An Operations Approach for Reducing Glycemic Variability: Evidence from a Primary Care Setting

Problem definition: Diabetes is a highly prevalent and expensive chronic disease that affects millions of Americans and is associated with multiple comorbidities. Clinical research has found long-term variation in a patient’s glycated hemoglobin levels to be linked with adverse health outcomes, such as increased hospitalizations. Consequently, there is a need for innovative approaches to reduce long-term glycemic variability and efficient ways to implement them. Academic/practical relevance: Although the operations literature has extensively explored ways to manage variability across patients, relatively little attention has been paid to within-patient variability. We draw on the management and healthcare literatures to hypothesize and then show that a key operational lever—continuity of care (CoC)—can be used to reduce glycemic variability, which in turn, improves patient health. In the process, we explore the moderating role of a key demographic characteristic: patient’s marital status. We also shed light on an important mechanism through which CoC reduces variability—adherence of patients to prescribed medications—thereby advancing the compliance literature. Academically, our study adds to the understanding of the importance of managing variability (via continuity in service) in settings where customers repeatedly interact with service providers. Methodology: We use a detailed and comprehensive data set from the Veterans Health Administration, the largest integrated healthcare delivery system in the United States. This permits us to control for potential sources of heterogeneity. We analyze more than 300,000 patients—over an 11-year period—with diabetes, a chronic disease whose successful management requires managing glycemic variability. We use an empirical approach to, first, quantify the relationship between CoC and glycemic variability and second, show how this relationship differs based on patient’s marital status. Third, we estimate the mediation effect of patients’ adherence to medications. Finally, we quantify how glycemic variability mediates the relationship between CoC and three important outcomes. Our findings are validated by extensive robustness checks and sensitivity analyses. Results: We find that CoC is related to reductions in glycemic variability, more so for patients who are not married. However, this reduction is not linear in continuity; we find evidence of curvilinearity but with a sufficiently high stationary point so that benefits almost always accrue, albeit at a diminishing rate. Additionally, we find that one mechanism through which CoC may reduce variability is through patients’ adherence to medications. We also find evidence of partial mediation for glycemic variability in the CoC outcomes process chain. Our counterfactual analysis reveals the extent of improvement that enhanced continuity can bring, depending on where it is targeted. Managerial implications: Identifying the process measures through which continuity of care reduces variability is of interest to practitioners and policy makers as it can help design appropriate policies and pathways in terms of both processes and staffing/work allocation.