Using survival modelling as a composite measure of outcome to demonstrate insulin pump therapy effectiveness in type 1 diabetes

Glycated haemoglobin (HbA 1c ) is a time‐series measure subject to variability; quantifying the difference between the first and last readings over a defined period may have little value in measuring success in service evaluation models. Identifying a composite measure for outcome would be an invaluable tool for service providers. We demonstrate the efficacy of survival modelling as a composite measure of outcome. This was a retrospective observational cohort analysis of patients with type 1 diabetes on insulin pump therapy. From these data, a service evaluation project was undertaken. Survival (time‐to‐event) analysis was undertaken for two HbA 1c values – 58 and 64mmol/mol (7.5% and 8.0%); analyses were based on time taken to reach the index HbA 1c value (58 or 64mmol/mol) for the first time from start of pump therapy. A total of 113 patients were treated with the insulin pump. The median time to reach an HbA 1c of 58 and 64mmol/mol was 25 and 13.9 months, respectively. Cox regression using gender, HbA 1c , weight and age prior to pump therapy as factor variables identified HbA 1c as the only predictor that significantly influenced the time‐to‐event (HR 0.94, p=0.001 for HbA 1c 58mmol/mol, and HR 0.97, p=0.008 for HbA 1c 64mmol/mol). Survival modelling appears to be a robust statistical tool to evaluate performance. Furthermore, adjusting for covariates identifies factors that may influence outcome. Pump therapy is considered a high cost area by commissioners, therefore having auditable outcome measures would be useful to inform authorities on the effectiveness of the service. Copyright © 2020 John Wiley & Sons.