Linking State Medicaid and Congenital Heart Surgical Registry Data: Building Capacity to Assess Disparities in Longitudinal Outcomes and Value for Children with Congenital Heart Disease

项目摘要 先天性心脏缺陷是美国最常见的和资源密集型的出生缺陷。 发病率和死亡率高的国家。据估计，它们影响了100多万美国儿童和140万 美国成年人，并导致约200，000生命年的损失和每年超过60亿美元的住院急性护理费用。 众所周知，在短期成果和资源利用方面存在着重大差异。我们已经证明 来自低收入社区的儿童住院死亡率的风险调整几率高出18%， 住院时间更长，需要的围手术期资源比高收入儿童多7% 社区，即使在控制了种族，公共与私人保险提供者的影响， 这些孩子最终接受手术修复的医院。长期成果研究和 卫生支出有限，造成卫生不平等的机制仍然不明。大于50%的 患有先天性心脏病的儿童可享受医疗补助。我们与纽约州政府合作， 并拥有纽约州15年来所有医疗补助患者的干净、有效数据。 我们已经开发了提取本地临床注册数据并将其链接到Medicaid文件的方法， 建立了一个由儿科心脏病专家、心脏外科医生、卫生服务研究人员组成的跨学科团队， 卫生经济学家和纽约卫生部高级领导，以确定医疗保健可及性的各个方面 这可以通过中央或州一级的干预措施来减少不平等。我们建议将 来自纽约州的儿科心脏外科临床登记数据、纵向医疗补助索赔、人口普查 统计局数据，地理编码数据，和国家死亡指数。我们将使用这些数据来完成 以下目的：1）我们将定义10年风险分层、多维结局（死亡率和发病率） 以及纽约州接受先天性心脏病手术的儿童的相关医疗费用; 2)我们将为患有先天性心脏病的儿童开发新的纵向风险模型， 健康的决定因素，以及3）我们将测试医疗保健可及性的维度作为健康的可修改驱动因素 纽约先天性心脏病儿童在医疗补助中的不平等。实现我们的目标将 1)为纵向成果和卫生支出建立全面的、基于人口的资源 研究，不仅包括住院患者数据，还包括门诊、急诊室、药房、康复， 家庭医疗保健、教育记录和社区一级的健康社会决定因素， 在纽约州接受先天性心脏病手术的儿童，2）产生一种调查方法， 适用于多个人群的长期结局和价值，3）评估通路结构， 健康的社会决定因素的可变中介，以及4）使我们能够将这些发现转化为政策 和医疗改革来减少健康不平等。

Project Summary Congenital heart defects are the most common and resource intensive birth defects managed in the United States with high morbidity and mortality. They are estimated to effect over 1 million US children and 1.4 million US adults and to result in ~200,000 life-years lost and >$6 billion in inpatient acute care costs per year. Significant disparities are known to exist in short-term outcomes and resource utilization. We have shown that children from low income neighborhoods have 18% higher risk-adjusted odds of in-hospital mortality, have 7% longer lengths-of-stay, and require 7% more perioperative resources than do children from higher income neighborhoods, even after controlling for the effects of race, public versus private insurance provider, and the hospitals at which these children ultimately receive surgical repair. Research on long-term outcomes and health expenditures is limited and mechanisms driving health inequities remain unknown. Greater than 50% of children with congenital heart disease are covered by Medicaid. We have partnered with the NY Department of Health and have clean, validated data for all Medicaid patient encounters over 15 years across NY State. We have developed methods of abstracting and linking locally-held clinical registry data to Medicaid files and have built an interdisciplinary team of pediatric cardiologists, cardiac surgeons, health services researchers, health economists, and NY Department of Health senior leadership to identify dimensions of healthcare access that could be targeted through center- or state-level interventions to reduce inequities. We propose linking pediatric cardiac surgical clinical registry data from across NY State, longitudinal Medicaid claims, Census Bureau data, geocoded data, and the National Death Index. We will use these data to accomplish the following Aims: 1) We will define 10-year risk-stratified, multi-dimensional outcomes (mortality and morbidities) and associated health expenditures for children undergoing congenital heart surgery across New York State; 2) we will develop novel longitudinal risk models for children with congenital heart disease that adjust for social determinants of health, and 3) we will test dimensions of healthcare access as modifiable drivers of health inequities among children in New York with congenital heart disease on Medicaid. Achieving our aims would 1) establish a comprehensive, population-based resource for longitudinal outcomes and health expenditure research, inclusive of not only in-patient data, but also out-patient, emergency room, pharmacy, rehabilitation, home healthcare, education records, and neighborhood-level social determinants of health for nearly half of all children undergoing congenital heart surgery in NY State, 2) generate a methodology for investigations on long-term outcomes and value applicable across multiple populations, 3) assess constructs of access as modifiable mediators of social determinants of health, and 4) position us to translate these findings into policy and care changes to reduce health inequities.