Optimization through Inventory Models in Meficaments and Supplies in Iess Hospitals

Abstract

Inventory management and price control of medicines and medical supplies in the hospitals of the Ecuadorian Social Security Institute (IESS) faces significant challenges at the national level, which highlights the need to implement optimization software. The objective of this study was to design software that optimizes economic resources and supports the management of inventory models within hospital planning. The methodological approach was mixed, combining quantitative and qualitative techniques, which allowed iterations to be carried out in each inventory model within the software until the robust validation of the equations applied in the system was obtained.

The study was carried out in 12 IESS hospitals in Ecuador, located in cities with a high concentration of inhabitants and affiliates such as Quito, Guayaquil, Cuenca, Ambato, Santo Domingo, Manta, Machala, Portoviejo, Durán and Quevedo. The database used was obtained from the web portal of the National Public Procurement Service (SERCOP). Statistical analyses using ANOVA tests revealed significant fluctuations in drug purchases during the years 2017 to 2020, with a p-value of 0.000925, confirming substantial differences. Likewise, important variations were observed in medical supplies, with a p-value of 0.00275 when comparing the means. Significant differences were also identified between the means of the different IESS hospitals, with a p-value lower than 2e-16, evidencing the heterogeneity in the management of supplies and medicines among these hospitals.

The software developed incorporates mathematical calculations in various deterministic and probabilistic models, optimizing inventory management through reliable data to calculate the economic quantity of orders and establish reorder points, adjusting to variations in demand and delivery times. In addition, the software monitors purchase prices, ensuring that they are made at reference prices, which is crucial to strengthen strategic decision-making in IESS hospitals.