EHR-Based Strategies to Improve Outcomes in Familial Hypercholesterolemia

基于 EHR 的改善家族性高胆固醇血症预后的策略

• 批准号: 9389934
• 负责人: Iftikhar J Kullo
• 金额: $ 52.01万
• 依托单位: MAYO CLINIC ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-07-01 至 2021-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9389934
• 关键词: Academy; Address; Algorithms; Atherosclerosis; Awareness; Benefits and Risks; Caring; Cholesterol; Clinic; Clinical; Clinical Management; Communities; Computerized Medical Record; County; Data; Data Set; Decision Aid; Decision Making; Detection; Diagnosis; Disease; Early Diagnosis; Early treatment; Electronic Health Record; Epidemiology; Europe; Familial Hypercholesterolemia; Family; Family history of; Family member; Genetic screening method; Genomics; Goals; Healthcare; Healthcare Systems; Hereditary Disease; Heritability; Individual; Institutes; LDL Cholesterol Lipoproteins; Label; Laboratories; Learning; Link; Lipids; Low-Density Lipoproteins; Manuals; Medical Records; Medicine; Methods; Minnesota; Morbidity - disease rate; Myocardial Infarction; Natural Language Processing; Outcome; Patients; Performance; Pharmaceutical Preparations; Pharmacotherapy; Phenotype; Plasma; Population Study; Preclinical Drug Evaluation; Predictive Value; Prevalence; Prevalence Study; Primary Prevention; Provider; Public Health; Recommendation; Recording of previous events; Records; Reporting; Research; Research Infrastructure; Resources; Risk; Structure; Test Result; Time; Work; World Health Organization; Xanthomas; adverse outcome; base; cardiovascular risk factor; case-based; epidemiology study; evaluation/testing; implementation science; improved; improved outcome; inhibitor/antagonist; innovation; lifetime risk; mortality; novel therapeutics; point of care; population based; precision medicine; premature; prevent; programs; screening; shared decision making; sudden cardiac death; tool

PROJECT SUMMARY/ABSTRACT Familial hypercholesterolemia (FH) is a relatively common genetic disorder characterized by elevated plasma low-density lipoprotein cholesterol (LDL-C) and a dramatically increased lifetime risk for premature atherosclerotic cardiovascular disease (ASCVD). Available data suggest substantial under treatment of individuals with FH, and it is estimated that <5% of prevalent FH cases in the US are diagnosed and treated. The proposed research will develop electronic health record (EHR)-based strategies to reduce mortality and morbidity from FH. We will develop and validate a phenotyping algorithm for rapid and efficient identification of FH cases thereby enabling EHR-based surveillance of FH. We will deploy the phenotyping algorithm in the population-based setting of Olmsted County, Minnesota, to estimate prevalence and provide hitherto unavailable data on awareness, detection and control of FH. We will develop CDS to help care providers manage FH patients and an FH-specific decision aid to facilitate shared decision making related to lipid-lowering therapy and screening of family members. To accomplish these goals, we will leverage the following resources: a) the electronic phenotyping expertise available in the electronic Medical Records and Genomics (eMERGE) network; b) the Rochester Epidemiology Project (REP), that links medical records of Olmsted County MN residents thereby capturing nearly all health care delivered to residents of the community; and c) expertise in developing and deploying CDS in the EHR and in creating decision aids for disclosing cardiovascular risk and the benefits of lipid-lowering drugs. Our specific aims are: Aim 1. Develop and validate an electronic phenotyping algorithm to rapidly identify FH cases from the EHR. Aim 2. Conduct an e- epidemiology study to obtain hitherto unknown data regarding prevalence, awareness, detection, control of FH in a population-based setting in the US. Aim 3. a) Develop EHR-based tools to help care providers manage FH and facilitate shared decision making and cascade screening and b) assess outcomes after implementation of CDS and decision aid. The proposed research will enable rapid identification of FH in EHRs, provide hitherto unavailable data on the burden of FH in the community, facilitate EHR-based strategies for early detection, increase awareness of FH among care providers, provide guidance for management of FH at point of care and help both patients and providers make informed decisions about drug therapy and screening of family members. These are critical steps for early detection and treatment of FH to reduce the burden of premature ASCVD due to this condition.

项目总结/摘要 家族性高胆固醇血症（FH）是一种相对常见的遗传性疾病，其特征是血浆胆固醇水平升高， 低密度脂蛋白胆固醇（LDL-C）和早产儿的终身风险显著增加 动脉粥样硬化性心血管疾病（ASCVD）。现有数据表明， 据估计，在美国，<5%的流行FH病例得到诊断和治疗。 拟议的研究将开发基于电子健康记录（EHR）的策略，以降低死亡率， FH的发病率。我们将开发和验证一种表型分析算法，用于快速有效的识别 从而实现基于EHR的FH监测。我们将在 明尼苏达州奥姆斯特德县的人口为基础的设置，以估计患病率，并提供迄今为止 没有关于FH的感知、检测和控制的数据。我们将开发CDS以帮助护理提供者 管理FH患者和FH特定的决策辅助工具，以促进与降脂治疗和家庭成员筛查相关的共同决策。为了实现这些目标，我们将利用以下方面 资源：a）电子病历和基因组学中可用的电子表型鉴定专业知识 （eMERGE）网络; B）罗切斯特流行病学项目（REP），将奥姆斯特德的医疗记录 MN县居民因此获得了向社区居民提供的几乎所有卫生保健;以及c） 在EHR中开发和部署CDS以及为披露创建决策辅助方面的专业知识 心血管风险和降脂药物的益处。我们的具体目标是：目标1。开发和验证 一种电子表型分析算法，用于从EHR中快速识别FH病例。目标2.进行电子- 流行病学研究，以获得迄今未知的关于FH的患病率、知晓率、检测和控制的数据 in a population-based人口为基础的setting设置in the US.目标3. a）开发基于EHR的工具来帮助护理提供者管理FH 并促进共同决策和级联筛选，以及B）评估实施后的成果 CDS和决策辅助。拟议的研究将使快速识别FH的EHR，提供迄今为止， 关于社区FH负担的不可用数据，促进基于EHR的早期检测策略， 提高护理提供者对FH的认识，提供护理点FH管理指南， 帮助患者和提供者就药物治疗和家庭筛查做出明智的决定 成员这些都是早期发现和治疗FH的关键步骤，以减少过早死亡的负担。 ASCVD由于这种情况。