farmaecFARMAKOEKONOMIKA. Modern Pharmacoeconomics and PharmacoepidemiologyФАРМАКОЭКОНОМИКА. Современная фармакоэкономика и фармакоэпидемиология2070-49092070-4933IRBIS LLC10.17749/2070-4909/farmakoekonomika.2023.184farmaec-829Research ArticleORIGINAL ARTICLESОРИГИНАЛЬНЫЕ ПУБЛИКАЦИИDevelopment of methodological approaches to the formation of a risk-based model to minimize the prevalence of adverse reactions in drug application in medical organizations of MoscowРазработка методических подходов к формированию риск-ориентированной модели для минимизации возникновения нежелательных реакций при применении лекарственных препаратов в медицинских организациях города Москвыhttps://orcid.org/0000-0002-1262-4430КузнецоваЕ. В.KuznetsovaE. V.

Кузнецова Елена Викторовна – заведующая организационно-методическим отделом по клинической фармакологии

ул. Шарикоподшипниковская, д. 9, Москва 115088

Elena V. Kuznetsova – Head of the Organizational and Methodological Department of Clinical Pharmacology

9 Sharikopodshipnikovskaya Str., Moscow 115088

https://orcid.org/0000-0002-9198-8661ЖуравлеваМ. В.ZhuravlevaM. V.

Журавлева Марина Владимировна – д.м.н., профессор кафедры клинической фармакологии и пропедевтики внутренних болезней; заместитель директора Центра клинической фармакологии; главный внештатный специалист по клинической фармакологии

Сеченовский университет) (ул. Трубецкая, д. 8/2, Москва 119048

Петровский б-р, д. 8, стр. 2, Москва 127051

Scopus Author ID: 55878917900

Marina V. Zhuravleva – Dr. Med. Sc., Professor, Chair of Clinical Pharmacology and Propaedeutics of Internal Diseases; Deputy Director, Center of Clinical Pharmacology; Chief Freelance Specialist

8/2 Trubetskaya Str., Moscow 119991

8 bldg 2 Petrovskiy Blvd, Moscow 127051

Scopus Author ID: 55878917900

https://orcid.org/0000-0001-8020-369XМихайловИ. А.MikhailovI. A.

Михайлов Илья Александрович – главный специалист отдела организационно-методического обеспечения поддержки деятельности национальных медицинских исследовательских центров; ассистент кафедры организации здравоохранения и общественного здоровья с курсом оценки технологий здравоохранения;  аспирант

Хохловский пер., д. 10/5, Москва 109028

ул. Баррикадная, д. 2, стр. 1, Москва 123995

ул. Воронцово поле, д. 12, стр. 1, Москва 105064

WoS ResearcherID: I-9035-2017

Scopus Author ID: 57203900904

Ilya A. Mikhailov – Chief Expert, Department of Organizational and Methodological Support for the Activities of National Medical Research Centers; Assistant Professor, Chair of Healthcare Organization and Public Health with a Course in Health Technology Assessment; Postgraduate

10/5 Khokhlovskiy Passage, Moscow 109028

2/1 bldg 1 Barrikadnaya Str., Moscow 123242

12 bldg 1 Vorontsovo Pole Str., Moscow 105064

WoS ResearcherID: I-9035-2017

Scopus Author ID: 57203900904

mikhailov@rosmedex.ruКурносоваТ. И.KurnosovaT. I.

Курносова Татьяна Игоревна – заместитель начальника отдела организационно-методического обеспечения поддержки деятельности национальных медицинских исследовательских центров

Хохловский пер., д. 10/5, Москва 109028

Tatiana I. Kurnosova – Deputy Head of Department of Organizational and Methodological Support for the Activities

10/5 Khokhlovskiy Passage, Moscow 109028

Государственное бюджетное учреждение г. Москвы «Научно-исследовательский институт организации здравоохранения и медицинского менеджмента» Департамента здравоохранения г. МосквыРоссияResearch Institute for Healthcare Organization and Medical ManagementRussian FederationФедеральное государственное автономное образовательное учреждение высшего образования «Первый Московский государственный медицинский университет им. И.М. Сеченова» Министерства здравоохранения Российской Федерации; Федеральное государственное бюджетное учреждение «Научный центр экспертизы средств медицинского применения» Министерства здравоохранения Российской ФедерацииРоссияSechenov University; Scientific Center for Expert Evaluation of Medicinal ProductsRussian FederationФедеральное государственное бюджетное учреждение «Центр экспертизы и контроля качества медицинской помощи» Министерства здравоохранения Российской Федерации; Федеральное государственное бюджетное образовательное учреждение дополнительного профессионального образования «Российская медицинская академия непрерывного профессионального образования»; Федеральное государственное бюджетное научное учреждение «Национальный научно-исследовательский институт общественного здоровья им. Н.А. Семашко»РоссияCenter for Healthcare Quality Assessment and Control; Russian Medical Academy of Continuing Professional Education; Semashko National Research Institute of Public HealthRussian FederationФедеральное государственное бюджетное учреждение «Центр экспертизы и контроля качества медицинской помощи» Министерства здравоохранения Российской ФедерацииРоссияCenter for Healthcare Quality Assessment and ControlRussian Federation202319072023162248257Copyright © Kuznetsova E.V., Zhuravleva M.V., Mikhailov I.A., Kurnosova T.I., 20232023Кузнецова Е.В., Журавлева М.В., Михайлов И.А., Курносова Т.И.Kuznetsova E.V., Zhuravleva M.V., Mikhailov I.A., Kurnosova T.I.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.pharmacoeconomics.ru/jour/article/view/829Objective

Objective: development of approaches to predict the likelihood of adverse reactions (ARs) when using drugs based on a comprehensive assessment of risk factors.

Material and methods

Material and methods. We used a database containing 1,450 drug-related ARs reports from January through December 2021. A list of antibacterial drugs by international nonproprietary name (INN) with 4 or more ARs reports was selected as a reference group to perform various types of statistical analysis. A cumulative multivariate regression analysis was carried out on a database of 187 ARs notifications for 13 INN of antibacterial drugs. The study was performed in two stages. In the first stage, a statistical method was used (classical multiple regression, linear discriminant analysis, factor analysis, principal component regression, partial least squares regression, estimation of variance accuracy); at the second stage a modeling method was used. As part of the modeling stage, the integral score of the risk of ARs was presented as a sum of values for individual risk factors. Two groups of risks were proposed to be assessed: 1) intrinsic risk value for each factor (attribute), which was equal to the sum of risks of all factors (conditions) in which the drug had been used; 2) intrinsic risk value for antibacterial drugs by each INN. The total risk value was defined as the sum of the risk of the drug and all factors (conditions) in which this drug had been used.

Results

Results. The results were visualized in the form of a two-level risk-based model matrix, with a “heat map” of the risk level overlaid on it. The maximum total risk of ARs was obtained for ceftriaxone – 404.96 points, depending on patient’s gender. The minimum total risk was calculated for azithromycin and cefotaxime depending on the International Classification of Diseases (10th revision) code – 88.46 points. The proposed methodological approach also allows combining all possible combinations of drugs and conditions of their use. For example, for the use of vancomycin in hospital conditions by intravenous administration: intrinsic risk of use – 42.93 points; risk of use in hospital conditions – 183.68 points; risk when administered intravenously – 209.95 points; the total risk value in the designated situation – 436.56 points.

Conclusion

Conclusion. The proposed approach can allow medical organizations to reduce significantly the number of ARs when using drugs by categorizing and preventing risks before they occur. It also has significant prospects of application at the federal level, given its modification on a large volume of data.

Цель

Цель: разработка подходов, позволяющих прогнозировать вероятность возникновения нежелательных реакций (НР) при применении лекарственных препаратов (ЛП) на основе комплексной оценки факторов риска.  

Материал и методы

Материал и методы. Использовали базу данных, содержащую 1450 извещений о НР при применении ЛП, поступивших с января по декабрь 2021 г. включительно. В качестве эталонной группы для выполнения различных видов статистического анализа был выбран перечень антибактериальных ЛП по международному непатентованному наименованию (МНН), количество извещений о возникновении НР по которым составляет 4 и более. Суммарно многофакторный регрессионный анализ выполнен на базе данных из 187 извещений о возникновении НР по 13 МНН антибактериальных ЛП. Исследование выполняли в два этапа. На первом этапе применяли статистический метод (классическая множественная регрессия, линейный дискриминантный анализ, факторный анализ, регрессия главных компонент, частичная регрессия методом наименьших квадратов, оценка точности дисперсий), на втором этапе – метод моделирования. В рамках этапа моделирования использовали методику балльной интегральной оценки риска возникновения НР, представленного в виде суммы значений по отдельным факторам риска. Предлагается проводить оценку рисков по двум группам: 1) собственное значение риска для каждого фактора (признака), равное сумме рисков всех факторов (условий), при которых применяется ЛП; 2) собственное значение риска для антибактериальных ЛП по каждому МНН. Суммарное значение риска определяется как сумма риска ЛП и всех факторов (условий), при которых этот ЛП применяется.  

Результаты

Результаты. Результаты визуализированы в виде двухуровневой матрицы риск-ориентированной модели, на которую наложена «тепловая карта» уровня риска. Максимальное суммарное значение риска возникновения НР получено для цефтриаксона – 404,96 балла в зависимости от пола пациента. Минимальное суммарное значение риска рассчитано для азитромицина и цефотаксима в зависимости от кода по Международной классификации болезней 10-го пересмотра – 88,46 балла. Предложенный методический подход также позволяет комбинировать все возможные сочетания ЛП и условий их применения. Например, для применения ванкомицина в стационарных условиях путем внутривенного введения: собственный риск применения – 42,93 балла, риск применения в стационарных условиях – 183,68 балла, риск при внутривенном введении – 209,95 балла, суммарное значение риска в обозначенной ситуации – 436,56 балла. 

Заключение

Заключение. Предложенный подход может позволить медицинским организациям значительно сократить количество случаев возникновения НР при применении ЛП путем категоризации и предотвращения рисков до их появления. Он также обладает значительными перспективами использования на федеральном уровне при условии его модификации на большом объеме данных.

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