Real-time solution for automated inventory monitoring of antiretroviral medicines: case of Nairobi County

Abstract

Cases of stockouts and expiry of Antiretroviral Therapy medicines are occurring and this is due the fact that the current inventory monitoring systems for Antiretroviral Therapy Medicines and commodities are manual despite the use of electronic systems for the ordering and issuing of the same. This research proposed a real-time inventory control and monitoring model to address the challenges. The model uses fuzzy logic through a fuzzy inference engine to predict the appropriate quantity level on when to place an order so as to reduce the probability of a stockout occurring. The model uses a continuous review technique to monitor the quantity of the medicines in real-time as they are being issued or received. The model gives immediate notification when a reorder point for a particular inventory item is reached. The model is also able to monitor product lifetime of the medicines to ensure those concerned are informed when medicines in inventory have expired and need to be replaced. The model is validated through the implementation of a web-based system which is then tested against the propositions of model to confirm it works as expected. The tests on the system yielded a positive validation of the model. The fuzzy inference engine’s accuracy of predictions was tested using the Random Mean Square Error method and it yielded a standard deviation error result of 4.3% from a set of actual test data sets. The model was then compared against other existing models and it was proven that the model developed in this research is the most appropriate for the monitoring of Antiretroviral Therapy medicines and commodities.