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Reducing Disparities among Kidney Transplant Recipients

减少肾移植受者之间的差异

基本信息

批准号：
9907867
负责人：
Andrew B Adams
金额：
$ 49.99万
依托单位：
EMORY UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-08-15 至 2022-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9907867
关键词：
Address African American Age Back Caring Characteristics Clinical Clinical Data Communities Computer software Data Data Mart Data Sources Databases Decision Support Systems Development Diabetes Mellitus Dialysis procedure Disadvantaged Educational workshop Electronic Health Record End stage renal failure Epidemiology Goals Hospitalization Hour Hypertension Infection Infrastructure Intervention Interview Kidney Transplantation Laboratories Length Medicare Methods Modeling Monitor Operative Surgical Procedures Outcome Patient-Focused Outcomes Patients Perioperative Population Poverty Predictive Analytics Provider Quality of life Race Research Research Personnel Resources Risk Risk Factors Socioeconomic Status Statistical Methods Statistical Models Structure Techniques Time Transplant Recipients Transplantation Transplantation Surgery care providers clinical care clinical decision support clinical decision-making clinical encounter community based participatory research comparative cost effectiveness dashboard data visualization design disparity reduction health management high risk hospital readmission improved low socioeconomic status meetings multidisciplinary national surveillance novel patient oriented patient stratification population health post-transplant prediction algorithm predictive modeling prevent programs psychosocial risk prediction model social surveillance data time use transplant centers

项目摘要

Abstract: Disparities exist in access and outcomes of kidney transplantation. More than half of patients are hospitalized in the year after transplantation, and these patients are more likely AA and have lower socioeconomic status. Several studies have identified risk factors for hospital admission using traditional statistical methods, but models have been limited by moderate predictive accuracy, the use of static (rather than dynamic) models, and the use of administrative data that may not capture the changing risk factors pre- to post-transplant. The overall goal of this research is to develop and validate rigorous, dynamic risk prediction models, integrate these models within a clinician dashboard, and develop potential interventions to address surgical disparities in hospitalization following kidney transplantation. Our specific aims are 1) To develop and validate predictive models to identify transplant recipients at high risk of hospitalization following transplant; 2) To use a community-based participatory research approach to build an electronic hospitalization risk dashboard that will aid in clinical decision-making and guide the use of scarce resources for patients at high risk for hospitalization post-transplant. The overall impact of this proposal is to improve transplant outcomes and reduce disparities among a primarily AA ESRD population in the Southeastern US.

摘要：肾移植的途径和结果存在差异。超过一半的患者在移植后一年住院，这些患者更有可能是再障并拥有较低的社会经济地位。几项研究已经确定了医院的风险因素使用传统的统计方法录取，但模型受到了适度的限制预测准确性，静态(而非动态)模型的使用，以及管理数据可能没有捕捉到移植前到移植后不断变化的风险因素。这个本研究的总体目标是开发和验证严格、动态的风险预测模型，将这些模型集成到临床医生控制面板中，并开发潜力解决肾移植后住院期间外科差异的干预措施。我们的具体目标是1)开发和验证识别移植的预测模型移植后住院风险高的受者；2)使用基于社区的参与式研究方法，以建立一个电子住院风险仪表盘，将协助临床决策并指导对高危患者使用稀缺资源供移植后住院治疗。这项提议的总体影响是改善移植东南部以AA为主的ESRD人群的结果和缩小差距我们。