Modifiable factors in emergent presentation of potentially elective general surgical disease for patients who are insured or insurance-eligible

项目总结/摘要 我们提出的研究的总体目标是了解为什么拥有医疗保险（或资格） 保健覆盖率）不足以使人们平等获得选择性外科护理。尽管成功 通过医疗补助扩张和平价医疗法案（ACA）扩大覆盖面的努力， 外科护理通常直到它成为紧急情况时才得到解决。这些患者往往来自 弱势群体，他们不仅更经常地进行急诊普通外科手术（EGS）， 结果更糟，成本更高。在美国导致这种表现的差异 在与保险状况、种族和收入的整体关系方面已经得到了很好的描述，但更深入的数据 迫切需要进行收集和分析，以确定可以为干预措施提供信息的可变因素 在这些人群中，特别是在医疗保健覆盖率方面， 即使在拥有全民医疗保健系统的国家，人们在如何能够真正实现健康方面也存在差异。 获取这些服务。 我们最初研究这个问题的背景下，紧急胆囊切除术，我们最常见的 EGS疾病的表现。我们发现缺乏医疗保健覆盖并不是一个主要因素;事实上，86% 我们的病人有某种类型的保险（29%的私人，57%的公共），许多其他社会因素导致了一个 紧急手术。我们现在试图扩展和探索这一点，详细的其他EGS条件定义 由美国创伤外科协会（AAST）使用多相混合方法进行。 我们将1）确定紧急表现的可改变因素，并探索进展轨迹， 在融合混合方法设计中使用计费数据和EHR的择期手术与急诊手术， 将定量变量与定性叙述数据相结合，2）识别和量化其他可修改的 从患者角度考虑的因素，这些因素在使用 探索性序贯设计，使用确定的领域进行系统综述和荟萃分析， 定量数据，以及3）确定哪些可修改的因素或确定的因素将对 使用马尔可夫模型的未来干预策略。 该提案将利用我们以新颖的方式将来自多个来源的数据联系起来的能力， 处于医疗补助扩张状态的普通外科人群，以及在其领域具有以下专长的合作研究者： 纵向数据建模和混合方法研究。利用这些数据，我们可以建模并了解 尽管覆盖率增加，但影响了获得选择性外科护理的能力的持续差异， 并预测哪些因素对差异贡献最大，从而具有最大影响的潜力。 通过确定可采取行动的可改变因素，我们最终将为有效的干预策略提供信息， 择期手术疾病的紧急表现。

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 intervention strategies to prevent emergent presentation of elective surgical disease.