Developing and Evaluating Quality-Weighted Hospital-Free Days as a Novel, Patient-Centered Outcome for Trials of Patients with Acute Respiratory Failure

制定和评估质量加权的非住院日作为急性呼吸衰竭患者试验的一种新颖的、以患者为中心的结果

• 批准号: 10427764
• 负责人: Catherine Louise Auriemma
• 金额: $ 19.37万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-05 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10427764
• 关键词: Acute; Acute respiratory failure; Admission activity; Adult; American; Caregiver Burden; Caregiver research; Caregivers; Clinical Trials; Cognitive; Cohort Studies; Consensus; Critical Care; Critical Illness; Data; Data Reporting; Development Plans; Electronic Health Record; Enrollment; Environment; Family; Family Caregiver; Family member; Financial Support; Frequencies; Future; Goals; Health; Home; Hospital Mortality; Hospitals; Impaired health; Impairment; Incidence; Institution; Intensive Care Units; Interdisciplinary Study; International; Intervention; K-Series Research Career Programs; Knowledge; Lead; Lung; Measurable; Measures; Mentors; Methodology; Methods; Modality; National Heart, Lung, and Blood Institute; Outcome; Outcome Measure; Patient Outcomes Assessments; Patient-Focused Outcomes; Patients; Pennsylvania; Physicians; Population; Positioning Attribute; Property; Prospective Studies; Prospective cohort; Prospective cohort study; Psychometrics; Public Health; Quality of life; Quality-of-Life Assessment; Records; Reporting; Research; Research Design; Research Personnel; Sample Size; Scholarship; Science; Scientist; Statistical Models; Structure; Surveys; Survivors; Techniques; Training; Translating; Universities; Weight; Work; acute care; career; career development; cohort; design; digital; experience; follow-up; functional status; health care service utilization; health goals; hospital readmission; improved; innovation; instrument; models and simulation; mortality; novel; palliative; patient engagement; patient oriented; prospective; psychosocial; randomized trial; recruit; response; skills; social; success; survivorship

Project Summary/Abstract Candidate: Catherine Auriemma, MD, is a pulmonary and critical care physician-scientist passionate about understanding and improving long-term outcomes of patients with acute respiratory failure (ARF). To advance her career towards research independence, she seeks didactic and experiential training to develop expertise in consensus methods, prospective study design, and statistical modeling and simulation. Research Context: Rising incidence and decreasing mortality of ARF has produced a growing population of survivors facing significant physical, cognitive, and social impairments requiring increased healthcare utilization. A crucial barrier to advancing ARF survivorship research is the lack of an outcome measure that is patient-centered and appropriate for evaluating interventions with either palliative or restorative intent. Hospital- free days (HFDs), the number of days spent alive and outside an acute care hospital, has become common in studies of other acutely ill populations. However, HFDs does not account for decrements in functional status or quality of life; and the bimodal distribution of HFDs among ARF patients raises questions regarding the statistical power and construct validity of HFDs for ARF. This study proposes to design and evaluate a method to quality-weight HFDs using patient-reported assessments of function, quality of life, or caregiver burden. Specific Aims: 1) Develop an optimal approach to quality-weight HFDs using consensus methods with key stakeholders; 2) Assess quality-weighted HFDs among a prospective cohort of ARF patients; 3) Compare statistical power and construct validity of HFDs with and without quality-weighting in a large ARF cohort. Research Plan: To accomplish these aims, Dr. Auriemma will convene a Delphi panel of ARF survivors, family caregivers, clinicians, and trialists to develop best practices for integrating patient- and caregiver-reported data into assessments of HFDs. She will then apply the novel method to a prospective cohort of ARF patients to assess acceptability, responsiveness, and variability of quality-weighted HFDs. Finally, she will use observed values in the Aim 2 cohort to simulate quality-weighted HFDs in a large clinical trial among patients with ARF to compare statistical power and construct validity of unweighted and quality-weighted HFDs. Career Development Plan: Working closely with her mentors and advisors, Dr. Auriemma will 1) develop expertise in consensus methods necessary to convert multiple patient-identified core values into measurable outcomes; 2) obtain the skills necessary to design, launch, oversee, and complete a multisite, prospective cohort study; and 3) gain methodologic expertise in advanced statistical modeling and simulation techniques. Environment: The University of Pennsylvania offers an ideal environment to pursue this training, with well- established mentors and her home department heavily dedicated to Dr. Auriemma’s success, and several multi-disciplinary research centers with long track records of producing successful, independent investigators.

项目总结/摘要 候选人：Catherine Auriemma，医学博士，是一位肺部和重症监护医生，科学家，热衷于 了解和改善急性呼吸衰竭（ARF）患者的长期结局。推进 她的职业生涯走向研究独立，她寻求教学和经验培训，以发展专业知识， 共识方法，前瞻性研究设计，统计建模和模拟。 研究背景：ARF发病率的上升和死亡率的下降使越来越多的人 幸存者面临严重的身体、认知和社会障碍，需要增加医疗保健 利用率推进ARF生存率研究的一个关键障碍是缺乏一种结果测量方法， 以患者为中心，适用于评估具有姑息或恢复意图的干预措施。医院- 自由日（HFD），即在急性护理医院外存活的天数，在美国已经很常见。 其他急性病患者的研究。然而，HFD不考虑功能状态的下降， 生活质量; ARF患者中HFD的双峰分布提出了关于 统计功效和结构效度。本研究提出设计和评估一种方法， 使用患者报告的功能、生活质量或护理者负担评估的质量加权HFD。 具体目标：1）使用关键的共识方法开发质量-重量HFD的最佳方法 利益相关者; 2）评估ARF患者前瞻性队列中的质量加权HFD; 3）比较 在一个大型ARF队列中，有和没有质量加权的HFD的统计功效和结构效度。 研究计划：为了实现这些目标，Auriemma博士将召集一个德尔菲小组，成员包括ARF幸存者、家庭成员和研究人员。 护理人员、临床医生和试验人员制定整合患者和患者报告数据的最佳实践 评估HFD。然后，她将把这种新方法应用于ARF患者的前瞻性队列， 评估质量加权HFD的可接受性、响应性和可变性。最后，她将使用观察 在ARF患者中进行的一项大型临床试验中，Aim 2队列中的数值模拟质量加权HFD， 比较未加权和质量加权HFD的统计功效和结构效度。 职业发展计划：奥里玛博士将与她的导师和顾问密切合作， 将多个患者确定的核心价值转化为可衡量的 成果; 2）获得设计，启动，监督和完成多站点，前瞻性 队列研究; 3）获得先进的统计建模和模拟技术的方法学专业知识。 环境：宾夕法尼亚大学提供了一个理想的环境，追求这种培训，以及- 建立导师和她的家庭部门严重致力于博士奥里玛的成功，和几个 多学科研究中心，长期以来培养出成功的独立研究人员。