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Top1. Introduction
The healthcare industry integrates sectors providing goods and services to care for people's health. Hospitals, a majority of this industry, must prepare enough resources, especially medicines, to ensure treatment quality. Unfortunately, they occasionally face shortages of some medicines, especially vital medicine, due to unpredictable excessive demand. To avoid shortage problems, they must increase buffer stock, which leads to an increase in inventory cost. Generally, the medicine inventory cost of each hospital was about twenty to thirty-five percent of the medical supplies budget (Jurado et al., 2016). Although higher buffer stock decreases the probability of shortage occurrence, it increases the probability of medicine to be expired. Therefore, reducing the effect of this irregular demand is challenging for small hospitals like most community hospitals. This study aims to develop a model which utilized a statistical approach to predict irregular demand and a purchasing policy to manage medicine inventory to reduce either shortage or medicine expired problems. Irregular demand can be classified as intermittent and slow-moving demand (Teunter & Sani, 2009; Teunter et al., 2011).
Most community hospitals have handled the irregular demand of medicine from their experience, such as by pharmacist expertise or based on the highest medical usage rate from the historical data, although inventory management software was available in fifty-six percent of all community hospitals (Kalaya et al., 2019b; Thai health coding center, n.d.; Ministry of Public Health Thailand, n.d.). The safety stock of medicine inventory management in the community hospital has been kept to serve the demand for two months (Kritchanchai & Srisakulwan, 2022). Thus, the higher the forecast demand, the greater is the overstock problem. In contrast, if forecast demand is lower than actual demand, a medicine shortage occurs, leading to poor service levels. Inventory management of medicine is a complicated procedure, particularly when it deals with various medicines with their context of use.
To handle irregular demand patterns, several attempts in various industry sectors were proposed. Williams (1984) and Costantino et al. (2018) suggested forecasting techniques for intermittent demand in the spare part industry. Synetotos & Boylan (2005) and Kourentzes (2014) proposed different demand forecasting techniques to handle intermittent demand patterns in the automotive industry, while Ghobbar & Friend (2003) also provides other techniques and related factors to predict irregular demand for spare parts in the aviation industry. Different forecasting techniques to predict irregular pharmaceutical demands were suggested by Kalaya et al. (2019a) and Kalaya et al. (2019b). Furthermore, Syntetos & Boyland (2008) introduced a periodic review and order-up-to-level policy to handle irregular demand for the aviation industry. On the other hand, both demand forecasting techniques and inventory control policy were recommended by Teunter & Sani (2009) based on the generated data set. It can be concluded that irregular demand patterns can be occurred in several industry sectors. Several methods have been proposed to effectively forecast as well as to provide an appropriate inventory control policy to handle irregular demand patterns.
This paper aims to propose appropriate forecasting techniques as well as inventory control policies to manage irregular demand patterns in the healthcare industry. The data used to conduct this research are real data from a community hospital and generated data sets to get more insights into several intermittent demand classifications. The performance indicators used to evaluate the performance of each approach proposed include 1) service level (SL) and 2) average inventory (AVI). These indicators are inverse aspects of other works focusing on the obsolescence problem because most demand sizes for spare parts were large and intermittent (Teunter et al., 2011; Babai et al., 2019). Nevertheless, the hospital's demand for vital medicines differs, and the shortage problem is a primary concern.