Artificial Intelligence driven Surgical Stock Management: Wastage Prevention

The healthcare industry within the UK is one that heavily depends on inventory, with billions invested each year to ensure high quality care standards are achieved. Medical supplies keep the hospitals functioning but fit an exhaustive bill to meet the demands of each department and provide day to day treatment to patients on arrival. Weiss et. al reported around 60% of hospital budgets go on operating room costs, with around 25% of hospital waste being generated there[1]. Despite the consumption, they also significantly contribute to the revenue stream within healthcare. The current state of the healthcare industry carries constant pressure to reduce costs whilst still improving and maintaining the quality of care and efficiency. With over 3 million surgical procedures carried out in the year 2020 [2], improving efficiency in surgery is one area that can be targeted. Currently, the NHS finds itself in financial hardships leading to longer surgery waiting times partly due to a lack of surgical equipment, particularly with the effects of Brexit and the Covid-19 Pandemic [3]. The planned budget for NHS England in 2023/24 is due to increase by £20.5bn [4], where some would query why financial targets are not being met and budgets often overspent, leaving the NHS heavily in the 'red'. Productivity analysis is crucial in today's climate and the exploration into improving the management of medical supplies and its logistics may be a realistic topic to explore for a solution to these financial issues. A great way to overcome financial struggles and inefficiencies within healthcare, is to employ the use of inventory management systems (IMS).
An IMS of medical devices serves to manage the acquisition, tracking, forecasting, storage and utilisation of equipment required to keep the hospital trust running. It upholds the efficient management of equipment levels to ensure stock availability, whilst minimizing excess stock that can become obsolete or expired. The clear goal of an IMS is to 1. Ensure availability of medical devices to maintain the efficient running of surgical procedures and minimize delays or cancellations; 2. Optimise inventory levels, by striking the best balance of having sufficient stock to meet the demands of surgical procedures and avoiding excess stock. 3. Controlling costs and reducing wasted expenditure. To achieve the 3 mentioned goals, hospital trusts employ IMSs to automate processes that allow real-time tracking using engineered software that provides accurate data on expiration dates of inventory, stock levels and utilisation patterns to enable better decision making prior to restocking. Demand forecasting is another feature that enables IMSs to support the efficient running of hospitals.
The addition of digital technologies and Artificial Intelligence offers significant benefits to the design framework and implementation of an IMS. The ability to automate daily tasks within the healthcare setting helps to improve efficiency, reduce costs and relieves staff to focus on more pressing clinical tasks.
The aim of this research is to identify the main causes of medical waste and design a solution using AI to reduce the waste; with a goal to create a model that can be applied to multiple medical settings and departments. The objectives are to firstly explore whether the amount of waste can be measured, and what techniques are currently in place to achieve it. Secondly, there is great value in understanding the role AI and digital technology play within the Surgical Inventory Management industry, its applications, benefits and limitations. With this we can further understand which medical specialties serve to gain the most when employing an IMS with the addition of AI, and thus create a fitting solution.
Furthermore, the research questions derived from the aims of this study are as follows: Research Question 1: Can we quantify waste that occurs from unused and expired surgical inventory waste? Question 2: Can w