Exploring risk pooling in hospitals to reduce demand and lead time uncertainty

Abstract

Nearly every eighth German hospital faces an elevated risk of bankruptcy. An inappropriate use of inventory management practices is among the causes. Hospitals suffer from demand and lead time uncertainty, and the current COVID-19 pandemic worsened the plight. The popular business logistics concept of risk pooling has been shown to reduce these uncertainties in industry and trade, but has been neglected as a variability reduction method in healthcare operations research and practice. Based on a survey with 223 German hospitals, this study explores how ten risk pooling methods can be adapted and applied in the healthcare context to reduce economic losses while maintaining a given service level. The results suggest that in general risk pooling may improve the economic situation of hospitals and, in particular, inventory pooling, transshipments, and product substitution for medications and consumer goods are the most effective methods in the healthcare context, while form postponement may be unsuitable for hospitals due to the required efforts, delay in treatments, and liability issues. The application of risk pooling in healthcare requires willingness to exchange information and to cooperate, adequate IT infrastructure, compatibility, adherence to healthcare laws and regulations, and securing the immediate treatment of emergencies. Compared to manufacturing and trading companies, hospitals seem to currently neglect the variability reducing effect of risk pooling.

What’s the penalty for using the Square Root Law of inventory centralisation?

“…The risk-pooling effect on safety stock (Schwarz, 1981; Zinn et al , 1989; Evers, 1995) and possible “EOQ cost effect” (Schwarz, 1981, p. 147) or “order quantity effect” (Evers, 1995, p. 5) arising from inventory pooling allow to decrease inventory for a given service level, increase service level for a given inventory, or a combination of both inventory reduction and service level increase (cf. Chopra and Meindl, 2007; Cachon and Terwiesch, 2012; Oeser, 2015). The SRL merely considers the first option.…”

“…full truck load) and only certain multiples can be ordered (e.g. only full palettes), centralising inventory and ordering can reduce average cycle stock, but not conformable to the SRL (Oeser, 2015).…”

“…Consequently, centralisation does not reduce system-wide safety stock, if the experientially determined safety factor is equal for all warehouses and remains the same. The service level increases, however, due to the risk-pooling effect, which might turn out higher than necessary or economically sensible (Oeser, 2015).…”

Is it worth treating patients with COVID‐19 in intensive care? Utility, choice, costs and value

“…et al undertook their study in an economic framework in Germany in which hospitals, being private financial entities, must balance their budgets. Failure to balance budgets leads to bankruptcy and around 12% are at risk of closure[25]. In contrast, governments and the public sector services they directly fund and underwrite, are not bound by the same fiscal rules because governments create (print) the currency used in the economy.…”

Implications of the ageing population for the food demand chain in Germany

“…Distribution logistics can also gather information about the end consumer for food retail and production Today food ordered online is either shipped from a central warehouse or retail store to the customer or picked up by the customer from a central warehouse or store For elder food consumers the first two solutions will be important (Usui, 2011) (continued ) May reduce inventory, stockout, and transportation costs for a given service level due to risk pooling (cf. Oeser, 2015) for food production, retail, and logistics, but increase the transportation cost for the consumer due to an increasing distance to the closest store German population expected to shrink; caloric needs (CNPP, 2015) and food consumption per elder consumer is lower than that of a younger one (Popper and Kroll, 2003;, share of elder consumers expected to increase, total amount of food consumed may decrease Total transport volumes and cycle stocks to cover the average food demand are likely to decrease and not utilise the existing capacities, which may increase costs Regions affected by ageing population differently (Grünheid, 2015;Grünheid and Sulak, 2016); home-delivery of food Regionalisation, more decentralised stock-holding and higher individual cycle and safety stocks Diverse food preferences of the heterogeneous elder consumers and offering single-packs (Kirchmair, 2005;Pak and Kambil, 2006;Moschis and Ünal, 2008;Silvera et al, 2012) May increase food product variety and consequently safety stocks for a given product availability, shortages, and waste because of higher forecast errors. The overall cycle stock decreases due to lower food consumption may well be higher than safety stock increases Business informatics…”