Developing a Risk Index of Healthcare Provider Alertness to Improve Safety

描述（由申请人提供）：卫生保健提供者睡眠剥夺已被证明是一个重大的患者安全危害。医学研究所估计，每年可能有多达98,000名美国人死于医疗事故。根据ahrq资助的哈佛工作时间、健康和安全研究中实习生自己的报告，数千例可预防的死亡可能归因于实习医生的长时间工作。同样，护士在长时间工作时也会犯更多的医疗错误。虽然提供者睡眠剥夺对医疗错误的贡献得到了很好的证明，但缺乏基于证据的传统调度实践解决方案。需要一些工具来帮助管理人员和项目主管识别高风险计划，并根据不同的临床环境采用基于证据的建议。因此，我们建议：1。扩展基于睡眠和昼夜节律医学原理的绩效和警觉性数学模型，以开发时变时间表绩效指数（SPI），该指数将量化卫生保健提供者工作时间表带来的风险。2. 为了检验用SPI预测的减少与ahrq资助的实习生睡眠与患者安全研究中实习生的经验表现数据之间的相关性。为了试点测试SPI预测先前在哈佛工作时间、健康和安全数据集中经验建立的测量风险的能力。在这些人群中初始开发SPI将是开发、验证和测试进度建模软件的使用的第一步，以识别和减少整个医疗保健专业中与疲劳相关的性能下降。为了实现这一目标，我们将邀请一个多学科咨询小组参与，指导我们实施和传播该指数，以改善护士、实习医生、执业医生、医生助理、药剂师和其他医护人员的时间表。

DESCRIPTION (provided by applicant): Health care provider sleep deprivation has proven to be a substantial patient safety hazard. The Institute of Medicine estimates that as many as 98,000 Americans may die each year from medical errors. According to interns' own reports in the AHRQ-funded Harvard Work Hours, Health, and Safety Study, thousands of preventable deaths may be attributable to the long work hours of physicians-in- training. Nurses have similarly been shown to make many more medical errors when working extended hours. While the contribution of provider sleep deprivation to medical error is well-demonstrated, evidence- based solutions to traditional scheduling practices are lacking. Tools to help managers and program directors identify high risk schedules and adapt evidence-based recommendations for use in each distinct clinical environment are needed. We therefore propose: 1. To extend a mathematical model of performance and alertness based on principals of sleep and circadian medicine to develop a time-varying schedule performance index (SPI) that will quantify a measure of risk due to health care providers' work schedules. 2. To test the correlation between decrements predicted using the SPI and empiric performance data obtained from interns in the AHRQ-funded Intern Sleep and Patient Safety Study. 3. To pilot test the SPI's ability to predict the measured risk previously established empirically in the Harvard Work Hours, Health, and Safety Dataset. Initial development of the SPI in these populations will be the first step in an effort to develop, validate, and test the use of schedule modeling software to identify and reduce fatigue-related performance decrements across healthcare professions. In anticipation of this goal, we will engage the participation of a multi-disciplinary advisory group to guide us in the implementation and dissemination of the index to improve the schedules of nurses, physicians-in-training, practicing physicians, physicians' assistants, pharmacists, and other healthcare workers. PUBLIC HEALTH RELEVANCE: The traditional long work hours of healthcare providers lead to many preventable medical errors, and injuries to the providers themselves. We propose developing a scientifically-based mathematical "risk index" to study healthcare workers' schedules. This index would allow healthcare managers to quantify the risk associated with current work schedules and design safer alternatives.