University of Minnesota Twin Cities, Minneapolis, MN, USA.
J Med Syst. 2019 Jan 30;43(3):56. doi: 10.1007/s10916-019-1174-z.
New sources of operational data are leading to novel healthcare delivery system design and opportunities to support operational planning and decision-making. Technologies such as real time locating systems (RTLS) provide a unique view and understanding of how healthcare delivery settings behave and respond to operational design changes. In this paper RTLS data from an outpatient clinical setting is leveraged to identify the appropriate number of scheduled providers in order to improve the utilization of the clinical space while balancing the negative effects of clinic congestion. The approaches presented pair historical utilization rates for the clinical space with scheduled provider and patient volumes to support scheduling decisions in an operationally flexible clinic design. These historical data are augmented with clinic staff observation logs to identify target utilization rates as well as high congestion levels. Results are presented for two approaches: one where utilization of clinical space is a key performance metric and another where the decision-maker may be risk averse toward the use of provider time and use a probabilistic approach to determine provider staffing levels.
新的运营数据来源正在推动新的医疗保健交付系统设计，并为支持运营规划和决策提供机会。实时定位系统 (RTLS) 等技术提供了一种独特的视角和理解，了解医疗保健交付环境的运作方式以及如何对运营设计变更做出响应。在本文中，利用门诊临床环境中的 RTLS 数据来确定适当数量的计划提供者，以提高临床空间的利用率，同时平衡诊所拥堵的负面影响。所提出的方法将临床空间的历史利用率与计划提供者和患者数量进行配对，以支持在运营灵活的诊所设计中进行调度决策。这些历史数据通过诊所工作人员观察日志进行扩充，以确定目标利用率和高拥堵水平。为两种方法提供了结果：一种方法将临床空间的利用率作为关键绩效指标，另一种方法决策者可能对使用提供者时间持规避风险的态度，并使用概率方法来确定提供者人员配备水平。
