US drug shortages compared to the World Health Organization's Model List of Essential Medicines for Children: A cross-sectional study.

PURPOSE: To describe US drug shortages affecting medications on the 2019 World Health Organization (WHO) Model List of Essential Medicines for Children (EMLc). METHODS: Drug shortage data from January 2014 to December 2019 were obtained from the University of Utah Drug Information Service. Shortage data for drugs on the EMLc were analyzed for the type of drug, American Hospital Formulary Service category, reason for the shortage, duration of the shortage, marketing status (generic vs brand name), and whether the agent was a single- or multisource drug. RESULTS: From 2014 to 2019, a total of 209 drug shortages impacted medications on the EMLc, of which 77 (36.8%) remained unresolved by 2019. Of all active shortages, 13 (6.2%) began before 2014. Resolved shortages had a median duration of 5.9 months (interquartile range [IQR], 3.6-13.2 months) while active shortages had a median duration of 18.3 months (IQR, 10.9-33.5 months; P ≤ 0.0001). The therapeutic categories most impacted by drug shortages were anti-infective agents (27.3%), central nervous system agents (12.9%), and antineoplastic agents (11.0%). The reason for the shortage was not reported in 46.4% of cases. When a reason was provided, the most common reason was manufacturing problems (29.2%) followed by supply/demand mismatch (15.8%). CONCLUSION: US drug shortages affected many medications on the WHO EMLc. Future studies should examine the global shortage climate and implications for patient care.

Validation of "Personal Protective Equipment Conservation Strategies Tool" to Predict Consumption of N95s, Facemasks, and Gowns During Pandemic-Related Shortages.

We sought to prospectively validate a model to predict the consumption of personal protective equipment in a pediatric emergency department during the COVID-19 pandemic. We developed the Personal Protective Equipment Conservation Strategies Tool, a Monte Carlo simulation model with input parameters defined by members of our emergency department personal protective equipment task force. Inputs include different conservation strategies that reflect dynamic reuse policies. Over the course of 4 consecutive weeks in April and May 2020, we used the model to predict the consumption of N95 respirators, facemasks, and gowns in our emergency department based on values for each input parameter. At the end of each week, we calculated the percent difference between actual consumption and predicted consumption based on model outputs. Actual consumption of personal protective equipment was within 20% of model predictions for each of the 4 consecutive weeks for N95s (range, -16.3% to 16.1%) and facemasks (range, -7.6% to 13.1%), using "maximum conservation" and "high conservation" strategies, respectively. Actual consumption of gowns was 11.8% less than predicted consumption for Week 1, gown resupply data were unavailable on Weeks 2-4. The Personal Protective Equipment Conservation Strategies Tool was prospectively validated for "maximum conservation" and "high conservation" models, with actual consumption within 20% of model predictions.