PROJECT SUMMARY/ABSTRACT The overall goal of our proposed research is to understand why having health care coverage (or eligibility for health care coverage) is not sufficient to allow equal access to elective surgical care. Despite successful efforts to expand coverage through Medicaid expansion and the Affordable Care Act (ACA), potentially elective surgical care is often not addressed until it becomes an emergency. These patients tend to come from vulnerable populations, who not only present more often for Emergency General Surgery (EGS), but experience worse outcomes and greater costs. The disparities leading to this presentation in the United States have been well-described in terms of overall relationship to insurance status, race and income, but deeper data collection and analysis are desperately needed to identify modifiable factors that can inform interventions around decreasing emergent presentation in these populations, particularly in regard to health care coverage. Even in countries with Universal Health Care systems, disparities are noted in how people are able to actually access those services. We initially studied this problem in the context of emergent cholecystectomy, one of our most common presentations of EGS disease. We found that lack of health care coverage was not a major factor; in fact, 86% of our patients had some type of coverage (29% private, 57% public), and many other social factors led to an emergency operation. We now seek to expand and explore this in detail for the other EGS conditions defined by the American Association for the Surgery of Trauma (AAST) using a multiphase mixed method approach. We will 1) identify modifiable factors for emergent presentation and explore the trajectory of progression to elective versus emergency surgery using billing data and EHR in a convergent mixed-methods design, combining quantitative variables with qualitative narrative data, 2) identify and quantify additional modifiable factors from the patient perspective that are not available in clinical or administrative datasets using an exploratory sequential design, using identified domains to conduct systematic review and meta-analysis for quantitative data, and 3) determine which modifiable factor or factors identified will have the greatest impact for future intervention strategies using Markov modeling. This proposal will leverage our ability to link data from multiple sources in novel ways, our diverse, robust general surgery population in a Medicaid expansion state, and Co-Investigators who are expert in their fields of longitudinal data modeling and mixed methods research. With this data we can model and understand what influences the persistent disparity in the ability to access elective surgical care despite increased coverage, and predict which factors contribute the most to the disparities and thus hold potential for the greatest impact. By identifying actionable modifiable factors, we will ultimately inform effective...