RESUMEN
Supply chain disruptions and demand disruptions make it challenging for hospital pharmacy managers to determine how much inventory to have on-hand. Having insufficient inventory leads to drug shortages, while having excess inventory leads to drug waste. To mitigate drug shortages and waste, hospital pharmacy managers can implement inventory policies that account for supply chain disruptions and adapt these inventory policies over time to respond to demand disruptions. Demand disruptions were prevalent during the Covid-19 pandemic. However, it remains unclear how a drug's shortage-waste weighting (i.e., concern for shortages versus concern for waste) as well as the duration of and time between supply chain disruptions influence the benefits (or detriments) of adapting to demand disruptions. We develop an adaptive inventory system (i.e., inventory policies change over time) and conduct an extensive numerical analysis using real-world demand data from the University of Michigan's Central Pharmacy to address this research question. For a fixed mean duration of and mean time between supply chain disruptions, we find a drug's shortage-waste weighting dictates the magnitude of the benefits (or detriments) of adaptive inventory policies. We create a ranking procedure that provides a way of discerning which drugs are of most concern and illustrates which policies to update given that a limited number of inventory policies can be updated. When applying our framework to over 300 drugs, we find a decision-maker needs to update a very small proportion of drugs (e.g., < 5 % ) at any point in time to get the greatest benefits of adaptive inventory policies.
RESUMEN
Nonalcoholic steatohepatitis (NASH) cirrhosis is the fastest growing indication for liver transplantation (LT) in the United States. We aimed to determine the temporal trend behind the rise in obesity and NASH-related additions to the LT waitlist in the United States and make projections for future NASH burden on the LT waitlist. We used data from the Organ Procurement and Transplantation Network database from 2000 to 2014 to obtain the number of NASH-related LT waitlist additions. The obese population in the United States from 2000 to 2014 was estimated using data from the U.S. Census Bureau and the National Health and Nutrition Examination Survey. Based on obesity trends, we established a time lag between obesity prevalence and NASH-related waitlist additions. We used data from the U.S. Census Bureau on population projections from 2016 to 2030 to forecast obesity estimates and NASH-related LT waitlist additions. From 2000 to 2014, the proportion of obese individuals significantly increased 44.9% and the number of NASH-related annual waitlist additions increased from 391 to 1,605. Increase in obesity prevalence was strongly associated with LT waitlist additions 9 years later in derivation and validation cohorts (R2 = 0.9). Based on these data, annual NASH-related waitlist additions are anticipated to increase by 55.4% (1,354-2,104) between 2016 and 2030. There is significant regional variation in obesity rates and in the anticipated increase in NASH-related waitlist additions (P < 0.01). Conclusion: We project a marked increase in demand for LT for NASH given population obesity trends. Continued public health efforts to curb obesity prevalence are needed to reduce the projected future burden of NASH. (Hepatology 2017).