Evaluation of glycemic over and under-treatment indicators for high-risk Veterans

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Background: One in four veterans have diabetes, of whom 40% are 60-69 years of age (the Vietnam era cohort); and about 25% are over 70 years of age. Serious co-morbid conditions are common (31%) even in younger (<65 years) veterans. About one in five veterans >65 years have cognitive impairment or dementia, and about 30% have an estimated Glomerular Filtration Rate of <60 ml/min/1.73m2. About 30% of veterans receive insulin, and the use of basal insulin has increased by 41% since 2008. Recent American Diabetes Association Guidelines agree with VHA-DoD Diabetes Guidelines that target values should be individualized based upon factors such as life expectancy, comorbid conditions, patient preferences, and risk for serious hypoglycemia. However, the current National Committee for Quality Assurance (NCQA) <7% A1c measure for persons less than 65 years of age neither stratifies by insulin nor excludes serious non-diabetes related or mental co-morbid conditions. The NCQA <8% A1c measure applicable to persons 65 to 74 years of age has no exclusion criteria. There is also no recommendation to assess glycemic management in individuals with diabetes >75 years of age. Due to these concerns, VHA only tracks A1c >9% (poor control).This gap led the DM-QUERI R&M Committee to recommend development of clinical indicators for potential over- and under treatment of glycemic control as a key strategic goal. Based upon our published work (continuous measures, glycemic regimen complexity and co-morbid conditions), we will work in partnership with VACO partners to refine and evaluate such indicators. Objectives: The long term objective of this proposal is to improve the appropriateness of glycemic management. Our specific aims are: (1) To develop technical specifications for clinical indicators of under- and overtreatment. a) To evaluate the impact of different inclusion and exclusion criteria on measure performance characteristics (e.g., sensitivity and specificity). b) To work with our VACO Program Office partners to finalize measure specification. (2) To assess variation at various VA organizational levels (CBOCs, facilities, and VISNS). 3) To work with our VACO Program Office partners to utilize clinical indicators for over- and undertreatment to inform quality improvement, surveillance and direct patient care. Methods: We will use Corporate Data Warehouse. All Veterans will be attributed to a facility or CBOC based upon primary care assignment; for unassigned Veterans, we will use the site where the majority of diabetes care was provided. The last A1c value within the time period of evaluation will be used as the primary analysis, and the first A1c as an alternative. Veterans will be eligible for the potential overtreatment measure if they are receiving sulfonylurea or insulin therapy and also meet inclusion criteria of age or significant co-morbid conditions. We will use three different thresholds reflecting increasingly tight glycemic control: <7%, <6.5%, and <6%. Veterans will be eligible for the under treatment measures if they are receiving a complex glycemic regimen (insulin or two or more oral agents) and do not have decreased life expectancy or serious comorbid illness. We will define undertreatment (which may vary by cohort) using a partial credit approach: A1c values >8.5% receive no credits (coded 1), full credit for <7.0% (or 7.5%) (coded 0), and partial credit for A1c values between 8.5% to 7.0% (or 7.5%) using our previously developed methodology of linear interpolation. Differences among facilities or CBOCs will be determined by assigning facilities within 5 ordinal categories based upon both Z score distribution (<=10% [5 Stars or best]; 10-33% [4 Stars]; 34-66% [3 Stars]; 67-90% [2 Stars], and >90% [1 Star] and statistical significance (P<0.05) for all categories (except the middle category (3 stars)) following NCQA criteria. Multi-level hierarchical linear modeling will estimate the amount of variation across different organizational units, as well as assess characteristics of Veterans who are at greatest risk.