OBJECTIVES/SPECIFIC AIMS: We developed a multilevel hierarchical statistical model which describes the association of prophylactic interventions to patient PONV risk, and provides an intuitive summary for anesthesiologists to understand how well they are adhering to PONV guidelines. METHODS/STUDY POPULATION: Accepted PONV risk factors as well as preventative interventions to reduce the PONV risk, (e.g. total intravenous anesthesia or pharmacological prophylaxis) are retrieved from the electronic medical record (EMR). Risk is regressed against interventions. Fig 1, Panel A visualizes adherence for an individual provider by plotting anesthesia cases, with PONV risk in the x-axis and the number of interventions in the y-axis. Fig 1, Panel B shows a “Jitterplot”, jittering individual cases, which would otherwise plot onto the same coordinates (Panel A). The distribution of the number of interventions in each risk category is better summarized in Fig 1 Panel C by overlaying a violin plot onto the “Jitterplot”. Finally, a fitted regression line provides a summary measure for the individual provider’s risk-adjusted utilization of PONV prophylaxis in Fig 1, Panel D. The model can control for confounders and interactions, such as patient or procedure characteristics, such as supervision by attending physicians, institutional culture, and surgical procedure. RESULTS/ANTICIPATED RESULTS: Fig. 2, Panel A demonstrates good adherence. The provider responded to increased risk with additional interventions leading to a steep regression line. Less discriminate administration of prophylaxis is shown in Fig 2, Panel B. The graphical representation of our proposed measure of individual provider performance is intuitive, allowing us to compare adherence of two distinct groups of providers (light lines) and institutional averages (dark lines) as shown in Fig 2, Panel C. Controlling for known risk factors and potential confounders renders the assessment irrepudiable. The rigorous statistical approach allows for multi-level modeling and comparative effectiveness research, realistically evaluating process changes and interventions like CDS in the hierarchical structure of contemporary healthcare delivery. DISCUSSION/SIGNIFICANCE OF IMPACT: The strength of our novel measure of individual provider performance is its generalizability to other care settings, as well as the intuitive graphical representation of risk-adjusted individual performance. However, accuracy, precision and validity, sensitivity to system perturbations (like the implementation of CDS), and acceptance among providers remain to be evaluated. Fig 1. Risk-Adjusted Utilization of Antiemetic Prophylaxis Fig 2. Comparing Performance between Provider Groups