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Algorithm for making managerial decisions based on the assessment of the staffing of primary health care providers using the index method

https://doi.org/10.47470/0044-197X-2026-70-3-196-201

EDN: pxuijx

Abstract

Introduction. The provision of qualified personnel to medical institutions providing primary health care remains a significant problem in Russian healthcare, which necessitates a comprehensive assessment of personnel provision at the regional healthcare system level for subsequent rational planning of human resources.

The purpose of the study is to develop an algorithm for making managerial decisions in the field of healthcare personnel policy at the regional level based on the results of an analysis of the staffing of primary healthcare providers conducted using the index method.

Materials and methods. The research materials include the results of an analysis of the staffing of primary health care facilities by doctors over 2018–2022, using the methodology for calculating the human resources well-being index in healthcare developed by the team of authors at the Russian Research Institute of Health, which was modified for the study of human resources providing primary health care. The research base includes all regions of the Russian Federation. The methodological framework is based on organizational modeling and analytical methods.

Results. Based on the data on the values of the human resources well-being index in healthcare for 2022 and the trends in its development, there were identified four clusters, included the constituent entities of the Russian Federation that have similar characteristics of the human resources well-being index in healthcare. The grouping of regions into clusters allowed for a differentiated approach to making management decisions in the field of implemented human resources policy in healthcare at the regional level based on a specially developed algorithm.

Limitations of the study. The study materials are limited to the results of the analysis of staffing by primary health care physicians using the methodology for calculating the human resources well-being index in healthcare.

Conclusions. The use of the management decision-making algorithm provides an opportunity to choose the tactics of further actions by the executive authorities of the constituent entities of the Russian Federation in relation to the implemented personnel policy in healthcare at the regional level to improve the performance of medical institutions providing primary health care.

Compliance with ethical standards. This study does not require a conclusion from the Local Ethics Committee.

Contribution of the authors:
Senotrusova Yu.E. — collection and processing of material, statistical data processing, writing of the text;
Khodakova O.V. — editing;
Senotrusova Yu.E., Khodakova O.V. — research concept and design, approval of the final version of the article, responsibility for the integrity of all parts of the article.

Funding. The study had no sponsorship.

Conflict of interest. The authors declare the absence of any conflicts of interest regarding the publication of this paper.

Received: January 16, 2026 / Accepted: April 24, 2026 / Published: July 28, 2026

 

About the Authors

Yulia E. Senotrusova
Russian Research Institute of Health
Russian Federation

Senior researcher, Department of scientific foundations of healthcare organization, Russian Research Institute of Health, Moscow, 127254, Russian Federation

e-mail: senotrusovaye@mednet.ru



Olga V. Khodakova
Russian Research Institute of Health
Russian Federation

Dr. Sci., (Medicine), Professor, Head, Department of scientific foundations of healthcare organization, Russian Research Institute of Health, Moscow, 127254, Russian Federation

e-mail: khodakovaov@mednet.ru



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Senotrusova Yu.E., Khodakova O.V. Algorithm for making managerial decisions based on the assessment of the staffing of primary health care providers using the index method. Health care of the Russian Federation. 2026;70(3):196-201. (In Russ.) https://doi.org/10.47470/0044-197X-2026-70-3-196-201. EDN: pxuijx

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ISSN 0044-197X (Print)
ISSN 2412-0723 (Online)
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