Medicine demand forecasting: an assessment of a private hospital in Pernambuco - Eduardo Fernando da Silva Souza; Antonio Reinaldo Silva Neto (Socioeconomic Analytics)
The efficient management of materials in the healthcare sector is crucial to avoid interruptions in the treatment of hospitalized patients, especially when demand is unpredictable and based on criteria of criticality, urgency and clinical status. In complex hospital environments with high-cost materials, demand forecasting becomes essential. This study aimed to compare demand forecast models for medicines used in the urgency and emergency sector of a private hospital in the Agreste Pernambucano. The methodology involves the selection of items and data collection using the company's information system. The ABC analysis identified 27 highly relevant drugs, and different models were tested, including experience-based parameters and hyperparameter optimization. The forecasts covered the period from January to November 2023. The results indicated the Holt-Winters Additive model as most suitable for 21 medications, Holt-Winters Multiplicative for 3, and ARIMA for the others, standing out for its precision. This study strengthens decision-making in the management of medication stocks, improving demand management and ensuring continuous treatments for patients.