Mark Aagren1, Wenli Luo. 1. Novo Nordisk Inc, Princeton, NJ, USA. mkae@novonordisk.com
Abstract
UNLABELLED: Abstract Objectives: Glycemic control, measured by HbA(1c), is well known to be a risk marker for long-term costly diabetes-related complications. The relationship between HbA(1c) and short-term costs is unclear. This study investigates how HbA(1c) is correlated to short-term diabetes-related medical expenses. METHODS: Patients with diabetes with an HbA(1c) reading ≥6% between April and September 2007 were identified from a large US managed-care organization. Healthcare utilization data was obtained during the subsequent 12-month period. Multivariate analyses were performed to estimate the correlation between HbA(1c) and diabetes-related healthcare costs. RESULTS: In all, 34,469 and 1,837 patients with type 2 and type 1 diabetes, respectively, were identified with an HbA(1c) reading ≥6% (mean HbA(1c): 7.4% and 7.9%). The majority of patients with type 1 diabetes were treated with insulin, while most patients with type 2 diabetes were treated with metformin. The multivariate analysis showed that several characteristics, including HbA(1c), significantly correlate with diabetes-related medical costs for both patients with type 1 and type 2 diabetes. A 1-percentage-point increase in HbA(1c) will, on average, lead to a 6.0% and 4.4% increase in diabetes-related medical costs for type 1 and type 2 diabetes, respectively. This corresponds to an annual cost increase of $445 and $250 for patients with type 1 and type 2 diabetes, respectively. LIMITATIONS: Retrospective data analyses inherently associated with selection bias which can only partly be adjusted by statistical techniques. Furthermore, the study population is not necessarily representative of the general population and there can be isolated coding or data errors in the dataset. CONCLUSIONS: These results suggest that tighter glycemic control is associated with short-term cost benefits for patients with diabetes. This supplements conventional wisdom that HbA(1c) affects risk of long-term complications and long-term costs.
UNLABELLED: Abstract Objectives: Glycemic control, measured by HbA(1c), is well known to be a risk marker for long-term costly diabetes-related complications. The relationship between HbA(1c) and short-term costs is unclear. This study investigates how HbA(1c) is correlated to short-term diabetes-related medical expenses. METHODS:Patients with diabetes with an HbA(1c) reading ≥6% between April and September 2007 were identified from a large US managed-care organization. Healthcare utilization data was obtained during the subsequent 12-month period. Multivariate analyses were performed to estimate the correlation between HbA(1c) and diabetes-related healthcare costs. RESULTS: In all, 34,469 and 1,837 patients with type 2 and type 1 diabetes, respectively, were identified with an HbA(1c) reading ≥6% (mean HbA(1c): 7.4% and 7.9%). The majority of patients with type 1 diabetes were treated with insulin, while most patients with type 2 diabetes were treated with metformin. The multivariate analysis showed that several characteristics, including HbA(1c), significantly correlate with diabetes-related medical costs for both patients with type 1 and type 2 diabetes. A 1-percentage-point increase in HbA(1c) will, on average, lead to a 6.0% and 4.4% increase in diabetes-related medical costs for type 1 and type 2 diabetes, respectively. This corresponds to an annual cost increase of $445 and $250 for patients with type 1 and type 2 diabetes, respectively. LIMITATIONS: Retrospective data analyses inherently associated with selection bias which can only partly be adjusted by statistical techniques. Furthermore, the study population is not necessarily representative of the general population and there can be isolated coding or data errors in the dataset. CONCLUSIONS: These results suggest that tighter glycemic control is associated with short-term cost benefits for patients with diabetes. This supplements conventional wisdom that HbA(1c) affects risk of long-term complications and long-term costs.
Authors: Robert Brett McQueen; Marc D Breton; Joyce Craig; Hayden Holmes; Melanie D Whittington; Markus A Ott; Jonathan D Campbell Journal: J Diabetes Sci Technol Date: 2018-04-21
Authors: Rebecca S Gold; Jonathan T Unkart; Robyn L McClelland; Alain G Bertoni; Matthew A Allison Journal: Prim Care Diabetes Date: 2020-12-09 Impact factor: 2.459
Authors: Hannah König; A Rommel; Jens Baumert; Christian Schmidt; Hans-Helmut König; Christian Brettschneider; Alexander Konnopka Journal: BMJ Open Date: 2021-04-21 Impact factor: 2.692