Developing emergency department physician shift schedules optimized to meet patient demand
Developing emergency department physician shift schedules optimized to meet patient demand
复制标题
DOI：
10.2310/8000.2013.131224
复制
发表时间：
2015-01-01
影响因子：
2.4
通讯作者：
Wood, David
中科院分区：
文献类型：
--
作者：
Savage, David W.;Woolford, Douglas G.;Wood, David
目的：1）评估急诊科（艾德）历史患者到达率的时间模式，以确定急诊护理区和快速通道诊所的适当班次数量; 2）确定是否可以通过使用优化规划模型将医生生产率与患者到达率相匹配来改善医生调度。对历史数据进行统计学分析，以确定到达艾德的患者数量是否因工作日、周末或假日周末而异。基于泊松的广义加性模型用于开发全天患者到达率的模型。一个数学规划模型被用来产生一个最佳的艾德轮班时间表的估计病人到达率。我们比较了目前的医生时间表，其他三个调度方案：1）修订的时间表产生的规划模型，2）修订的时间表与额外的急性护理医生，和3）修订的时间表与额外的快速通道诊所physics.Results：统计建模发现，病人到达率不同的急性护理与快速通道诊所;在急症护理区，每天的到达模式基本相同;在快速通道诊所，工作日和周末的到达模式不同。计划模型减少了未满足的患者需求（即，到达艾德的病人的平均数量超过了平均医生生产力）的19%，39%，和69%for the three scenariesexamined.Conclusions：该规划模型通过调整医生的生产力与到达ED的病人来改善轮班时间表。
Objectives: 1) To assess temporal patterns in historical patient arrival rates in an emergency department (ED) to determine the appropriate number of shift schedules in an acute care area and a fast-track clinic and 2) to determine whether physician scheduling can be improved by aligning physician productivity with patient arrivals using an optimization planning model.Methods: Historical data were statistically analyzed to determine whether the number of patients arriving at the ED varied by weekday, weekend, or holiday weekend. Poisson-based generalized additive models were used to develop models of patient arrival rate throughout the day. A mathematical programming model was used to produce an optimal ED shift schedule for the estimated patient arrival rates. We compared the current physician schedule to three other scheduling scenarios: 1) a revised schedule produced by the planning model, 2) the revised schedule with an additional acute care physician, and 3) the revised schedule with an additional fast-track clinic physician.Results: Statistical modelling found that patient arrival rates were different for acute care versus fast-track clinics; the patterns in arrivals followed essentially the same daily pattern in the acute care area; and arrival patterns differed on weekdays versus weekends in the fast-track clinic. The planning model reduced the unmet patient demand (i.e., the average number of patients arriving at the ED beyond the average physician productivity) by 19%, 39%, and 69% for the three scenarios examined.Conclusions: The planning model improved the shift schedules by aligning physician productivity with patient arrivals at the ED.