Outpatient Worsening Heart Failure in an Integrated Health Care Delivery System: An Innovative Approach to Characterizing a Novel Clinical Entity

综合医疗服务系统中门诊患者心力衰竭恶化：表征新临床实体的创新方法

• 批准号: 10685420
• 负责人: Andrew Patrick Ambrosy
• 金额: $ 19.21万
• 依托单位: KAISER FOUNDATION RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10685420
• 关键词: Acute; Address; Affordable Care Act; Algorithms; Award; Board Certification; California; Cardiac; Caring; Characteristics; Clinical; Clinical Trials; Computer software; Congestive Heart Failure; Data; Data Sources; Devices; Disease; EHR research; Environment; Epidemiology; Event; Funding; Future; Goals; Guidelines; Health Policy; Health Services; Health system; Heart failure; Hospitalization; Hospitals; Impairment; Incentives; Incidence; Institution; Integrated Delivery of Health Care; International; K-Series Research Career Programs; Knowledge; Learning; Location; Machine Learning; Manuals; Medical; Mentors; Mentorship; Methodology; Morbidity - disease rate; Natural History; Natural Language Processing; Outcome; Outpatients; Patient Admission; Patient Care; Patients; Pharmaceutical Preparations; Physicians; Pragmatic clinical trial; Public Health; Recommendation; Recording of previous events; Reporting; Research; Research Methodology; Research Personnel; Research Project Grants; Research Proposals; Resources; Risk; Risk Adjustment; Science; Scientist; Series; System; Training; United States National Institutes of Health; Work; adjudication; analytical method; clinical encounter; clinical risk; cohort; deep learning; design; electronic health record system; evidence base; experience; health related quality of life; high risk; hospital readmission; implementation science; improved; innovation; interest; machine learning algorithm; mortality; novel; programs; prospective; readmission rates; skills; standard of care; success; treatment pattern; trend; unstructured data

PROJECT SUMMARY/ABSTRACT Although the management of ambulatory heart failure (HF) has been revolutionized by evidence-based drug and device therapies, there has been no such parallel progress in the care of patients admitted for worsening HF (WHF). To incentivize health systems to reduce 30-day readmissions, the Affordable Care Act (ACA) launched the Hospital Readmission Reduction Program (HRRP) in 2012, which penalizes hospitals financially if they have higher than expected risk-adjusted 30-day readmission rates for conditions including HF. Although the HRRP has modestly reduced readmissions, this program has had the unintended consequence of shifting a significant fraction of HF-related care to the outpatient setting. Thus, there is a growing interest in the field to disentangle WHF from location of care and move away from using hospitalization as a surrogate for acute decompensated HF. However, little is known about the epidemiology, clinical profile, treatment patterns, and/or outcomes of outpatient WHF. In addition, while the overall survival of ambulatory HF patients has improved dramatically, guideline-directed medical therapy (GDMT) has had minimal impact on impairments in health- related quality of life (HRQOL). Despite this reality, there are few real-world data sources available to describe the trajectory of HRQOL in the ambulatory setting. To address these critical knowledge gaps, we propose (1) to systematically describe the contemporary epidemiology, clinical characteristics, treatment patterns, and outcomes associated with outpatient WHF and (2) to evaluate the impact of an episode of outpatient WHF on generic and disease-specific HRQOL in the context of a fully integrated health care delivery system. The first objective will leverage observational data from a large, state-of-the-art, and validated electronic health record (EHR) system and machine learning algorithms for natural language processing (NLP) to systematically ascertain and comprehensively characterize episodes of outpatient WHF. The second objective will prospectively apply this software-based solution to evaluate generic and disease-specific HRQOL among patients with a recent clinical encounter for outpatient WHF. The overarching goal of this career development award is to provide me with the requisite training in research methodology and project experience to build upon my past successes as a traditional clinical trialist in order to also becoming a leader in health services, implementation science, and pragmatic clinical trials within a learning health system. Strengths of my proposal include my prior relevant training and track record in research, the experience and commitment of my mentors, collaborators, and consultants, and the vast institutional resources and support. In summary, this research proposal will employ innovative analytic approaches to elucidate the epidemiology, clinical features, and outcomes of this previously underappreciated and novel clinical entity. Given the current trend towards managing acute cardiac conditions primarily in the ambulatory setting, these findings have immediate implications for formulating public health policy as well as the design and conduct of future clinical trials.

项目摘要/摘要 尽管门诊心力衰竭的管理（HF）已通过循证药物进行了革新 和设备疗法，在接受恶化的患者的护理中没有这样的平行进展 HF（WHF）。激励卫生系统减少30天的再入院，《平价医疗法案》（ACA） 2012年启动了医院减免计划（HRRP），该计划对医院进行财务惩罚 如果他们对包括HF在内的条件有高于预期的风险调整率。虽然 HRRP的重新入院率适度降低，该程序具有转移的意想不到的后果 与HF相关的护理大部分为门诊环境。因此，该领域越来越兴趣 从护理位置解开whf，而不是使用住院作为急性的替代品 代偿性HF。但是，关于流行病学，临床特征，治疗模式和/或 门诊的结果。此外，虽然门诊HF患者的总体存活率有所改善 急剧，指导指导的医疗疗法（GDMT）对卫生的障碍的影响很小 相关生活质量（HRQOL）。尽管有这样的现实，但几乎没有现实世界的数据源可以描述 在门诊环境中HRQOL的轨迹。为了解决这些关键的知识差距，我们提出（1） 系统地描述当代流行病学，临床特征，治疗模式和 与门诊WHF相关的结果和（2）评估门门诊情节的影响 在完全整合的医疗保健提供系统的背景下，通用和疾病特异性的HRQOL。第一个 目标将利用大型，最先进且经过验证的电子健康记录的观察数据 （EHR）自然语言处理（NLP）系统的系统和机器学习算法 确定和全面地表征门诊WHF的发作。第二个目标将 前瞻性地应用此基于软件的解决方案来评估通用和疾病特异性的HRQOL 近期临床接触的患者在门诊病人中遇到。这项职业发展的总体目标 奖项是为我提供研究方法和项目经验的必要培训 我过去作为传统临床试验者的成功，以便成为卫生服务领域的领导者， 学习卫生系统中的实施科学和务实的临床试验。我的优势 建议包括我先前的相关培训和研究中的记录，我的经验和承诺 导师，合作者和顾问以及广泛的机构资源和支持。总而言之，这 研究建议将采用创新的分析方法来阐明流行病学，临床特征， 以及这种先前不足和新颖的临床实体的结果。考虑到当前的趋势 这些发现主要在门诊环境中管理急性心脏状况，立即有 制定公共卫生政策以及未​​来临床试验的设计和行为的影响。

项目成果

A Machine Learning Methodology for Identification and Triage of Heart Failure Exacerbations.

• DOI: 10.1007/s12265-021-10151-7
• 发表时间: 2022-03
• 期刊: Journal of cardiovascular translational research
• 影响因子: 3.4
• 作者: Morrill J;Qirko K;Kelly J;Ambrosy A;Toro B;Smith T;Wysham N;Fudim M;Swaminathan S
• 通讯作者: Swaminathan S

A randomized trial of icosapent ethyl in ambulatory patients with COVID-19.

• DOI: 10.1016/j.isci.2021.103040
• 发表时间: 2021-09-24
• 期刊: iScience
• 影响因子: 5.8
• 作者: Kosmopoulos A;Bhatt DL;Meglis G;Verma R;Pan Y;Quan A;Teoh H;Verma M;Jiao L;Wang R;Juliano RA;Kajil M;Kosiborod MN;Bari B;Berih AA;Aguilar M;Escano A;Leung A;Coelho I;Hibino M;Díaz R;Mason RP;Steg PG;Simon T;Go AS;Ambrosy AP;Choi R;Kushner AM;Leiter LA;Al-Omran M;Verma S;Mazer CD
• 通讯作者: Mazer CD

Trends and characteristics of hospitalizations for heart failure in the United States from 2004 to 2018.

• DOI: 10.1002/ehf2.13823
• 发表时间: 2022-04
• 期刊: ESC heart failure
• 影响因子: 3.8
• 作者: Salah HM;Minhas AMK;Khan MS;Khan SU;Ambrosy AP;Blumer V;Vaduganathan M;Greene SJ;Pandey A;Fudim M
• 通讯作者: Fudim M

Long-Term Cardiovascular Effects of COVID-19: Emerging Data Relevant to the Cardiovascular Clinician.

• DOI: 10.1007/s11883-022-01032-8
• 发表时间: 2022-07
• 期刊: CURRENT ATHEROSCLEROSIS REPORTS
• 影响因子: 5.8
• 作者: Tobler, Diana L.;Pruzansky, Alix J.;Naderi, Sahar;Ambrosy, Andrew P.;Slade, Justin J.
• 通讯作者: Slade, Justin J.

Characteristics and Outcomes of Suspected Digoxin Toxicity and Immune Fab Treatment Over the Past Two Decades-2000-2020.

• DOI: 10.1016/j.amjcard.2022.08.004
• 发表时间: 2022-11-15
• 期刊: AMERICAN JOURNAL OF CARDIOLOGY
• 影响因子: 2.8
• 作者: Peters, Anthony E.;Chiswell, Karen;Hofmann, Paul;Ambrosy, Andrew;Fudim, Marat
• 通讯作者: Fudim, Marat