Quantifying Compliance to the New 2017 Hypertension Treatment Guidelines and Investigating the Association Between Guideline Compliance and Patients' Trajectory of Blood Pressure

项目总结/摘要 血压（BP）达到140/90 mm Hg会使心血管疾病（CVD）的风险增加一倍， 高血压每年高达510亿美元。尽管存在巨大的风险和成本， 在高血压患者中，不到一半（48.3%）的高血压患者的血压（BP）得到控制。 美国的临床试验表明，使用以下药物可以实现高血压控制率（高达85%） 目前可用的疗法，并严格遵循推荐的治疗方案。这表明 高比例的血压不受控制可能是由于治疗不积极，随访不佳， 使用更少或更少有效的药物。最近发布了2017年高血压管理指南， 将开始用药的阈值和血压不受控制的定义降低至血压≥130/80 mm Hg (from 140/90）的CVD或CVD风险较高的患者。这就要求医生改变他们的 传统的高血压管理，并可能恶化已经很低的依从率（范围25-65%）， 高血压治疗指南。此外，以前的研究关于遵守 旧的高血压治疗指南由于未能评估 高血压护理，如合并症、随访和实验室评估;以及使用主观 评估，如医生自我报告。电子健康记录（EHR）的广泛采用 技术和EHR数据中存在的重要患者信息提供了一个绝佳的机会， 客观评价高血压护理的几个方面，如处方药物，实验室检查， 手术顺序、达到的血压水平、随访监测检查、人口统计学和共病 信息.因此，我们建议使用西北医药企业数据仓库（NMEDW） - 290万患者健康信息的综合EHR数据库，以1）评估对 2017年高血压管理指南发布5年（2018-2022年）; 2）调查是否 患者的年龄、种族、体重指数、糖尿病史、CVD、慢性肾病、药物依从性， 健康保险和常规医生的存在以及医生专业可以预测对 新的治疗指南;和3）检查依从性水平与2017年 高血压治疗指南和5年（2019-2023年）的前瞻性患者BP轨迹。新 确诊的高血压患者的人口统计学资料、BP、药物、实验室检查结果、随访访视和共病 将从NMEDW评估条件，并将与基于2017年制定的标准进行比较 高血压治疗指南，以量化对指南的依从性。拟议的研究提供了 候选人有机会学习EHR数据挖掘技能，以评估遵守新的 高血压治疗指南和患者血压轨迹，并确定这种依从性的预测因素，作为第一个 在设计未来的有针对性的干预措施，以加强准则的遵守和BP控制的步骤。

Project Summary/Abstract Blood pressure (BP) of ³140/90 mm Hg doubles the risk of cardiovascular diseases (CVD) and the total cost of hypertension reaches as high as $51 billion per year. Despite the enormous risk and cost associated with hypertension, less than half (48.3%) of hypertensive patients have a controlled blood pressure (BP) in the United States. Clinical trials demonstrated that a high rate of BP control (up to 85%) can be achieved with currently available therapies and strictly following recommended treatment protocols. This suggests that a higher proportion of uncontrolled BP could be explained by less aggressive treatment, poorer follow-up, and use of fewer or less effective drugs. The 2017 guideline for high BP management was recently published and lowered the threshold for the initiation of medication and definition of uncontrolled BP to BP ≥130/80 mm Hg (from 140/90) for patients with CVD or higher risk of CVD. This challenges physicians to change their traditional hypertension management and could worsen the already low rate of compliance (range 25-65%) to hypertension treatment guidelines. Furthermore, conclusions from previous studies regarding compliance to older hypertension treatment guidelines were compromised due to failure to evaluate multiple aspects of hypertension care, such as comorbidities, follow-up and laboratory assessments; and use of subjective assessment such as physician self-report. The wide-spread adoption of electronic health record (EHR) technology and the vital patient information present in EHR data provide an exceptional opportunity to objectively evaluate several aspects of hypertension care, such as medications prescribed, laboratory procedures ordered, BP level achieved, follow-up monitoring examinations, demographic and comorbid information. We, therefore, propose to use the Northwestern Medicine Enterprise Data Warehouse (NMEDW) – an integrated EHR database of health information from 2.9 million patients to 1) assess compliance to the 2017 hypertension management guidelines for 5 years since its release (2018-2022); 2) investigate whether patient’s age, race, body mass index, history of diabetes, CVD, chronic kidney disease, medication adherence, presence of health insurance and regular physician, and physican speciality predict level of compliance to the new treatment guideline; and 3) examine the association between level of compliance to the 2017 hypertension treatment guidelines and prospective patient BP trajectory over 5 years (2019-2023). Newly diagnosed hypertensive patients’ demographics, BP, medications, lab results, follow-up visit, and comorbid conditions will be assessed from the NMEDW and will be compared to criteria developed based on the 2017 hypertension treatment guidelines to quantify compliance to the guideline. The proposed study provides the candidate an opportunity to learn EHR data-mining skills to assess association between compliance to the new hypertension treatment guideline and patient BP trajectory and to identify predictors of this compliance, as a first step, in designing future targeted interventions to enhance guideline compliance and BP control.