Background: Several studies have been carried out with the objective of identifying health costs and developing methods to improve this research, thus contributing to better decision making based on more reliable evidence. However, there are some gaps to be filled to provide such information. This research aims to fill one of these gaps, proposing a cost calculation model for surgical hospitalizations based on real patient flow to determine hospital institutions' costs.Methods: An empirical-theoretical study was developed. The empirical approach adopted the three-step modeling process to propose a cost model based on patient flow, considering CHEERS guidelines. For the theoretical approach, a systematic literature review using PRISMA recommendation was applied.Results: The modeling process made it possible to identify the real flow of the surgical patient. This step made it possible to identify cost sources and comprehend that costs incurred by patient occur from admission (preoperative stage) to discharge (postoperative stage). The literature review showed that most studies only address the surgical stage, neglecting the costs of the two stages mentioned. The cost model was developed with a top-down approach allowing a balance between the accuracy of the information and the feasibility of the cost estimate. The proposed model fills two gaps in the literature, the standardization of a cost model and the ability to assess a vast number of different surgery costs in the same hospital.Conclusions: Flexibility stands out as an important advantage of the proposed model, as its application is possible to encompass elective and urgent surgeries of medium and high complexity performed in public and private hospitals. As a limitation, the hospital should have a HIS and cost system implemented. The proposed cost model can provide important information that can induce better decision making. This becomes more relevant in the health sector, especially public health, which faces the lack of resources and whose positive effects can improve health care.