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首页> 外文期刊>Value in health: the journal of the International Society for Pharmacoeconomics and Outcomes Research >Predicting Hospital Resource Use During COVID-19 Surges: A Simple but Flexible Discretely Integrated Condition Event Simulation of Individual Patient-Hospital Trajectories
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Predicting Hospital Resource Use During COVID-19 Surges: A Simple but Flexible Discretely Integrated Condition Event Simulation of Individual Patient-Hospital Trajectories

机译：在COVID-19预测医院资源利用激增:一个简单而灵活的离散综合条件事件模拟个人Patient-Hospital轨迹

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Objectives: To assist with planning hospital resources, including critical care (CC) beds, for managing patients with COVID-19. Methods: An individual simulation was implemented in Microsoft Excel using a discretely integrated condition event simulation. Expected daily cases presented to the emergency department were modeled in terms of transitions to and from ward and CC and to discharge or death. The duration of stay in each location was selected from trajectory-specific distributions. Daily ward and CC bed occupancy and the number of discharges according to care needs were forecast for the period of interest. Face validity was ascertained by local experts and, for the case study, by comparing forecasts with actual data. Results: To illustrate the use of the model, a case study was developed for Guy's and St Thomas' Trust. They provided inputs for January 2020 to early April 2020, and local observed case numbers were fit to provide estimates of emergency department arrivals. A peak demand of 467 ward and 135 CC beds was forecast, with diminishing numbers through July. The model tended to predict higher occupancy in Level 1 than what was eventually observed, but the timing of peaks was quite close, especially for CC, where the model predicted at least 120 beds would be occupied from April 9, 2020, to April 17, 2020, compared with April 7, 2020, to April 19, 2020, in reality. The care needs on discharge varied greatly from day to day. Conclusions: The DICE simulation of hospital trajectories of patients with COVID-19 provides forecasts of resources needed with only a few local inputs. This should help planners understand their expected resource needs.
机译：目的:协助规划医院资源,包括重症监护(CC)床管理COVID-19患者。单独的模拟实现使用离散集成Microsoft Excel条件事件模拟。呈现在急诊室模型的转换与病房和CC出院或死亡。在每个位置被选中trajectory-specific分布。CC床入住率和排放的数量根据保健需求预期感兴趣的时期。由当地专家,为案例研究预测与实际数据进行比较。说明模型的使用,一个案例研究发达的家伙和圣托马斯的信任。为2020年1月到4月初提供输入2020年,当地观察病例数是适合的提供应急部门的估计到达。床是预测,减少数字通过7月。在一级入住率比最终是什么观察,但峰值的时间相当密切,尤其是对CC,模型预计至少120个床位将占领2020年4月9日,4月17日,2020年,相比4月7日,2020年4月19日,2020年现实。一天比一天。模拟医院病人的轨迹COVID-19提供预测的资源只有几个地方需要输入。帮助规划者了解他们预期的资源的需求。

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