Description of a New Predictive Modeling Approach That Correlates the Risk and Associated Cost of Well-Defined Diabetes-Related Complications With Changes in Glycated Hemoglobin (HbA1c)

Abstract

The modeling approach described here is designed to support the development of spreadsheet-based simple predictive models. It is based on 3 pillars: association of the complications with HbA1c changes, incidence of the complications, and average cost per event of the complication. For each pillar, the goal of the analysis was (1) to find results for a large diversity of populations with a focus on countries/regions, diabetes type, age, diabetes duration, baseline HbA1c value, and gender; (2) to assess the range of incidences and associations previously reported. Unlike simple predictive models, which mostly are based on only 1 source of information for each of the pillars, we conducted a comprehensive, systematic literature review. Each source found was thoroughly reviewed and only sources meeting quality expectations were considered. The approach allows avoidance of unintended use of extreme data. The user can utilize (1) one of the found sources, (2) the found range as validation for the found figures, or (3) the average of all found publications for an expedited estimate. The modeling approach is intended for use in average insulin-treated diabetes populations in which the baseline HbA1c values are within an average range (6.5% to 11.5%); it is not intended for use in individuals or unique diabetes populations (eg, gestational diabetes). Because the modeling approach only considers diabetes-related complications that are positively associated with HbA1c decreases, the costs of negatively associated complications (eg, severe hypoglycemic events) must be calculated separately.

The Financial Impact of Inaccurate Blood Glucose Monitoring Systems

“…The HbA1c Translator modeling approach is designed to support the development of simple predictive models that estimate the health and economic impact of changes in HbA1c values on insulin-treated diabetes patients. 22 The tool contains 16 cost datasets and draws on medical evidence based on studies of over 1.08 million patients or 9.6 million patient years. The approach can be used with mixed populations of both T1DM and insulin-treated T2DM patients, regardless of age, gender and other demographic parameters.…”

“…We then utilized a model built on the HbA1c Translator approach 22 to calculate the financial impact of these changes, utilizing our T1DM population data set in conjunction with the UK cost data for a T1DM population as reported by Roze and colleagues. 16 Results are reported in cost (British pounds [£]) per patient year (PPY).…”

“…The design and methodology utilized by the HbA1c Translator Model is described in a recent publication. 22 …”

“… 21 In this analysis, we apply findings from the study to assess the financial impact of inaccuracy of BGM devices on changes in HbA1c, annual SHE, and health care resource utilization (insulin and test strip consumption), using the HbA1c Translator model. 22 …”

Modeling of Diabetes and Its Clinical Impact

“…11 Fortwaengler and colleagues modeled risk and cost estimation of insulin-treated patients with diabetes by assessing the association of complications with HbA1c changes, the incidence of complications and the average cost per event of the complications associated with HbA1c changes. 50 Based on this, they combined their modeling approach with data provided by the UVA/Padova type 1 diabetes simulator to investigate the influence of SMBG system accuracy on clinical outcomes and their financial impact. They could show an increase in costs associated with less accurate SMBG systems as a result of an increased incidence of complications.…”