Optimizing cardiology capacity to reduce emergency department boarding: A systems engineering approach
Optimizing cardiology capacity to reduce emergency department boarding: A systems engineering approach
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DOI：
10.1016/j.ahj.2008.07.007
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发表时间：
2008-12-01
影响因子：
4.8
通讯作者：
France, Daniel
中科院分区：
文献类型：
--
作者：
Levin, Scott R.;Dittus, Robert;France, Daniel
背景当医院科室之间的低效协调阻碍艾德患者获得住院心脏护理时，患者安全和急诊科（艾德）功能受到损害。本研究的目的是确定如何从竞争的心脏病入院来源的床位需求影响艾德患者的访问住院cardiac care.Methods医院的病人流量的随机离散事件模拟预测艾德患者登机时间，定义为心脏病入院请求住院床位安置之间的时间间隔，作为主要的结局措施。模拟建立和测试从1年的病人流量数据，并被用来检查前瞻性的策略，以减少心脏病患者登机time.Results的1,591艾德患者谁被录取到心脏遥测单元的登机时间平均为5.3小时（中位数3.1，四分位数间距1.5-6.9）。人口统计学和临床病人的特点是没有显着的预测登机时间。从竞争入院来源的床位需求的测量显着预测登机时间，导管插入实验室的需求水平是最有影响力的。医院政策要求为每名择期导管插入患者保留遥测床，但分析显示，这些患者中有70.4%（95% CI 51.2-92.5）没有转移到遥测床，每天出院回家。基于模拟的分析结果显示，将一个下午预定的择期导管插入病例移动到中午之前导致平均住院时间减少20分钟，而通过增加一个额外的遥测床位来增加容量则减少9分钟。结论基于测量的患者转移模式的调度和床位管理实践可以减少住院床位阻塞，优化医院容量，并改善艾德患者的访问。(Am Heart J 2008; 156：1202-9.）
Background Patient safety and emergency department (ED) functionality are compromised when inefficient coordination between hospital departments impedes ED patients' access to inpatient cardiac care. The objective of this study was to determine how bed demand from competing cardiology admission sources affects ED patients' access to inpatient cardiac care.Methods A stochastic discrete event simulation of hospital patient flow predicted ED patient boarding time, defined as the time interval between cardiology admission request to inpatient bed placement, as the primary outcome measure. The simulation was built and tested from 1 year of patient flow data and was used to examine prospective strategies to reduce cardiology patient boarding time.Results Boarding time for the 1,591 ED patients who were admitted to the cardiac telemetry unit averaged 5.3 hours (median 3.1, interquartile range 1.5-6.9). Demographic and clinical patient characteristics were not significant predictors of boarding time. Measurements of bed demand from competing admission sources significantly predicted boarding time, with catheterization laboratory demand levels being the most influential. Hospital policy required that a telemetry bed be held for each electively scheduled catheterization patient, yet the analysis revealed that 70.4% (95% CI 51.2-92.5) of these patients did not transfer to a telemetry bed and were discharged home each day. Results of simulation-based analyses showed that moving one afternoon scheduled elective catheterization case to before noon resulted in a 20-minute reduction in average boarding time compared to a 9-minute reduction achieved by increasing capacity by one additional telemetry bed.Conclusions Scheduling and bed management practices based on measured patient transfer patterns can reduce inpatient bed blocking, optimize hospital capacity, and improve ED patient access. (Am Heart J 2008; 156:1202-9.)