1165-P — 2014 ePoster: Development of a Personalized, Patient-Centered Glycemic Control Benchmarking Tool for T2DM


Presented on Sunday, June 15, 2014 12:00 PM


Glycemic control treatment targets for T2DM are intended to trigger clinical action in the management of patients; however, targets are usually benchmarked against averaged, population outcomes, and are not specific to individual patient characteristics. To explore treatment effectiveness heterogeneity (TEH) and to pilot test a personalized diabetes treatment benchmarking tool, we developed a causal model, statistical algorithm and a prototype interactive calculator using a pooled database of clinical, demographic and outcomes data from 19 diabetes RCTs (N=6870, 989 clinics) with rigorous protocols as the high quality benchmark standard. The prototype was developed from a database subsample of new or recently diagnosed patients with two treatment options using multiple logistic regression equations to obtain estimated high benchmark probabilities (HBPs) for achieving 12-wk, HbA1c < 7% and < 8.0%. The Excel-based calculator required input of individual patient pretreatment characteristics including HbA1c and FPG after 3 wks of diet and exercise only (D+E), sex, age, BMI, diabetes duration, race/ethnicity, prior treatment and planned treatment option (monotherapy or D+E). The HBPs for a White male, age 50 yrs, BMI = 30, FPG = 150 mg/dl and HbA1c = 9%, diabetes duration = 1 yr and treated previously with D+E were 0.51 and 0.94 for HbA1c < 7% and < 8% after 12 weeks on sulfonylurea monotherapy, and 0.06 and 0.48 if remaining on D+E. HBPs for a Black female, age 50 yrs, BMI = 36, FPG = 150 mg/dl, HbA1c = 9.5%, diabetes duration = 1 yr and treated previously with D+E were 0.41 and 0.78 on sulfonylurea, and 0.04 and 0.18 if remaining on D+E. Mean (SD) clinic-specific HBPs with case mix adjustment for personalized data were 0.35 (0.18) and 0.67 (0.17) for HbA1c < 7% and < 8% respectively indicating substantial TEH among clinics reflecting the variability in patient characteristics. Personalized benchmarking can provide a more equitable and patient-centered quality of care standard for T2DM

Disclosure:  M.A. Testa: None. D.C. Simonson: None. To view this Abstract and e-Poster, click on the hyperlink and then the View e-Poster Icon    View e-Poster -Click Here  To open View e-Poster it is best to use Chrome or Mozilla. If your browser opens automatically in Windows Explorer copy and direct link below in Chrome or Mozilla browser: https://ada.scientificposters.com/index.cfm?k=pskb57qwb6


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