Measuring continuity in primary care: how it is done and why it matters

Abstract

Abstract Continuity of care (COC) is a foundational element of primary care and is associated with improved patient satisfaction and health outcomes and decreased total cost of care. The patient–physician relationship is highly valued by both parties and is often the reason providers choose to specialize in primary care. In some settings, such as outpatient residency clinics, however, patients may only see their primary care provider (PCP) 50% or less of the time. Considering the many benefits of COC for patients and providers, there is a clear need for us in primary care to understand how to compare different COC measures across studies and how to choose the best COC measure when conducting quality improvement efforts. However, at least 32 different measures have been used to evaluate COC. The manifold variations for measuring COC arise from data source restrictions, purpose (research or clinical use), perspective (patient or provider), and patient visit frequency/type. Key factors distinguishing common COC formulas are data source (e.g. claims data or electronic medical records), and whether a PCP is identifiable. There is no “right” formula, so understanding the nuances of COC measurement is essential for primary care research and clinical quality improvement. While the full complexity of COC cannot be captured by formulas and indices, they provide an important measure of how consistently patients are interacting with the same provider.