How Continuity in Service Impacts Variability: Evidence from a Primary Care Setting
45 Pages Posted: 23 Aug 2019 Last revised: 10 Feb 2020
Date Written: August 20, 2019
Abstract Variability plays an important role in service operations, where customers repeatedly interact with providers. This raises three vital questions for service design. First, what role does continuity in service play in managing variability in intermediate components of a service delivery process? Second, how critical is the role of variability in determining final outcomes? Third, since customers play an integral role in service operations, what part do they play in mitigate this variability? These questions are particularly important in healthcare services, where patients with chronic conditions visit primary care offices repeatedly. Therefore, we investigate this topic in the context of management of diabetes, a chronic disease. We use a detailed and comprehensive dataset 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 eleven-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 continuity of care and glycemic variability, and, second, to show that glycemic variability mediates the relationship between continuity of care and five important health outcomes. Finally, we estimate the mediation effect of patients' adherence to medications. We find that continuity of care is related to reductions in glycemic variability. 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 glycemic variability (partially) mediates the relationship between continuity of care and patient outcomes. Additionally, we find that one mechanism through which continuity may reduce variability is through patients' adherence to medications. Our findings are validated by extensive robustness checks and sensitivity analyses .Our paper is of interest to managers and decision-makers as it brings attention to within-individual variability that has received relatively little attention within the operations literature. Identifying the process measures through which continuity of care improves outcomes and reduces variability in them is of interest to practitioners and policymakers as it can help in designing appropriate policies and pathways, both in terms of processes and staffing/work allocation.
Keywords: Continuity of Care, Healthcare Operations, Learning, Empirical Operations
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