Developing and Implementing a Weighted Lottery to Equitably Allocate Scarce COVID-19 Medications

Abstract

RATIONALE: The burdens of the COVID-19 pandemic have fallen disproportionately on disadvantaged groups, including the poor and Black, Latinx, and Indigenous communities. We sought to develop and implement a weighted lottery to more equitably allocate scarce COVID-19 medications in a large U.S. health system. METHODS: We convened a multi-institution consortium of experts in bioethics, economics, health disparities, medicine, pharmacy, and health law to develop the weighted lottery. The UPMC Patient and Family Advisory Council and the Commonwealth of Pennsylvania's Ethical Allocation Committee reviewed and endorsed the framework. We implemented the weighted lottery during periods when there was inadequate remdesivir to treat all patients in need. We used administrative data to ascertain the number and characteristics of patients who, on days of drug shortage: 1) were eligible for remdesivir;2) were offered remdesivir;and 3) accepted remdesivir. RESULTS: We implemented the weighted lottery across 23 hospitals in the UPMC health system during periods of drug shortage in May-July 2020. We proactively identified eligible patients using an EHR-and telephone-based screening system. To determine the general population chances in the lottery, each week we divided the number of available treatment courses by the predicted number of patients who would be eligible that week, based on the number of eligible patients in the prior week. The table contains the weighting factors in the remdesivir lottery. An allocation team met daily to apply the weighting system that determined each eligible patient's chance, then used a random number generator to run the lottery. Overall, 93 patients met the clinical eligibility criteria outlined in the FDA's emergency use authorization;44% were from disadvantaged neighborhoods, 20% were essential workers, and 9% had an underlying end-stage medical condition. During the periods of drug shortage, the general population chances to receive treatment ranged from 28%-88%. 59% of eligible patients (55 of 93) were allocated remdesivir, 13% of whom (7 of 55) refused the treatment. Overall 61% of drug was allocated to patients who were from disadvantaged neighborhoods and/or were essential workers, who made up 56% of the population. >CONCLUSIONS: We developed and implemented a weighted lottery to promote equity in the allocation of scarce COVID-19 therapeutics. The lottery resulted in heightened access to treatment among groups that have been disproportionately impacted by the pandemic, though larger weightings may be needed to substantially mitigate disparities. (Table Presented).