The Intersection of Personalized Medicine and Implementation Science to Improve Healthcare Utilization in Cirrhosis

摘要 肝硬变的管理是资源密集型的，而且不成比例地增加了 医疗保健。住院护理是这一负担中相当大的一部分，近30%的住院患者导致 在30天内再次入院。不幸的是，基于卫生系统的干预措施成功地减少了 重新入院率面临着传播的重要障碍。为了成功地提供医疗服务，重新设计以 发生时，重要的是以正确的患者为目标并提供量身定制的干预措施。对患者进行精确分割 确定高利用率的人口是重要的第一步。当前的重新接纳预测模型基于 传统病历数据在肝硬变中表现较弱。相反，我们新奇的初步数据与 患者报告结果测量(PROM)到未来医疗保健利用(HCU)。此外，私家侦探的导师已经 显示了当医疗保健系统将实时专业跟踪与基于证据的管理相结合时 算法和面向患者的健康工具，可以减轻HCU的负担。根据这些数据，这项提案将 首先测试总体假设，即基于电子病历和非电子病历、以患者为中心的测量相结合 将更好地识别肝硬变患者的高利用率。更进一步，这项提议还将检验这样一个假设： 成功的、可扩展的护理模式可以通过适应健康状况转变为高危肝硬化症患者 技术工具。我们将通过三个目标和一个稳健的培训计划来检验这些假设。具体目标#1将 通过现有风险模型评估HCU预测，然后利用全州范围的数据源进一步细化风险 使用肝病特定数据和人群健康数据进行预测。具体目标#2将进一步校准预测 在住院肝硬变患者的前瞻性队列中使用PROMS的未来HCU的可能性。有能力识别一个 来自SA#S 1-2的肝硬化症弱势群体，具体目标#3将建立在共同导师的基础上(布斯塔尼博士) 通过改编《脑部护理笔记》，手机健康，成功改善痴呆症人群的HU 旨在支持实时症状跟踪、护理人员支持和参与以减少HCU的应用程序 在那些有肝硬化症的人身上。此外，在完成这些目标的同时，PI还将完成3个跨学科培训 目标：1)发展先进的生物统计和大数据管理和分析技能；2)获得经验 在PROM研究所需的方法论方面；3)获得医疗保健实施科学方面的专业知识 所有研究都在一个由拟议领域的国家专家领导的强有力的指导小组的指导下进行。 这些目标的成功完成将支持未来R01级干预的设计，该干预提供 针对肝硬变慢性病管理的创新、可扩展的解决方案。

ABSTRACT Management of cirrhosis is resource-intensive and disproportionately contributes a growing burden on healthcare. Inpatient care is a sizeable portion of this burden where nearly 30% of admissions result in a readmission within 30 days. Unfortunately, health system-based interventions successful in reducing readmission rates face important barriers to dissemination. In order for successful health delivery redesign to occur, it is important to target the right patient and deliver a tailored intervention. Precisely segmenting patient populations to identify high utilizers is an important first step. Current readmission prediction models based on traditional medical records data have weak performance in cirrhosis. Instead, our novel preliminary data correlate patient reported outcome measures (PROMs) to future healthcare utilization (HCU). Further, the PI’s mentor has shown that when healthcare systems combine real-time PRO tracking with evidence-based management algorithms and patient-facing health tools, HCU burden can be reduced. Based on these data, this proposal will first test the overarching hypothesis that a combination of EHR-based and non-EHR, patient-centered measures will better identify high utilizers in cirrhosis. Taken a step further, this proposal will also test the hypothesis that successful, scalable models of care can be translated to high-risk cirrhotics through adaptation of a health technology tool. We will test these hypotheses via three aims and a robust training plan. Specific Aim #1 will assess HCU prediction by existing risk models and then utilize a state-wide data source to further refine risk prediction with liver disease-specific and population health data. Specific Aim #2 will further calibrate prediction of future HCU using PROMs in a prospective cohort of hospitalized cirrhotics. With the ability to identify a vulnerable group of cirrhotics from SA#s 1-2, Specific Aim #3 will build on the co-mentor’s (Dr. Boustani) success in improving HCU in dementia populations by adapting Brain Care Notes, a mobile phone health application designed to support real-time symptom tracking, care-giver support and engagement to reduce HCU in those with cirrhosis. Further, while completing these aims, the PI will accomplish 3 interdisciplinary training goals: 1) develop advanced biostatistical and big data management and analysis skills; 2) acquire experience in methodologies needed for the study of PROMs; 3) gain expertise in healthcare implementation science research all under the guidance of a robust mentorship team led by national experts in the proposed fields. Successful completion of these aims will support the design of a future R01-level intervention that provides innovative, scalable solutions for the chronic disease management in cirrhosis.