Implementation Science to Improve Cardiovascular Health: Leveraging EHR Systems to Advance Care of Resistant Hypertension

改善心血管健康的实施科学：利用 EHR 系统推进难治性高血压的护理

• 批准号: 10630490
• 负责人: Joseph Ebinger
• 金额: $ 4.84万
• 依托单位: CEDARS-SINAI MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-15 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10630490
• 关键词: Acute Renal Failure with Renal Papillary Necrosis; Address; Affect; Algorithms; American; Antihypertensive Agents; Automobile Driving; Award; Back; Bioinformatics; Biometry; Birth; Blood Pressure; Cardiology; Cardiovascular Diseases; Cardiovascular system; Caring; Characteristics; Child; Clinic; Clinical; Clinical Sciences; Communities; Conceptions; Data; Data Analyses; Data Set; Diagnostic; Disease; Dose; Drug Prescriptions; Echocardiography; Electronic Health Record; Enrollment; Ensure; Environment; Event; Fellowship; Foundations; Functional disorder; Funding; Future; Goals; Grant; Guidelines; Health; Health Policy; Health Services; Health Services Research; Health Technology; Health system; Heart; Heart failure; Hemorrhage; Human Resources; Hypertension; Individual; Infant Care; Informatics; Infrastructure; Institutes; Institution; Internal Medicine; Intervention; Left; Life; Link; Medical center; Medicine; Mentored Patient-Oriented Research Career Development Award; Mentors; Mentorship; Methodology; Minnesota; Morbidity - disease rate; Mus; Myocardial; Myocardial Infarction; NCI Scholars Program; Neonatal; Newborn Infant; Oregon; Outcome; Outcomes Research; Parents; Patient Care; Patients; Pattern; Pharmaceutical Preparations; Population; Productivity; Public Health Schools; Publications; Quality of Care; Research; Research Personnel; Research Project Grants; Research Training; Resistance; Resistant Hypertension; Resources; Risk; Role; Schedule; Source; Specialist; Stimulant; Stroke; Syncope; System; Therapeutic; Time; Training; Translational Research; United States; United States National Institutes of Health; Urban Population; Validation; Work; analytical tool; angiogenesis; base; blood pressure control; cardiovascular health; cardiovascular risk factor; care delivery; career; clinical application; clinical center; clinical decision support; cohort; computerized; cost; design; experience; falls; fascinate; flexibility; health care service organization; health care service utilization; health information technology; health management; hypertension control; hypertension treatment; hypertensive; implantation; implementation science; improved; individualized medicine; innovation; insight; interest; medical schools; medication compliance; medication nonadherence; mortality; professor; programs; provider behavior; scientific computing; skills; statistics; stem cells; success; support tools; tool

PROJECT SUMMARY Resistant hypertension (RH) doubles the risk for adverse cardiovascular outcomes compared to non-resistant hypertension. Defined as having uncontrolled high blood pressure despite the use of at least 3 antihypertensive medications or controlled blood pressure on at least 4 medications, RH is estimated to affect at least 20 million Americans. Importantly, true RH must be differentiated from pseudo-resistant hypertension (pseudo-RH), occurring when blood pressure remains elevated due to extrinsic factors such as suboptimal medication dosing, medication non-adherence, or white-coat effect. Inability to distinguish true RH from pseudo-RH, and tailor treatment accordingly, compounds the risks of overtreating pseudo-RH (e.g. syncope, falls, acute kidney injury) as well as undertreating true RH (e.g. stroke, myocardial infarction). Distinguishing true from pseudo-RH, however, is clinically difficult, in part given the complexities involved in capturing medication adherence patterns and confirming white-coat effect. Therefore, our overall objective is to determine whether electronic health record (EHR) based analytics and tools can be used to close persistent gaps in care for RH. The specific aims of the research project are to: (1) develop and validate a computerized algorithm that uses EHR data to identify RH and distinguish between true and pseudo-RH including its subtypes; (2) develop and optimize a CDS tool for aiding clinicians in the identification and management of apparent RH; and, (3) pilot the implementation of a CDS tool for facilitating care of RH in addition to pseudo-RH and its subtypes. This research promises to enhance our understanding of how health information technology can be leveraged to inform scientific discovery, while also driving high-value care for RH. The proposed work will be conducted as part of a K23 award program, designed provide the advanced research skills and experience needed for the PI to successfully pursue an independent academic career focused on: (i) optimizing value of care (i.e. improved quality at decreased cost); (ii) leveraging health information technology and clinically generated data to gain new insights into disease states; and, (iii) promoting innovation in care delivery using implementation science principles. These efforts will be supported by the outstanding research environment and infrastructure of Cedars-Sinai including the Smidt Heart Institute, the Biostatistics and Bioinformatics Research Center, and the Research Informatics and Scientific Computing Core. Given the strong mentoring, institutional, and infrastructure supports in place, this award is ideally designed to provide the experience needed to launch the PI in his career as an independent investigator and future leader in cardiovascular outcomes research. This addended proposal includes plans for continuity of these research aims during a critical life event for the PI. This calls for the addition of new personnel who will assist with data validation, as well as coordination with external partners. The PI’s institution has provided flexibility for the clinical schedules for both the PI and new personnel to ensure success of this proposal. Further, this proposal outlines mechanisms by which the PI will replace missed training with equivalent opportunities.

项目摘要 耐药性高血压（RH）使心血管不良结局的风险增加一倍 高血压。尽管使用至少3次降压，但被定义为无法控制的高血压 据估计，对至少4种药物的药物或控制血压至少会影响至少2000万种 美国人。重要的是，必须将真实的RH与抗伪高压（伪RH）区分开 当血压由于外部因素（例如次优药物剂量）引起的血压升高时发生， 药物不遵守或白大衣效应。无法区分真实RH和伪RH和量身定制 因此，治疗使过度治疗伪RH的风险（例如晕厥，瀑布，急性肾脏损伤） 以及未处理的真实RH（例如中风，心肌梗塞）。区分true和pseudo-rh， 但是，在临床上很难，部分鉴于捕获药物依从性模式所涉及的复杂性 并确认了白色大衣效应。因此，我们的总体目标是确定电子健康记录是否 （EHR）基于分析和工具可用于缩小RH护理的持续差距。特定目标 研究项目将要：（1）开发和验证使用EHR数据识别RH的计算机化算法 并区分真实和伪RH，包括其亚型； （2）开发并优化了用于 协助临床医生对明显RH的识别和管理； （3）试行实施 除伪RH及其亚型外，还可以支持对RH护理的CDS工具。这项研究有望增强 我们对如何利用健康信息技术的理解来告知科学发现，而 还为RH推动高价值护理。拟议的工作将作为K23奖项计划的一部分进行， 设计提供了PI成功追求PI所需的高级研究技能和经验 独立的学术职业专注于：（i）优化的护理价值（即以提高成本提高质量）； （ii）利用健康信息技术和临床生成的数据来获得对疾病的新见解 国家（iii）使用实施科学原则促进护理交付的创新。这些努力会 由Cedars-Sinai的杰出研究环境和基础设施提供支持，包括Smidt 心脏研究所，生物统计学和生物信息学研究中心以及研究信息学和科学学 计算核心。鉴于有强烈的心理，机构和基础设施支持，该奖项是 理想的设计旨在提供独立调查员职业生涯中PI发起PI所需的经验 以及心血管结局研究的未来领导者。此附加的建议包括有关连续性的计划 这些研究的目的是在PI的关键生活事件中。这要求增加新人员 协助数据验证以及与外部合作伙伴的协调。 PI的机构提供了 PI和新人员的临床时间表的灵活性，以确保该提案的成功。此外， 该提案概述了PI将用同等机会取代错过的培训的机制。