.8, 7.7]), presence of an endocrinologist visit (2.7 [2.2, 3.4]), acute metabolic complications (e.g., ketoacidosis, hypoglycaemia with coma; 2.5 [1.2, 5.4]), insulin use (no insulin vs. insulin; 0.2 [0.1-0.4]), and West region (vs. North Central; 0.6 [0.4, 0.9]). Results of the sensitivity analysis were similar to the primary analysis, with the exception that elevated HbA1c replaced region in the top 5 predictors. CONCLUSIONS: Factors associated with pump initiation among people with T2D include technology use (CGM), diabetes engagement including endocrinologist visits, maintained insulin use, and acute metabolic complications.
Conference/Value in Health Info
2021-11, ISPOR Europe 2021, Copenhagen, Denmark
Value in Health, Volume 24, Issue 12, S2 (December 2021)
Code
POSC390
Topic
Health Service Delivery & Process of Care, Medical Technologies, Methodological & Statistical Research
Topic Subcategory
Artificial Intelligence, Machine Learning, Predictive Analytics, Disease Management, Medical Devices, Prescribing Behavior
Disease
Diabetes/Endocrine/Metabolic Disorders, Medical Devices
Explore Related HEOR by Topic