Predictive modeling of drug procurement for treatment of patients with chronic myeloid leukemia at the level of a constituent entity of the Russian Federation (exemplified by the Tyumen Oblast)

Introduction. Arranging procurement of drugs to provide pharmacotherapy for cancer patients is a focus area in the development of medicine and pharmacy. Large amounts of money are allocated to purchase drugs for the therapy of this group of patients. To save and rationally use financial resources, it is important to timely and accurately identify the needs and competently schedule the procurement. Aim. To develop prognostic models of drug procurement for the pharmacotherapy of patients with chronic myeloid leukemia in the Tyumen region till 2026. Materials and Methods. The data provided by the Tyumen Oblast Department of Health Care and the Tyumen Oblast Territorial Compulsory Medical Insurance Fund were used, as well as those obtained from Goszakupki, the unified information system in procurement. Scientific forecasting methods were used, namely: Trend extrapolation method and the normative predictive model building technique. Data were processed using computer technologies and mathematical methods. Results and Discussion. Based on the analysis of data on the procurement of medicines and the data provided, predictive models were built using scientific prognosis techniques, the changes in indicators were analyzed and the reasons for these changes were identified. Conclusions. Predictive models can be used to forecast procurement, provided that the forecast is made based on the need for a specific drug. The normative scientific prognosis method is more accurate, taking into account chain growth, as it allows tracing the dynamics of changes in the need, considering the balance of medicines at the end of the reporting period. The trend extrapolation method reflects only seasonality of changes in indicators.