A regression model to identify supply chain cost drivers in healthcare and make cost predictions

Supply chain (SC) is again in the news because of SC disruptions about to jeopardise the 2021 Christmas season in the USA. Although abundant literature on healthcare supply chain management (SCM) exists, most research projects focus on finding cost-reduction strategies. Little research exists on what actually drives cost increases in a specific segment of the healthcare SC. This study analyses SC costs in the primary care sector as an attempt to uncover SC actual cost drivers in that segment beyond the well-known traditional classification so that SCM professionals can prioritise their efforts in resolving one or two most important factors that account for a significant portion of the total cost in that important sector. Using regression analysis and a test of statistical significance, the study determined that in the healthcare sector, inventory (with a p-value of 0.0001), and not transportation (traditionally known as the largest SC cost in all industry SC), is the biggest SC cost driver in primary care SCM. The result might lead to a positive managerial practice change in that segment of the healthcare SCM.