Predicting the probability of failure in medicinesʼ public procurement

The quality and timeliness of medicinesʼ supply to the healthcare system through public procurement is an urgent task of public policy in all countries of the world, including Russia. Failure to close (failure of tenders, termination of already concluded contracts) procurement procedures in such a socially significant area carries risks for the population, provokes the emergence of hidden transaction costs for the budget system to eliminate the consequences of procurement failures. In their previous works, the authors identified the factors that lead to the failure to close tenders for the purchase of remedies, and initially assessed the consequences of their influence on procurement procedures. The purpose of this article is to present a mathematical model of the probability of non-closure tenders based on the obtained results. To achieve this goal, through processing more than 1 million notifications of public procurement of remedies for 2022–2023, collected from the open sources, the tasks with no methodological solutions were completed. Thus, a set of features accompanying the failure to close procedures for the purchase of remedies was compiled. The composition of identified features was analyzed; their influence on non-closure of the procedure was assessed. A model of the probability of non-closure of the procedure was constructed, and the results were interpreted. Unlike previously published studies, the forecast model was implemented on the ensembles of decision trees using gradient boosting. This made possible to significantly improve the quality of the forecast for each factor affecting the probability of non-closure of the bidding. The results obtained in the article are not only scientifically novel, but can also be used by regulatory and control bodies in public procurement to develop methodological recommendations for customers on establishing optimal conditions for concluding and fulfilling contracts, which will reduce procurement risks and damage to the state budget.

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Publication Details

Journal
Economics and Mathematical Methods
Published
2024-11-11
DOI
https://doi.org/10.31857/s0424738824040066
Primary Topic
Pharmaceutical Economics and Policy
Type
article
Field-Weighted Citation Impact
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article

Predicting the probability of failure in medicinesʼ public procurement

Д. А. Созаева, A. I. Denisova, G. A. Aleksandrov, K. V. Gonchar
Economics and Mathematical Methods
Pharmaceutical Economics and Policy
article

Predicting the probability of failure in medicinesʼ public procurement

Д. А. Созаева, A. I. Denisova, G. A. Aleksandrov, K. V. Gonchar
article en

Abstract

The quality and timeliness of medicinesʼ supply to the healthcare system through public procurement is an urgent task of public policy in all countries of the world, including Russia. Failure to close (failure of tenders, termination of already concluded contracts) procurement procedures in such a socially significant area carries risks for the population, provokes the emergence of hidden transaction costs for the budget system to eliminate the consequences of procurement failures. In their previous works, the authors identified the factors that lead to the failure to close tenders for the purchase of remedies, and initially assessed the consequences of their influence on procurement procedures. The purpose of this article is to present a mathematical model of the probability of non-closure tenders based on the obtained results. To achieve this goal, through processing more than 1 million notifications of public procurement of remedies for 2022–2023, collected from the open sources, the tasks with no methodological solutions were completed. Thus, a set of features accompanying the failure to close procedures for the purchase of remedies was compiled. The composition of identified features was analyzed; their influence on non-closure of the procedure was assessed. A model of the probability of non-closure of the procedure was constructed, and the results were interpreted. Unlike previously published studies, the forecast model was implemented on the ensembles of decision trees using gradient boosting. This made possible to significantly improve the quality of the forecast for each factor affecting the probability of non-closure of the bidding. The results obtained in the article are not only scientifically novel, but can also be used by regulatory and control bodies in public procurement to develop methodological recommendations for customers on establishing optimal conditions for concluding and fulfilling contracts, which will reduce procurement risks and damage to the state budget.

Economics and Mathematical MethodsVol. 60(4)
State University of Management (RU)
Peace, Justice and strong institutions
Openalex Percentile: Top 76%
Pharmaceutical Economics and Policy
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