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Artificial intelligence technologies in the activities of primary healthcare in Moscow
- Authors: Blokhina E.V.1, Bezymyannyy A.S.1
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Affiliations:
- Directorate for Coordination of Medical Organizations' activities
- Issue: Vol 5, No 1S (2024)
- Pages: 21-23
- Section: Articles by YOUNG SCIENTISTS
- Submitted: 12.02.2024
- Accepted: 13.03.2024
- Published: 03.07.2024
- URL: https://jdigitaldiagnostics.com/DD/article/view/626790
- DOI: https://doi.org/10.17816/DD626790
- ID: 626790
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Abstract
BACKGROUND: In recent years, the healthcare sector has emerged as a key area where artificial intelligence technologies are gaining strategic importance. In particular, the implementation of these technologies in primary healthcare has demonstrated particular relevance and importance [1–3].
AIM: The aim of the study is to characterize the stages of implementation of artificial intelligence technologies in the activities of urban polyclinics in Moscow.
MATERIALS AND METHODS: Analytical, statistical, socio-hygienic, and experimental methods were used.
RESULTS: The primary objective of integrating artificial intelligence into the operations of city polyclinics was to enhance the efficacy of medical data processing, mitigate the likelihood of professional missteps, and optimize the coordination of interactions between different medical professionals.
The initial challenge of processing a vast quantity of information was met by the implementation of artificial intelligence in the analysis of electronic medical records. This approach resulted in the development of integrated and secure systems that facilitate the accessibility of patient data to physicians and medical staff for the purpose of quality of care analysis.
In addressing the second task of using artificial intelligence technologies to provide consulting services to physicians in making a diagnosis, the work was carried out in several stages. In 2020, the top three medical decision support systems were implemented, which assist therapists in making preliminary diagnoses based on the International Classification of Diseases 10th revision (ICD-10).
Since 2023, the Diagnostic Assistant system, which analyzes data from a patient’s electronic medical record and offers a second opinion on a confirmed diagnosis, has been actively used. Currently, this system includes 95 codes of ICD-10 and similar diagnoses, with plans to expand its functionality to 268 diagnoses. As a consequence of the training and implementation of the expansion, the system will be capable of covering approximately 85% of the most frequently established confirmed diagnoses.
A considerable number of expert physicians were involved in the establishment and evaluation of the systems, with over 10,000 cases being handled.
In December 2023, a pilot project was conducted at the City Polyclinic No. 64 (Moscow) with the involvement of almost 100 doctors of this medical institution to identify the possibility of improving the reliability of the model. According to its results, it was found that the diagnoses made by the doctor and the artificial intelligence system coincide by 89%. Despite the impressive achievements of technology, it is important to emphasize that the use of artificial intelligence is not intended to replace the doctor, but rather serves as a second opinion in the work of a specialist.
CONCLUSIONS: The integration of artificial intelligence into the operations of Moscow’s polyclinics not only reduces the time required to search and process a substantial volume of information, but also helps to avoid professional errors. Furthermore, it enhances the efficiency of primary health care in Moscow as a whole.
Full Text
BACKGROUND: In recent years, the healthcare sector has emerged as a key area where artificial intelligence technologies are gaining strategic importance. In particular, the implementation of these technologies in primary healthcare has demonstrated particular relevance and importance [1–3].
AIM: The aim of the study is to characterize the stages of implementation of artificial intelligence technologies in the activities of urban polyclinics in Moscow.
MATERIALS AND METHODS: Analytical, statistical, socio-hygienic, and experimental methods were used.
RESULTS: The primary objective of integrating artificial intelligence into the operations of city polyclinics was to enhance the efficacy of medical data processing, mitigate the likelihood of professional missteps, and optimize the coordination of interactions between different medical professionals.
The initial challenge of processing a vast quantity of information was met by the implementation of artificial intelligence in the analysis of electronic medical records. This approach resulted in the development of integrated and secure systems that facilitate the accessibility of patient data to physicians and medical staff for the purpose of quality of care analysis.
In addressing the second task of using artificial intelligence technologies to provide consulting services to physicians in making a diagnosis, the work was carried out in several stages. In 2020, the top three medical decision support systems were implemented, which assist therapists in making preliminary diagnoses based on the International Classification of Diseases 10th revision (ICD-10).
Since 2023, the Diagnostic Assistant system, which analyzes data from a patient’s electronic medical record and offers a second opinion on a confirmed diagnosis, has been actively used. Currently, this system includes 95 codes of ICD-10 and similar diagnoses, with plans to expand its functionality to 268 diagnoses. As a consequence of the training and implementation of the expansion, the system will be capable of covering approximately 85% of the most frequently established confirmed diagnoses.
A considerable number of expert physicians were involved in the establishment and evaluation of the systems, with over 10,000 cases being handled.
In December 2023, a pilot project was conducted at the City Polyclinic No. 64 (Moscow) with the involvement of almost 100 doctors of this medical institution to identify the possibility of improving the reliability of the model. According to its results, it was found that the diagnoses made by the doctor and the artificial intelligence system coincide by 89%. Despite the impressive achievements of technology, it is important to emphasize that the use of artificial intelligence is not intended to replace the doctor, but rather serves as a second opinion in the work of a specialist.
CONCLUSIONS: The integration of artificial intelligence into the operations of Moscow’s polyclinics not only reduces the time required to search and process a substantial volume of information, but also helps to avoid professional errors. Furthermore, it enhances the efficiency of primary health care in Moscow as a whole.
About the authors
Ekaterina V. Blokhina
Directorate for Coordination of Medical Organizations' activities
Author for correspondence.
Email: lebedeva488@gmail.com
ORCID iD: 0009-0000-1620-8293
Russian Federation, Moscow
Alexey S. Bezymyannyy
Directorate for Coordination of Medical Organizations' activities
Email: bezpromo@ya.ru
ORCID iD: 0000-0002-3685-9111
SPIN-code: 9362-1390
Russian Federation, Moscow
References
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- Khusanov UA, Kudratillaev MB, Siddikov BN, Dovletova SB. Artificial intelligence in medicine. Science and Education. 2023;4(5):772–782.
- Ryazanova SV, Komkov AA, Mazaev VP. Russian and world experience in the application of new artificial intelligence technologies in real medical practice. Nauchnoe obozrenie. Meditsinskie nauki. 2021;(6):32–40. EDN: FIBIWT doi: 10.17513/srms.1215
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