Hedging Risks of Demand and Lead Time Variabilities in Healthcare Inventory Management
DOI:
https://doi.org/10.33423/jaf.v24i5.7431Keywords:
accounting, finance, inventory, demand, lead time, safety stock, stock-out cost, overstock cost, reorder pointAbstract
This paper proceeds from the premise, derived from the literature, that uncertainty is predominantly a demand-side and/or lead time problem in healthcare inventory management. It conceptually explores how organizational exposure to the risks of uncertain demand and lead time may be hedged, especially considering that forecasting stock-outs and overstocks can be quite challenging in healthcare. We examine these challenges probabilistically. Theoretically, by inquiring into the underlying premises of aggregate demand, order quantity, and reorder point. And practically, regarding the implications of hedging inventory risks under conditions of uncertainty. Three measures that can efficiently hedge against demand and lead time variabilities under a continuous review inventory system are identified and analyzed: safety stock with service level, stock-out and overstock costing, and low-cost reorder point. Mathematical modeling, simulation, and optimization enhance integrated financial and operational problem-solving. With appropriate technology and software, demand forecasting and risk-hedging offer real-time visibility into stock levels. These should help healthcare organizations make critical, data-driven decisions and contain costly understocking and unnecessary overstocking when demand and lead time are stochastic and discreet.
References
Anderson, E.T., Fitzsimons, G.J., & Simester, D. (2006). Measuring and mitigating the costs of stockouts. Management Science, 52(11), 1751–1763.
Arnold, J.R.T., Chapman, S.N., & Clive, L.M. (2008). Introduction to Materials Management (6th ed.). Upper Saddle River, NJ: Pearson Education, Inc.
Arrow, K.J. (1963). Uncertainty and the welfare economics of medical care. American Economic Review, 53(5), 941–973.
Atiya, B., Bakheet, A.J.K., Abbas, I.T., Bakar, M.R.A., Soon, L.L., & Monsi, M.B. (2016, January 26–28). Application of simulated annealing to solve multi-objectives for aggregate production planning. Proceedings of the 2nd International Conference on Mathematical Sciences and Statistics. Kuala Lumpur, Malaysia.
Barrros, J., Cortez, P., & Carvalho, M.S. (2021). A systematic literature review about dimensioning safety stock under uncertainties and risks in the procurement process. Operations Research Perspectives, 8(100192), 1–25.
Berman, H.J., Kukla, S.F., & Weeks, L.E. (1994). The financial management of hospitals (8th ed.). Chicago: Health Administration Press.
Buchanan, L. (2023). Conquer intermittent demand with probabilistic inventory planning. Retrieved from https://www.logility.com/blog/conquer-intermittent-demand-with-probabilistic-inventory-planning/
Choi, T.M., Govindan, K., Li, X., & Li, Y. (2017). Innovative supply chain optimization models with multiple uncertainty factors. Annals of Operations Research, 257(1–2), 1–14.
Cleverley, W.O., Cleverly, J.O., & Parks, A.V. (2023). Essentials of health care finance (9th ed.). Burlington, MA: Jones & Bartlett Learning.
Farahani, R.Z., Rezapour, S., & Kardar, L. (2011). Logistics Operations and Management. Amsterdam: Elsevier, Inc.
Gapenski, L. (2016). Healthcare Finance: An Introduction to Accounting and Financial Management (6th ed.). Chicago: Health Administration Press.
Gonçalves, J.N.C., Sameiro Carvalho, M., & Cortez, P. (2020). Operations research models and methods for safety stock determination: A review. Operations Research Perspectives, 7(100164), 1–14.
Gonzatto Junior, O.A., Nascimento, D.C., Russo, C.M., Henriques, M.J., Tomazella, C.P., Santos, M.O., . . . Louzada, F. (2022). Safety-Stock: Predicting the demand for supplies in Brazilian hospitals during the COVID-19 pandemic. Knowledge-Based Systems, 247(108753), 1–10.
Han, P.K., Klein, W.M., & Arora, N.K. (2011). Varieties of uncertainty in health care: A conceptual taxonomy. Medical Decision Making, 31(6), 828–838.
Institute of Chartered Accountants of India (ICAI). (2021). Cost and management accounting. New Delhi: Sahitya Bhawan Publications. Retrieved from https://live.icai.org/bos/vcc-3rd-batch/pdf/Chapter_2_Material_Costing.pdf
Khokhar, S.A. (2023). The challenges of inventory management in medical supply chain. South Asian Journal of Operations and Logistics, 2(2), 1–18.
Knowles, J.C. (1995). Research note: Price uncertainty and the demand for health care. Health Policy and Planning, 10(3), 301–303.
Kuntz, K., Sainfort, F., & Butler, M. (2013). Decision and simulation modeling in systematic reviews. Rockville, MD: Agency for Healthcare Research and Quality.
Moon, I., & Choi, S. (1998). A note on lead time and distributional assumptions in continuous review inventory models. Computers & Operations Research, 25(11), 1007–1012.
Nowicki, M. (2022). Introduction to the financial management of healthcare organizations (8th ed.). Chicago, Illinois: Gateway to Healthcare Management.
Oeser, G., & Romano, P. (2021). Exploring risk pooling in hospitals to reduce demand and lead time uncertainty. Operations Management Research, 14(1–2), 78–94.
Olofsson, O. (2024). Wilson inventory formula. Retrieved from https://world-class-manufacturing.com/eoq/wilson.html
Ouyang, L.Y., & Chang, H.C. (2002). A minimax distribution free procedure for mixed inventory models involving variable lead time with fuzzy lost sales. International Journal of Production Economics, 76(1), 1–12.
Ovezmyradov, B. (2022, November 30). Product availability and stockpiling in times of pandemic: Causes of supply chain disruptions and preventive measures in retailing. Annals of Operations Research, (unassigned), 1–33.
Poswal, P., Chauhan, A., Rajoria, Y.K., Boadh, R., & Singh, A.P. (2022). An economic ordering policy to control deteriorating medicinal products of uncertain demand with trade credit for healthcare industries. International Journal of Health Sciences, 6(S2), 9392–9414.
Ramachandram, K.A.L. (2015). Improving delivery lead time in medical device supplies to public hospitals in Malaysia. Masters thesis, Universiti Sains Malaysia, Pulau Pinang, Malaysia.
Raturi, A.S., & Singhal, V.R. (1990). Estimating the opportunity cost of capital for inventory investments. Omega, 18(4), 407–413.
Saha, E., & Ray P.K. (2019). Modelling and analysis of inventory management systems in healthcare: A review and reflections. Computers & Industrial Engineering, 137(106051), 1–20.
van Beek, L.R. (2023). A continuous review inventory model for the improvement of material logistics in hospitals. Unpublished M.Sc. thesis, Department of Behavioural, Management, and Social Sciences, University of Twente, Enschede, Netherlands.
Waters, D. (2003). Inventory control and management, 2nd ed. West Sussex, England: John Wiley & Sons Ltd.
Yeung, A. (2023). What are stockout costs and how do you avoid them? Retrieved from https://www.thoughtspot.com/data-trends/analytics/stockout-costs