Selection of element(s) of a prototype model of a medical organization in order to optimize the processes of a regional project using dynamic programming methods.

Changes in federal legislation regulating the provision of patients suffering from cardiovascular diseases initiate a revision of the regional legislation, and inevitably raises questions of practical adaptation and optimization of the processes of ongoing projects, taking into account resources in the established management model in medical organizations. Finding elements of a prototype model of a medical organization implementing a regional project as objects of influence for theoretical proof of hypotheses using the dynamic programming method (callback function, recursion) is the task of optimizing the project processes considered in this article. The purposeof the research question was to optimize the processes of a regional project using the dynamic programming method, which is focused on finding the objective function F(i) – the number of ways to return the function. The subgoal was to justify the use of dynamic programming methods. Materials and methods. The information base for the study was federal and regional regulatory legal acts published in the legislative reference and legal systems of the Russian Federation, and electronic resources. The study was carried out using methods of dynamic programming, optimization, recursion, and modeling. Results. We did not find similar studies in the available literature. This study was carried out using the dynamic programming method, which is designed to solve the problem of finding the target function(s) F(i) of regional projects. The authors attempted to find a prototype of an operating procedure at the level of project executors, which is indivisible and elementary for subsequent optimization of the variable (non-constant) elements of the prototype of a medical organization model from the found objective function. Finding F(i) by categories of patients (object of influence) registered at the dispensary, obtained using the callback function F(0), F(1), F(2), F(3), …F(k); F (0) ←F (1) ←F (2) ← F (3) ……F(n‑1) ← Fn (recursion) consists of decomposing the problem into smaller subproblems, finding the optimal solution to the subproblems recursively and using the resulting solution subtasks for constructing a solution to the original problem – optimizing an element of a prototype model of a medical organization, a regional project as a whole. Conclusion. The main tasks associated with project optimization are the tasks of minimizing the cost of the project for a given deadline for its implementation and minimizing (maximizing) the project completion period for a given marginal cost of its implementation. In search of a solution to optimization issues, the authors proposed finding F(i) by categories of patients (object of influence) registered as “D”, obtained using the callback function F (0) ←F (1) ←F (2) ← F (3) ……F(n‑1) ← Fn (recursion).