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一个分析全院患者流动物流的框架:来自意大利一项比较研究的证据。

A framework to analyze hospital-wide patient flow logistics: evidence from an Italian comparative study.

作者信息

Villa Stefano, Prenestini Anna, Giusepi Isabella

机构信息

Department of Management, Catholic University, Rome, Italy; CERISMAS, Research Centre in Health Care Management, Catholic University, Milano, Italy.

CERGAS, Center for Research on Health and Social Care Management, Bocconi University, Milano, Italy; SDA Bocconi, School of Management, Via Roentgen, 1, 20136 Milano, Italy.

出版信息

Health Policy. 2014 Apr;115(2-3):196-205. doi: 10.1016/j.healthpol.2013.12.010. Epub 2014 Jan 5.

Abstract

Through a comparative study of six Italian hospitals, the paper develops and tests a framework to analyze hospital-wide patient flow performance. The framework adopts a system-wide approach to patient flow management and is structured around three different levels: (1) the hospital, (2) the pipelines (possible patient journeys within the hospital) and (3) the production units (physical spaces, such as operating rooms, where service delivery takes places). The focus groups and the data analysis conducted within the study support that the model is a useful tool to investigate hospital-wide implications of patient flows. The paper provides also evidence about the causes of hospital patient flow problems. Particularly, while shortage of capacity does not seem to be a relevant driver, our data shows that patient flow variability caused by inadequate allocation of capacity does represent a key problem. Results also show that the lack of coordination between different pipelines and production units is critical. Finally, the problem of overlapping between elective and unscheduled cases can be solved by setting aside a certain level of capacity for unexpected peaks.

摘要

通过对六家意大利医院的比较研究,本文开发并测试了一个用于分析全院患者流绩效的框架。该框架采用全系统方法进行患者流管理,并围绕三个不同层面构建:(1)医院层面;(2)流程(医院内患者可能的就医路径)层面;(3)生产单元(进行服务交付的物理空间,如手术室)层面。研究中开展的焦点小组讨论和数据分析表明,该模型是研究患者流对全院影响的有用工具。本文还提供了医院患者流问题成因的证据。具体而言,虽然容量短缺似乎不是一个相关驱动因素,但我们的数据表明,因容量分配不当导致的患者流变异性确实是一个关键问题。结果还表明,不同流程与生产单元之间缺乏协调至关重要。最后,通过预留一定水平的容量以应对意外高峰,可以解决择期病例和非计划病例重叠的问题。

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