The shortage of medical personnel represents a significant challenge worldwide, impacting millions of people. In Peru, a study revealed that 43.72% of health facility managers identified the lack of human resources as the main obstacle in healthcare management, compounded by the lack of equipment, drugs, and problems associated with demand. The National Institute of Biomedical Imaging and Bioengineering (NIBIB) has underlined the crucial importance of CT scanners for the diagnosis of serious conditions such as hemorrhages and cancer. However, in Peru, the significant shortage of such equipment results in long waiting periods, with potentially life-threatening consequences if not addressed promptly. The centered moving average model is a tool with favorable results in terms of resource planning. However, it is important to develop the optimization of this model based on correlation of accuracy measures to understand this tool better and make improvements. The test performed showed that the accuracy measures and the length of the centered moving average model present high correlation coefficient with values of 0.924 for the MAPE, 0.888 for MAD and 0.863 for the MSD, all with p-value of 0.000 and a CI of 95%. Negative values of correlation were observed in terms of experimental error and the accuracy measures. Finally, the increase of the accuracy measures themselves presented values similar to the first mentioned relationship.