vitjВрач и информационные технологииMedical Doctor and Information Technologies1811-01932413-5208Pirogov National Medical and Surgical Center10.25881/18110193_2025_2_54vitj-83Research ArticleОРИГИНАЛЬНЫЕ ИССЛЕДОВАНИЯORIGINAL RESEARCHПодход к разработке модульной архитектуры базы данных в области интенсивной терапии и реанимацииAn approach for modular database architecture design in the intensive care unithttps://orcid.org/0009-0006-3082-3499ГлушковВ. С.GlushkovV. S.

Вениамин Сергеевич Глушков, к. м. н.

Тюмень

PhD

Tyumen

glushkovvs@tyumsmu.ruhttps://orcid.org/0000-0002-0649-4342ВдовинЕ. П.VdovinE. P.

Евгений Петрович Вдовин, д. ф.-м. н., доцент

Тюмень

DSc, Associate Professor

 Tyumen

e.p.vdovin@utmn.ruЕрмаковН. В.ErmakovN. V.

Николай Владимирович Ермаков

Тюмень

Tyumen

n.ermakov@innovalab.ruhttps://orcid.org/0009-0002-0979-9173БакановскаяЛ. Н.BakanovskayaL. N.

Людмила Николаевна Бакановская, к. т. н., доцент

Тюмень

PhD, Associate Professor

Tyumen

l.n.bakanovskaya@utmn.ruhttps://orcid.org/0000-0002-9943-1243ЧернышеваТ. Ю.ChernyshevaT. Yu.

Татьяна Юрьевна Чернышева, к. т. н., доцент

Тюмень

PhD, Associate Professor

Tyumen

t.y.chernysheva@utmn.ruhttps://orcid.org/0009-0001-8677-7472КравецВ. Д.KravetsV. D.

Виктория Дмитриевна Кравец, студент бакалавриата

Тюмень

Tyumen

vkravets03@gmail.comhttps://orcid.org/0009-0003-1479-9597СоболевИ. С.SobolevI. S.

Илья Сергеевич Соболев, студент магистратуры

Тюмень

Tyumen

ilia.sobolev2014@yandex.ruhttps://orcid.org/0009-0002-9762-5500ВолковД. Е.VolkovD. E.

Дмитрий Евгеньевич Волков, студент магистратуры

Тюмень

Tyumen

vbnzwolf@gmail.comhttps://orcid.org/0009-0001-7985-7685МиляевМ. В.MilyaevM. V.

Михаил Владимирович Миляев, студент бакалавриата

Тюмень

Tyumen

epev.nd@mail.ruФГБОУ Тюменский ГМУ Минздрава РоссииРоссияFederal State Budgetary Educational Institution of Higher Education "Tyumen State Medical University" of the Ministry of Health of the Russian FederationRussian FederationФГАОУ ВО «Тюменский государственный университет»РоссияUniversity of TyumenRussian FederationООО "Ин Нова"Россия"In Nova" LLCRussian FederationФГАОУ ВО «Тюменский индустриальный университет»РоссияIndustrial University of TyumenRussian Federation202513062025025469Copyright © Глушков В.С., Вдовин Е.П., Ермаков Н.В., Бакановская Л.Н., Чернышева Т.Ю., Кравец В.Д., Соболев И.С., Волков Д.Е., Миляев М.В., 20252025Глушков В.С., Вдовин Е.П., Ермаков Н.В., Бакановская Л.Н., Чернышева Т.Ю., Кравец В.Д., Соболев И.С., Волков Д.Е., Миляев М.В.Glushkov V.S., Vdovin E.P., Ermakov N.V., Bakanovskaya L.N., Chernysheva T.Y., Kravets V.D., Sobolev I.S., Volkov D.E., Milyaev M.V.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.vit-j.ru/jour/article/view/83

   В статье представлено проектирование базы данных, предназначенной для оптимизации хранения и обработки медицинских данных, с акцентом на поддержку принятия решений в области интенсивной терапии и реанимации.

   Целью исследования является разработка логической модели базы данных на основе передовых принципов и методов, используемых в международных проектах открытых баз данных, способной минимизировать ошибки, связанные с человеческим фактором, и улучшить точность прогноза состояния пациентов в реальном времени.

   Методология работы основана на сравнительном анализе существующих международных медицинских баз данных, таких как MIMIC-IV и eICU. Для проектирования новой базы данных применен инновационный модульный подход, который обеспечивает гибкость и масштабируемость системы. Основные результаты работы заключаются в создании логической модели базы данных, которая может быть эффективно использована в российской системе здравоохранения, в том числе в удаленных и малоресурсных регионах. Логическая модель разработана с учётом специфики медицинских данных, включая модули для хранения информации о госпитализациях, показателях состояния пациентов, лабораторных исследованиях, медикаментозных назначениях и других аспектах клинической практики. Важной частью исследования является интеграция базы данных с российскими медицинскими информационными системами и адаптация к национальным стандартам и нормативным требованиям. Созданная архитектура логической модели минимизирует влияние человеческого фактора, автоматизирует анализ данных и может использоваться в разработке систем поддержки принятия врачебных решений. Практическая значимость заключается в повышении качества медицинской помощи и снижении нагрузки на персонал. Система применима в российских учреждениях, включая удаленные регионы, и способствует цифровизации здравоохранения.

   This article presents the design of a database intended to optimize the storage and processing of medical data, with a focus on decision support in intensive care and resuscitation.

   The aim of the study is to develop a logical database model based on advanced principles and methods used in international open database projects, capable of minimizing human error and enhancing the accuracy of real-time patient prognosis.

   The methodology is founded on a comparative analysis of existing international medical databases, such as MIMIC-IV and eICU. An innovative modular approach was applied in designing the new database, ensuring system flexibility and scalability. The primary outcome is the creation of a logical database model that can be effectively utilized within the Russian healthcare system, including remote and low-resource regions. The logical model was developed taking into account the specifics of medical data, including modules for storing information on hospitalizations, patient condition indicators, laboratory tests, medication prescriptions and other aspects of clinical practice. An important part of the study is the integration of the database with Russian medical information systems and adaptation to national standards and regulatory requirements. The developed architecture of the logical model minimizes the influence of the human factor, automates data analysis and can be used in the development of medical decision support systems. The practical significance lies in improving the quality of medical care and reducing the burden on the staff. The system is applicable in Russian institutions, including remote regions, and contributes to the digitalization of healthcare.

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The authors declare that there are no conflicts of interest present.