RAPID: Documenting Hospital Surge Operations in Responding to the COVID-19 Pandemic

RAPID：记录应对 COVID-19 大流行的医院激增操作

• 批准号: 2029917
• 负责人: Osman Ozaltin
• 金额: $ 12.84万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-01 至 2022-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2029917&HistoricalAwards=false
• 关键词: RAPID; Documenting; Hospital; Surge; Operations

The ongoing COVID-19 pandemic has caused many hospitals to dramatically shift their normal operations, including delaying elective and non-emergency surgeries, to accommodate a surge in critically ill infectious disease patients while still admitting and treating other severe injuries and illnesses not related to COVID-19. This Rapid Response Research (RAPID) grant will support the collection of time-sensitive data from two major hospital systems, Samaritan Health Services in Oregon and MedStar Health System in Washington DC/Maryland, to document changes in admissions patterns due to COVID-19, operational changes in practices to manage the surge, and patient outcomes during the pandemic. The project has the potential to provide important decision support to hospitals as they respond to future pandemics and other mass casualty events and should lead to better understanding of how hospital systems can mount an effective response to these major disturbances.The PIs will collect qualitative and quantitative data to document hospital operations as well as assess patient characteristics and outcomes during the COVID-19 pandemic. Data collection will be sourced from medical records characterizing the patient population treated, health outcomes, including diagnoses, length of stay, treatment, as well as pre-pandemic planning guidelines, real-time operational changes in ICU and hospital bed capacity allocation and staffing, equipment availability, including personal protective equipment and testing equipment, and other hospital, state, and federal interventions. Once collected, analysis of these data is expected to lead to knowledge, through better models and simulation, that can improve response to future pandemics.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

正在进行的COVID-19大流行使许多医院急剧转移其正常运作，包括延迟选举和非紧急手术，以适应重症患病的患病患者的激增，同时仍接受和治疗其他与Covid-19无关的严重伤害和其他严重伤害和疾病。 这项快速响应研究（Rapid）Grant将支持收集来自两个主要医院系统的时间敏感数据，即俄勒冈州的Samaritan Health Services和华盛顿特区/马里兰州的MedStar Health System，以记录Covid-19引起的入院模式的变化，在流行期间，由于COVID-19，实践的运作变化以及在管理过程中管理涌现以管理激增和患者的病人。 该项目有潜力为医院对未来的大流行病和其他大规模伤亡事件做出反应，为医院提供重要的决策支持，并应更好地理解医院系统如何对这些重大干扰产生有效的反应。PIS将收集定性和定量数据以记录医院的运营以及评估COVID-19 COVID-19 PANDEMIC期间的患者特征和目的。 数据收集将来自表征患者群体治疗的患者的病历，包括诊断，住院时间，治疗时间以及流行前计划指南，ICU和医院床位的实时操作变化，以及设备可用性，包括个人保护设备和测试设备以及其他医院，州以及联邦干预措施。 一旦收集，对这些数据的分析预计将通过更好的模型和模拟导致知识，从而改善对未来大流行的反应。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和更广泛影响的评估审查标准来通过评估来获得支持的。