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Optimizing Intensive Care Unit Staffing in the United States

Optimizing Intensive Care Unit Staffing in the United States
优化美国重症监护病房的人员配置
批准号:
10611850
负责人:
Hayley Beth Gershengorn
金额:
$33.42万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-04-15 至 2026-03-31

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中文摘要
翻译
摘要 医疗质量受结构和组织的影响。大约有600万美国人获准进入 每年到重症监护病房(ICU),许多人需要机械通气来治疗急性呼吸衰竭。 了解最佳的ICU组织对于确保为这些患者提供高质量的护理至关重要,我们的 病情最重的病人。在过去的20年里,随着美国ICU床位的数量和提供的护理的复杂性 大幅增加,强化医生(接受过专门重症护理培训的医生)与 跨专业ICU团队(包括护士、呼吸治疗师、临床药剂师等)已经变成了 这是许多ICU的常态。研究强调了对危重病人进行强化护理的积极影响 患者;为此,重症护理医学会建议“高强度强化人员配备”。 同样,多学科团队对患者预后的积极影响也是众所周知的。什么不是 然而,已知的是ICU护理提供者如何在团队结构和工作量的背景下影响患者护理。 我们最近在英国的研究表明,在英国, 每个强化疗法患者的护理和他们的患者的死亡率;这种关系在美国是否相同 它如何受到其他ICU护理提供者的影响尚不清楚。最后,自2000年一项里程碑式的研究以来 突显了美国集约化需求和供应之间的差距,很明显,更新的ICU 需要劳动力预测来帮助进行资源规划;然而,如果受到以下因素的限制,这些预测将会失败 “孤岛”(例如,预测集中需求,而不考虑其他护理提供者的缓解效果)和 对最优人员结构可能与目前使用的人员结构有何不同认识不足。在这项研究中,我们 将使用与多个美国ICU的现有患者级别数据相关联的初步调查和一项新的 解决3个目标的系统动力学建模方法:(1)确定当前详细的人员配置模型 在全美使用;(2)量化患者与护理提供者比率与患者结果之间的关联 选定的ICU;以及(3)估计当前和未来的ICU劳动力需求。这个项目将产生重要的见解 ICU护理服务的最佳人员配备模式,以及未来必须如何分配资源才能完成 ICU护理提供者的差距。在专注于ICU护理的同时,该项目将为(1)创建一个可复制的框架 根据其他可用人员和(2)使用系统,通过每日患者普查来量化提供者的工作量 动态建模以模拟劳动力供应和需求,这将有助于计划以下任何方面 医疗保健。我们将向临床医生和政策制定者提供有关ICU人员配置的关键信息,以改善患者状况 安全。
英文摘要
ABSTRACT Healthcare quality is impacted by structure and organization. Approximately 6 million Americans are admitted to an intensive care unit (ICU) yearly and many require mechanical ventilation for acute respiratory failure. Understanding optimal ICU organization is essential to ensure high quality care is delivered to these, our sickest patients. Over the past 20 years as the number of US ICU beds and the complexity of care provided has increased dramatically, intensivists (physicians trained specifically in critical care) working with interprofessional ICU teams (including nurses, respiratory therapists, clinical pharmacists, etc.) have become the norm in many ICUs. Studies highlight the positive impact of having an intensivist care for critically ill patients; for this reason, the Society of Critical Care Medicine recommends “high intensity intensivist staffing”. Similarly, the positive impact of a multidisciplinary team on patient outcomes is well established. What is not known, however, is how ICU care providers impact patient care in the context of team structure and workload. Our recent work in the United Kingdom suggests there is a significant relationship between the number of patients each intensivist cares for and their patients’ mortality; whether this relationship is the same in the US and how it is affected by other ICU care providers is unknown. Finally, since a landmark study in 2000 highlighted the gap between intensivist demand and supply in the US, it has become clear that updated ICU workforce projections are needed to aid in resource planning; however, these will fail if they are limited by “siloing” (e.g., projecting intensivist need without considering the mitigating effect of other care providers) and an underappreciation of how optimal staffing structures may differ from what is in use today. In this study we will use primary surveys linked with existing patient- level data across multiple US ICUs and a novel methodology of System Dynamics Modeling to address 3 aims: (1) determine detailed staffing models currently used across the US; (2) quantify the association of patient-to-care provider ratio with patient outcomes across selected ICUs; and (3) estimate current and future ICU workforce need. This project will yield critical insights into the best staffing models for ICU care delivery and how resources must be allocated in the future to close ICU care provider gaps. While focused on ICU care, this project will create a replicable framework for (1) quantifying provider workload by daily patient census in light of other staffing availability and (2) using System Dynamics Modeling to simulate workforce supply and demand which will be useful to plan for any aspect of healthcare. We will provide clinicians and policy makers with key information on ICU staffing to improve patient safety.
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Optimizing Intensive Care Unit Staffing in the United States
Optimizing Intensive Care Unit Staffing in the United States
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