Optimization and Rule-Based Models for Hospital Inventory Management

This thesis shows how optimization, rule-based models, and operational analytics can be used to help manage hospital surgical inventory. The models were created for AITA™, a team under Johnson & Johnson’s Ethicon subsidiary. The AITA™ Smart System is an intelligent inventory management solution that stores, organizes, and distributes products via Kiosk, Smart Shelf, and Mobile Hub devices. Every device requires a planogram, or a visual representation of which products to stock and the location of each product. This project focuses on creating models to automatically build and update these planograms. The models presented in this paper have already been adopted by the AITA™ team and have begun to show accuracy and efficiency gains when compared to the current manual process. Model-designed kiosks cover, on average, 7% more historical procedures than hand-made kiosks. Also, model-generated planograms are free from manual product selection and sorting errors. From an efficiency perspective, automatically creating and updating planograms will save the AITA™ team an average of 145 hours annually for every hospital served. These accuracy and efficiency gains will add value across the entire chain of care. The AITA™ team will have more time to grow their business and to develop new features. Meanwhile, providers will save time when managing and retrieving hospital inventory, which will free up more capacity for direct patient care.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2024

Author dc:creator

• Harihara, Caeley Gaw

Advisors dc:contributor.advisor

• Gray, Martha
• Zheng, Yanchong Karen

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/156045

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/156045