Anticipated Impact on Veterans Health Care: Nearly 25% of VA users are diagnosed with diabetes. Diabetes is the leading cause of blindness, end stage renal disease, amputations and a significant cause of hospitalizations for myocardial infarction (MI) and stroke. Mortality rates among veterans with diabetes are twice as high compared to veterans without diabetes. In 2012, diabetes was estimated to cost $176 billion in direct medical and indirect costs. These health and cost implications make the effective management of diabetes a policy priority for healthcare providers and policymakers nationwide. This proposal will move beyond hemoglobin A1c (A1c) control to prevent diabetes complications and assess the role of A1c variability. Project Background: A major focus of diabetes management is glucose control, since persistently elevated A1c levels predict adverse health outcomes including microvascular complications. But lowering A1c to moderately stringent targets (<7%) could increase risks of macrovascular disease or mortality. There are increasing data showing that glucose variability plays a significant role in predicting risk of complications. Longer term variability as reflected in A1c fluctuations over time has been linked to risk of both microvascular and macrovascular complications. We have shown that among Veterans with diabetes, increasing A1c variability over a 3 year period is independently associated with risk of MI, ambulatory care sensitive condition hospitalization, and mortality. We wish to further study this for its potential clinical application by developing and validating a novel clinical measure of A1c variability that is unique to each patient. Project Objectives: We propose an observational study to (a) construct statistical measures and determine predictors of A1c variability, (b) develop and validate more intuitive clinical measures of A1c variability (i.e. % time-in-range), and (c) assess the relationship between these measures of A1c variability and adverse health outcomes in patients with diabetes. Specific objectives include: Objective 1. Construct statistical measures and determine the predictors of A1c variability. Objective 2. Develop and validate a more intuitive clinical measure of A1c variability defined as A1c time-in- range. We will calculate the percentage of days an individual has an A1c level in the appropriate range, based on clinical parameters and the VA-DoD clinical practice guidelines. Objective 3. Estimate the relationship between A1c variability, % time-in-range, and adverse health outcomes? including micro- and macrovascular complications and mortality. Project Methods: The proposed project is a retrospective observational study of secondary data from patient- level administrative and claims data from VA and Medicare. Utilization and pharmacy files will be used to determine patients diagnosed with diabetes between 2004 and 2015. A three-year baseline period will be used to calculate the individual A1c variability measure of coefficient of variation and a %time in range measure. The %time in range measure will be the percentage of days an individual has an A1c level in the appropriate range based on VA-DoD clinical practice guidelines. Patients will be assigned to the provider that orders the most A1c tests for them during the baseline period and provider A1c variability measures will be calculated. Provider A1c variability will be used as an instrumental variable to predict individual A1c variability, controlling for process quality (Objective 1, 2). Residuals will be captured from the equations estimated in these two objectives for Objective 3 to measure the effect of individual A1c variability on health outcomes. Significant relationships will then be further validated in a VA-Medicaid population.
Data suggest that long-term glucose variability may play a significant and previously overlooked role in predicting risk of microvascular and macrovascular complications. Prior studies have failed to control for selection bias and cannot determine whether the relationship between A1c variability and adverse health outcomes is causal. The proposed study advances understanding of the effect of A1c variability on health outcomes in three key ways: (1) by developing a novel clinical measure of A1c variability (i.e. time in range) that will help clinicians tailor diabetes care based on a patient?s unique goals of care, (2) by studying the effects of A1c variability and time in range on health outcomes in Veterans who are dually enrolled in VA and Medicare, using advanced econometric techniques to stringently control for selection bias and (3) by validating the effects of A1c variability and time in range on health outcomes in a VA-Medicaid sample.
