COVID-19: An Algorithmic Model for Critical Medical Resource Rationing in a Public Health Emergency

该项目的目的是开发一种算法模型，通过解决当前稀缺医疗资源分配协议的缺点，校准患者优先级的动态指数。英国新冠肺炎确诊死亡总人数已超过4.5万人。如此可怕的死亡人数部分归因于英国大流行初期个人防护装备、医务人员和重症监护病房床位的短缺。科学家估计，在医疗系统最紧张的冬季，第二波Covid-19可能会出现，英国可能会有大约12万人死于冠状病毒。为了使最多的患者获得最大的利益，必须在稀缺资源的分配方面制定合乎伦理和临床的合理政策。现有的分诊指南根据几个属性确定患者的优先级，包括疾病严重程度和出院后的近期预后。他们关注的是个别患者，而忽略了当前患者概况的整体混合，以及随着时间的推移，危重患者数量的不确定性。以前的研究表明，这种框架可能导致预防性死亡和稀缺资源的低效使用。在这个项目中，我们的目标是通过开发一个算法模型来解决这些限制，该模型可以校准动态索引（优先级）。通过使用英国公共卫生部收集的新冠肺炎患者的匿名数据进行实证研究，将其表现与基准进行比较。

The aim of the project is to develop an algorithmic model that calibrates a dynamic index for patient priority by addressing the shortcomings of the current allocation protocols of scarce medical resources. The total number of confirmed Covid-19 deaths in the UK has already passed the 45,000 mark. Such a horrific number of deaths is partly attributable to the shortage of PPE, medical staff, and ICU beds in the early stages of UK pandemic. For a second wave of Covid-19 likely in the winter when the healthcare system is most stretched, scientists have estimated that the UK could see about 120,000 new coronavirus deaths. To achieve the greatest good for the greatest number of patients, it is essential to have in place ethically and clinically sound policies on the allocation of scarce resources. Existing triage guidelines determine patient priority based on several attributes, including the illness severity and the near-term prognosis after discharge. They focus on individual patients but ignore the overall mixture of current patient profiles and the uncertainty in the number of patients who become critical ill over time. Previous research has shown that such frameworks could lead to preventative deaths and inefficient usage of scarce resources. We aim to address these limitations in this project via the development of an algorithmic model that calibrates a dynamic index (priority). Its performance is to be compared against the benchmarks via an empirical study using anonymised data of Covid-19 patients collected by Public Health England.