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Optimal Hospital Readmissions and Resources Allocation in the Presence of a Pandemic: The Case of COVID-19

大流行期间的最佳再入院和资源分配：以 COVID-19 为例

基本信息

批准号：
554865-2020
负责人：
Hassini, Elkafi
金额：
$ 3.35万
依托单位：
McMaster University
依托单位国家：
加拿大
项目类别：
Alliance Grants
财政年份：
2020
资助国家：
加拿大
起止时间：
2020-01-01 至 2021-12-31
项目状态：
已结题

来源：
https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=705708
关键词：
Optimal Hospital Readmissions Resources Allocation

项目摘要

In their quest to avoid the devastating experiences of certain countries, the Canadian health care system as well as stakeholders across most countries have focused their contingency plans for COVID-19 on trying to avoid shortages in ICU beds in intensive care, ventilators and personal protection equipment (PPE). This has necessarily shifted attention and resources from primary care. Given the state of emergency and the restrictions implemented through the COVID-19 safety measures, primary health care provision has been impacted negatively. Coupled with the strain on both medical professionals and health care managers and the speed and dynamic nature of the changes, it has become very challenging to deal with complex operational efficiency matters such as hospital readmissions and resource allocations. It is thus our goal in this partnership research to address the complex problems of patient readmission and resource allocations during and immediately after the pandemic time frame. 3M plans to utilize the research outcomes outlined in this proposal to adapt its current software tools and algorithms to better handle extreme events, such as pandemics, with a focus on the Canadian health care system. This research will enhance effective decision making within hospital stakeholders during and beyond the pandemic context.

为了避免某些国家的灾难性经历，加拿大卫生保健系统以及大多数国家的利益相关者都将其COVID-19应急计划的重点放在试图避免重症监护病房床位，呼吸机和个人防护设备（PPE）短缺上。这必然转移了对初级保健的注意力和资源。鉴于紧急状态和通过COVID-19安全措施实施的限制，初级卫生保健服务受到负面影响。再加上医疗专业人员和卫生保健管理人员的压力以及变化的速度和动态性质，处理复杂的运营效率问题（如医院再入院和资源分配）变得非常具有挑战性。因此，我们在这项伙伴关系研究中的目标是解决大流行期间和之后的病人重新入院和资源分配的复杂问题。3 M计划利用本提案中概述的研究成果，调整其当前的软件工具和算法，以更好地处理极端事件，如流行病，重点是加拿大的医疗保健系统。这项研究将提高医院利益相关者在大流行期间和之后的有效决策。