Cancer Patient Safety Learning Laboratory (CaPSLL): Preventing Clinical Deterioration in Outpatients

项目摘要/摘要 可预防伤害的一个常见原因是未能发现并适当地对临床 恶化。需要及时干预，特别是在医学上复杂的(例如癌症)患者中，以 减轻不良事件、疾病进展和医疗差错的影响。这个具有挑战性的问题 需要有效的临床监测，及早识别，及时通知适当的临床医生， 和有效的干预。在医院环境中，“未能救援”(FTR)是公认的安全故障。 为了应对FTR，医院引入了新的工具和流程(例如，持续监测、早期 警报系统和“快速反应”小组)。然而，“死在床上”仍然很常见。 范德比尔特-英格拉姆癌症中心，与人类因素和系统工程合作 系统安全研究和创新中心(CRISS)的教职员工以及我们的 工程与管理学院将创建癌症患者安全学习实验室 (CAPSLL)。我们将与外科医生、肿瘤学家、护士、工作人员以及患有肺部和头部疾病的成人患者合作。 或正在康复和/或作为门诊患者接受治疗的宫颈癌患者，以及他们的非专业护理人员，以 更可靠地检测和更有效地应对意外的临床恶化。这些细节是 以下内容是基于我们目前的理解，但由于我们采用了 面向系统工程的以用户为中心的设计(UCD)过程，分析、设计、开发、实施、 并评估用于解决这一复杂的患者安全问题的创新工具和流程。 我们将通过三个具体目标来实现这一目标：1)创建和完善软件工具和 用于监测和响应系统的预测模型，以防止意外的全因伤害 接受癌症治疗的门诊患者的临床恶化；2)创建和完善流程和 培训，使患者及其照顾者成为积极和可靠的参与者，以检测和 报告有潜在的临床恶化。我们将应用高可靠性组织(HRO)原则 和理论为相关的“团队”开发流程和培训--癌症患者，他们的 护理人员和需要对来自监视系统的信号做出反应的临床医生；以及3) 在运行环境中实施，并正式评估集成的检测和响应 工具和流程。我们假设(H1)该系统将降低 计划外治疗事件(UTE；例如入院)。此外，随着一项 以患者/家庭为中心的人力资源管理框架，我们假设系统将增加非常规事件 (NRE；偏离最佳护理)报告(H2)并缩短临床医生响应时间(H3)。这个 由此产生的工具、方法和预测模型将可扩展到其他癌症类型以及 可推广到其他机构和其他高危门诊人群(例如心力衰竭)。

Project Summary/Abstract A common cause of preventable harm is the failure to detect and appropriately respond to clinical deterioration. Timely intervention is needed, particularly in medically complex (e.g., cancer) patients, to mitigate the effects of adverse events, disease progression, and medical error. This challenging problem requires effective clinical surveillance, early recognition, timely notification of the appropriate clinician, and effective intervention. In the hospital setting, “failure to rescue” (FTR) is a recognized safety failure. To address FTR, hospitals have introduced new tools and processes (e.g., continuous monitoring, early warning systems, and `Rapid Response' teams). Yet, `death in bed' remains common. The Vanderbilt-Ingram Cancer Center, in collaboration with human factors and systems engineering faculty in the Center for Research and Innovation in Systems Safety (CRISS), as well as faculty in our Schools of Engineering and Management, will create the Cancer Patient Safety Learning Laboratory (CaPSLL). We will partner with surgeons, oncologists, nurses, staff, and adult patients with lung and head or neck cancer recovering from and/or undergoing treatment as outpatients, and their lay caregivers, to more reliably detect and respond more effectively to unexpected clinical deterioration. The details that follow in this proposal are based on our current understandings but will be modified as we employ a systems engineering oriented user-centered design (UCD) process to analyze, design, develop, implement, and evaluate innovative tools and processes to address this complex patient safety problem. We will achieve this through three Specific Aims: 1) To create and refine software tools and a predictive model for a surveillance-and-response system to prevent harm from unexpected all-cause clinical deterioration in outpatients receiving cancer treatment; 2) To create and refine processes and training that engage patients and their caregivers as active and reliable participants in detecting and reporting potential clinical deterioration. We will apply high reliability organizational (HRO) principles and theories to develop processes and training for the relevant “team” – the cancer patients, their caregivers, and the clinicians who need to respond to signals from the surveillance system; and 3) To implement in the operational environment and formally evaluate the integrated detection and response tools and processes. We hypothesize (H1) that this system will decrease the likelihood and severity of unplanned treatment events (UTE; e.g. hospital admission). Further, with the incorporation of a patient/family focused HRO framework, we hypothesize that the system will increase non-routine event (NRE; deviations from optimal care) reporting (H2) and decrease clinician response time (H3). The resulting tools, methods and predictive model will be scalable to other cancer types as well as being generalizable to other institutions and to other high-risk outpatient populations (e.g., heart failure).