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Classification of digital solutions for public health information management in the Russian Federation

https://doi.org/10.15829/1728-8800-2026-4886

EDN: XMPXGV

Abstract

Aim. To develop a methodological approach to the functional classification of healthcare digital solutions in the Russian Federation (RF), based on satisfying the information needs of healthcare entities, and to formulate a classification architecture.

Material and methods. The material was drawn from Russian and international information sources on methodological approaches to compiling digital solution classifications, strategic documents and regulatory legal acts of the Russian Federation regarding healthcare digital transformation, and a description of the digital solutions used in Russia. There were following methods: content analysis, systematization, and comparison.

Results. Using the developed methodological approach, a following three-level classification architecture for healthcare digital solutions was created for four groups of healthcare entities, their function groups, and the functions of the entities: 1) functions of healthcare managers — planning, management, monitoring, and control of the healthcare system, implementation of public policy, resource and financing management, and strategic development of the industry; 2) functions of health workers — professional activities, medical record maintenance, use of telemedicine, and interaction between specialists; 3) Patient functions — receiving care, using their medical information, remote services, feedback, and managing their health; 4) Functions of IT specialists — ensuring the regulatory, technological, and architectural development of healthcare digitalization, including data management, security, standardization, and analytics.

Conclusion. The developed digital solutions’ classification architecture will allow us to systematize existing digital solutions and identify gaps in the implementation of strategic decisions and regulatory defects.

About the Authors

O. M. Drapkina
National Medical Research Center for Therapy and Preventive Medicine; Russian University of Medicine
Russian Federation

Petroverigsky Lane, 10, bld. 3, Moscow, 101990,

Dolgorukovskaya str., 4, Moscow, 127006



R. N. Shepel
National Medical Research Center for Therapy and Preventive Medicine; Russian University of Medicine
Russian Federation

Petroverigsky Lane, 10, bld. 3, Moscow, 101990,

Dolgorukovskaya str., 4, Moscow, 127006



D. V. Voshev
National Medical Research Center for Therapy and Preventive Medicine
Russian Federation

Petroverigsky Lane, 10, bld. 3, Moscow, 101990



А. V. Korotkova
National Medical Research Center for Therapy and Preventive Medicine
Russian Federation

Petroverigsky Lane, 10, bld. 3, Moscow, 101990



R. O. Pugachev
Yaroslavl State Medical University
Russian Federation

Revolutsionnaya str., 5, Yaroslavl, 150000



D. S. Tyufilin
Russian Research Institute of Health
Russian Federation

Dobrolyubova str., 11, Moscow, 127254



T. D. Tarasenko
Russian Research Institute of Health
Russian Federation

Dobrolyubova str., 11, Moscow, 127254



References

1. Drapkina OM, Shepel RN. Features of medical care using te­le­medicine technologies: legal regulation and open questions. Rus­sian Journal of Preventive Medicine. 2019;22(3):5-13. (In Russ.) doi:10.17116/profmed2019220315. EDN: HOERBG.

2. Khanov AM, Gusev AV, Tyurganov AM. Prospects for the ap­pli­cation of artificial intelligence technologies for the digital trans­formation of healthcare. The Journal of telemedicine and ­e-­Health. 2024;10(3):70-6. (In Russ.) doi:10.29188/2712-9217-2024-10-3-70-76. EDN: BWSYDB.

3. Melerzanov AV, Almazov AA, Ivanova MA, et al. Classification of digital technologies and their impact on health indicators. Health care Standardization Problems. 2020;5-6:3-9. (In Russ.) doi:10.26347/1607-2502202005-06003-009.

4. Andrusov VE, Derbenev DP, Timoshevsky AA, et al. Aspects of ap­plication of digital solutions in primary health care. Problems of So­cial Hygiene, Public Health and History of Medicine. 2024; 32(2):1063-7. (In Russ.) doi:10.32687/0869-866X-2024-32-s2-1063-1067.

5. Lebedev GS, Shepetovskaya NL, Reshetnikov VA. Telemedicine and mechanisms of its integration. National Health Care (Russia). 2021;2(2):21-7. (In Russ.) doi:10.47093/2713-069X.2021.2.2.21-27.

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8. Rubtsov AV, Mamaeva SV, Khramova LN et al. Information sup­port of the organization's management system: textbook. Krasno­yarsk: Siberian Federal University. 2022. p. 111. (In Russ.) ISBN: 978-5-7638-4659-1.


What is already known about the subject?

  • Existing approaches to classifying digital solutions al­low to divide them into two following groups: clas­si­fications based on various technical charac­te­ris­tics and on functionality.
  • The vast majority of developed digital solutions clas­si­fications in healthcare are aimed at sys­te­ma­ti­zing existing digital solutions.

What might this study add?

  • The study developed a methodological approach to classifying digital resources in Russian healthcare. It is based on identifying four key groups of par­ti­ci­pants in the public healthcare system: healthcare ma­nagers at all levels, health workers, patients, and IT specialists. It also identifies their healthcare func­tions, for which digital resources meet their infor­mation needs.
  • The developed digital resource classification archi­tec­ture can help to systematize existing digital re­sour­ces, identify digital transformation gaps and re­gu­la­tory defects.

Review

For citations:


Drapkina O.M., Shepel R.N., Voshev D.V., Korotkova А.V., Pugachev R.O., Tyufilin D.S., Tarasenko T.D. Classification of digital solutions for public health information management in the Russian Federation. Cardiovascular Therapy and Prevention. 2026;25(5):4886. (In Russ.) https://doi.org/10.15829/1728-8800-2026-4886. EDN: XMPXGV

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ISSN 1728-8800 (Print)
ISSN 2619-0125 (Online)