Importance of artificial intelligence for procurement of medicine in hospitals

Hospitals face immense burden due to high demand for care, variations in hospital management, rapid changes in clinical cases, and demand uncertainty, all of which increase the complexity of the healthcare processes. It has become very challenging for the hospital management to provide high-quality service efficiently, i.e., with the optimal allocation of resources (i.e., medical, and surgical supplies, well-maintained facilities, and skilled staff).

While the complexities in the healthcare industry are increasing daily, the cost of producing quality care is also increasing. Therefore, effective management of logistics activities in a hospital helps to produce quality outcomes, by overcoming these challenges while reducing the cost of operations. Among the logistics processes in a hospital, inventory and procurement management of medical and surgical supplies plays a critical role because a hospital requires stocked supplies to produce quality care at the right time; otherwise, it may have fatal consequences. The variety of surgical and medical supplies requirement is substantially high and different for divergent procedures.

At the same time, hospitals are affected by demand uncertainty due to unexpected changes in diseases and new developments in medical knowledge. Supply uncertainty due to unreliable sources also affects the service level. Strong regulatory forces make an impact on inventory management because that drives hospital management to inaccurate demand forecasts. Because they tend to keep very high safety stocks, which may expire before consumption. Moreover, hospitals regularly tighten the budget and work with limited storage capacity.

Finally, the behavioural influence of stakeholders, such as physician prescribing patterns, can also be considered a cause of demand uncertainty. Demand patterns of these items are highly volatile, noisy, and non-stationary due to these complexities and uncertainties. Hence, forecasting inventory has become a challenging job in healthcare. Hospitals tend to use simple inventory models to forecast without considering the uncertainties that exist in the industry has resulted in inefficient solutions. A dearth of scholarly work conducted in hospital inventory management and has developed several models using different techniques to increase the efficiency of hospital inventory and procurement management.

New research is conducted to seek more practical approaches using Artificial Intelligence (AI) techniques in this context. Extreme demand patterns are regularly seen in healthcare inventory but are challenging to model. Existing simple inventory and procurement models in hospitals consider stationary demand for decision making and end up with low-quality decisions.

This study aims to develop advanced AI-based models to improve inventory and procurement management decision-making, two essential healthcare logistics processes. These models are developed to capture hospitals' dynamic and uncertain environment, impacting inventory and procurement decisions. The key objective is to assure the availability of medical and surgical items in a hospital at the right time to treat patients. As managerial implications, we propose AI-based decision support models to reduce inventory and procurement-related costs while assuring a continuous supply of medical and surgical items without shortages.

We are working on two research projects to automate decision-making in healthcare logistical procedures (i.e., inventory management and procurement management). The first study uses AI techniques to improve hospital inventory management decisions, and the second uses the same methodologies to improve procurement contracts that account for demand uncertainty.

AI is now being used in hospitals from diagnosis to treatment of patients and has shown efficient and effective results in service delivery. AI in logistics management in hospitals generates a data-driven environment to improve incredibly complex processes and deliver high-quality patient care.

Additionally, the use of AI in medicine logistics will optimize the response to uncertainty in demand for the medicines. It will help reduce the cost of procurement while ensuring availability. This research towards automation of inventory and procurement management of medication in hospitals using AI techniques will improve the healthcare industry and, therefore, the quality of service delivery.