Optimizing Inventory: A Process Improvement Case Study In Orthopedic Medical Devices

Open Access
- Author:
- Lombardo, Hannah
- Area of Honors:
- Supply Chain and Information Systems
- Degree:
- Bachelor of Science
- Document Type:
- Thesis
- Thesis Supervisors:
- Robert Alexander Novack, Thesis Supervisor
John C Spychalski, Honors Advisor - Keywords:
- supply chain management
healthcare
six sigma
inventory management
medical devices
process improvements - Abstract:
- The purpose of this thesis is to address medical device inventory optimization as a supply chain solution synergistically supporting both the clinical needs of a hospital and also the business needs of a medical device manufacturing company. Supply chain responsibilities are increasingly becoming stressors for healthcare clinicians and administrators alike. Improper management of supplies and inventory often leads to higher costs and an inefficient use of skilled labor, further taxing an industry increasingly being strained by operational costs and diminishing insurance reimbursements. The bottom line: supply chain is where hospitals should save resources, not further consume them. This thesis addresses optimizing the inventory management practices of a hospital’s orthopedic surgery department. The process, rationale and stakeholders are outlined, from the preliminary meetings to useful data analytics and identifying performance metrics to final recommendations for implementing improvements. These improvements all aim to solve the hospital’s primary pain point: periodic inventory stock-outs. The recommendations addressed in this study can be summarized as follows. Data on the existing inventory should be transferred into an electronic inventory database and maintained as inventory is added or removed for improved real-time visibility to stock availability. The calculated periodic automatic replenishment (PAR) levels should be used to guide optimal supply reorder frequency and quantity. Key performance indicators including real-time inventory consumption, order frequency and order volatility should be monitored with time and used to measure the success of the new process or if adjustments need to be made to the PAR levels. Finally, as this thesis was a designed case study, future collaborations between hospitals and manufacturing companies may consider the recommendations generalizable and applicable to the broader healthcare industry.