Measuring Progressive Independence With the Resident Supervision Index: Theoretical Approach

Abstract

Graduate medical education is based on an on-the-job training model in which residents provide clinical care under supervision. The traditional method is to offer residents graduated levels of responsibility that will prepare them for independent practice. However, if progressive independence from supervision exceeds residents' progressive professional development, patient outcomes may be at risk. Leaders in graduate medical education have called for "optimal" supervision, yet few studies have conceptually defined what optimal supervision means and whether optimal care is theoretically compatible with progressive independence, nor have they developed a test for progressive independence. This research develops theory and analytic models as part of the Resident Supervision Index to quantify the intensity of supervision. We introduce an explicit set of assumptions for an ideal patient-centered theory of optimal supervision of resident-provided care. A critical assumption is that informed attending staff will use available resources to optimize patient outcomes first and foremost, with residents gaining clinical competencies by contributing to optimal care. Next, we derive mathematically the consequences of these assumptions as theoretical results. Under optimal supervision, (1) patient outcome is expected to be no worse than if residents were not involved, (2) supervisors will avoid undersupervising residents (when patients are at increased risk for poor outcomes) or oversupervising residents (when residents miss clinical opportunities to practice care), (3) optimal patient outcomes will be compatible with progressive independence, (4) progressive development can be inferred from progressive independence whenever residents contribute to patient care, and (5) analytic models that test for progressive independence will emphasize adjusting the association between length of graduate medical education training and supervision for case complexity and clinic workload, but not patient health outcomes. An explicit theoretical framework is critical to measure scientifically progressive independence from supervision using graduate medical education data.