Abstract: In the face of limited health care resources, waiting time often serves as a rationing mechanism in health systems around the world. We evaluate the efficiency and equity consequences of rationing surgical care via queues. Focusing on the U.S. private insurance market, we first develop a new measure of wait time that captures the full patient trajectory---including visits for primary care, laboratory testing, and medical imaging---along the path to surgery. Exploiting exogenous variation due to congestion within a patient's insurance network, we show that patients who wait a month more spend 1% more on hospital care, are 1.1% more likely to be readmitted to a hospital, and fill 2.6% more opioid prescriptions in the six months following a surgery. We further quantify misallocation of wait times relative to the planner's ideal. We identify heterogeneous effects of waiting and show that those patient groups who suffer the highest costs from delay do not uniformly experience shorter waits. In our setting, positive prioritization---say, by providing physicians information on the treatment effects of waiting by patient type---can both reduce insurer spending on hospital care and improve patient health outcomes.