Comparative review of methodologies for estimating the cost of adverse drug reactions in the Russian Federation and Brazil

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The aim of the review article was to highlight the methodologies for assessing the financial costs of adverse drug reactions exemplified by the Russian Federation and Brazil.

Materials and methods: for a comparative analysis, materials from open sources were used. The study of the experience of methods used for assessing the burden of adverse drug reactions, was carried out using the system for calculating payments for medical care by clinical-statistical and clinical-profile groups, the methodology for assessing the severity of adverse events of the US National Cancer Institute, drug-associated problems, and “the decision tree” model.

Results. When comparing the costs of ADR management in the Russian Federation and Brazil, the following results have been obtained: in the Russian Federation, the “cost” of reaction can be estimated only for a limited number of nosological groups that are regulated by the classification of diseases by clinical and statistical groups; in Brazil, when predicting the costs of adverse reactions management, the combination of “the decision tree” method and the Delphi method is used. In the Russian Federation, the cost of the 3rd and above severity adverse event (according to CTCAE v. 4.03), varies from 26,849.22 up to 26,196.37 RUB in the North-West region (St. Petersburg). In Brazil, the cost of ADR ranges from 13 USD (the best scenario for the patient) to 574 USD (the worst scenario for the patient), which is about 975 and 43,000 RUB, respectively. The introduction of methods that make it possible to predict the development and potential outcomes of adverse drug reactions, as well as taking into account the experiences of foreign colleagues in their modeling, will reduce economic costs in the Russian Federation at the federal level.

Conclusion: for the economic value analysis and further forecasting, an improvement of existing methodologies is required. The models used in the Russian Federation (“the decision tree”, classification of diseases by clinical groups, Markov model) do not take into account the time factor, therefore, when planning the analysis of potential costs for adverse reactions, it is necessary to reinforce the methods with such tools as QALY, YLL, and YLD.

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Abbreviations: ADRs – Adverse drug reactions; AIS – Automatic information system; CICU – Critical and intensive care unit; ALV – artificial lung ventilation; ARCADe – Adverse Reactions in Crimea, Autonomic Database; AWF – average weight factor; CPG – Clinical profile group; CSG – Clinical statistic group; DALY – Disability Adjusted Life Year; DRM – Drug-Related Morbidities; DRP – Drug Related Problems; GBD – Global Burden of Disease; GTA – General Tariff Agreement; HLE – Healthy Life Expectancy; ICU – intensive care unit; MedDRA – Medical Dictionary for Drug Regulatory Affairs; MMR – Maternal Mortality Ratio; MS – Medical substance; NMP – New Medical Problem; NPS – National Pharmacovigilance System; PCNE – Pharmaceutical Care Network Europe; PE – Pharmacoeconomics; PSG – The program of state guarantees of free provision of medical care to citizens; QALY – Quality-adjusted life year; SADR – Serious Adverse Drug Reaction; SAR – Serious Adverse Reaction; SGBP – Program of state guarantees for free provision of medical care to citizens; SOFA – Sequential Organ Failure Assessment; SUS – Sistema Unico de Sau; SUSAR – Suspected Unexpected Serious Adverse Reaction; TF – Treatment Failure; UADR – Unexpected Adverse Drug Reaction; UAE – Unexpected adverse events; USD – United States dollar; WACIF – Weighted average cost intensity factor; YLL – Years of Life Lost; YLD – Years Lived with Disability.


The costs of drug provision come to the fore when planning the budget of the healthcare system [1]. It is necessary to take into account not only the benefits of prescribed medicinal products but also the potential risks and predictability of adverse drug reactions (ADRs) development. A comprehensive assessment of the risk/benefit ratio during the prescribing of medicinal products (MPs) should include an analysis of clinical efficacy, a safety profile, and potential economic consequences [2]. Methodological approaches to assessing pharmacoeconomic parameters are varying and include the analysis of the databases on known ADRs, and the subsequent draw of conclusions and formulation of recommendations to minimize ADRs costs; high-quality clinical trial data; the results of clinical and economic research as well as a pharmacoeconomic analysis [3].

Adverse drug reactions are harmful and unexpected reactions in response to the use or withdrawal of a medicinal product prescribed in therapeutic doses to a person for prevention, diagnosis, therapy, or changing physiological functions [4]. The aim of continuous ADRs monitoring is not only to identify previously unknown medical effects and potential drug interactions, but also to control the increase in the frequency of occurrence of known ADRs and/or their severity, to identify risk factors and possible mechanisms that cause them, and to spread information required to improve the prescription of drugs [5].

For a comprehensive assessment of an adverse event, in both global and Russian kinds of practice, the presence and/or the absence of seriousness criterion is also taken into account as well as the expectedness of the event. Therefore, reactions can be classified as unexpected adverse reactions (UADRs), Serious Adverse Drug Reactions (SADR), and Suspected Unexpected Serious Adverse Reactions (SUSAR) (Official website of Roszdravnadzor, 2020). The collection of ADRs data in different countries is carried out in a similar manner – notification forms that contain the data that make possible the identification of the patient, a suspected drug, the ADR description, and information about these sources [6].

According to the information from Roszdravnadzor, about 30% of the notification forms it receives, do not contain the minimum required data for a complete analysis [8].

The deviations in the ADR manifestations, are possible due to various characteristics of the population (demographic, genetic, etc.). In addition, they can be explained by the conditions of drug manufacturing and transportation. It does not make it possible to fully extrapolate the available foreign data to the Russian practice, and requires the study of ADRs on the territory of the Russian Federation.

The pharmacovigilance system, which was introduced into routine medical practice at the post-authorization stage of MPs use around the world, makes it possible to accumulate and evaluate the data on ADRs [9]. Working with these resources, is aimed at collecting and analyzing information on adverse events not specified in the instructions for medical use, UADR, SADR and SUSAR, and drug interactions. The collected information is evaluated by experts of regulatory authorities, often with the involvement of other expert organizations. ADRs databases maintained by WHO and national regulatory authorities, accumulate information on the events related to the safety of MPs, for example, Vigibase, Eudravigilance, FAERS, etc. An Automatic Information System (AIS) for the input of ADR information called “FARMAKONADZOR”, has been introduced by the Russian Federation [10]. The ARCADe regional database (Adverse Reactions in Crimea, Autonomic Database) has been used since 2009 on the territory of the Republic of Crimea and cumulates the data of spontaneous reports in the region [11]. Brazil has a National Pharmacovigilance System (NPS) of their own, and it operates as a part of the Brazilian National Health Surveillance Agency (ANVISA) [12].

Regardless of the particular type of a local pharmacovigilance system and pharmacovigilance assessment methods, the obtained data make it possible to draw a preliminary conclusion regarding the safety profile and the effectiveness of drugs. However, spontaneous reporting does not take into account the time factor in the ADRs development, and does not make it possible to assess the pharmacoeconomic costs of a separate ADR, including indirect costs, and additionally, it cannot predict further ADRs development.

THE AIM of this review article is to highlight the methodologies for assessing the financial costs of adverse drug reactions exemplified by the Russian Federation and Brazil.


The costs of ADRs must be taken into consideration in an integrated manner, i.e., with keeping account of a range of other problems associated with ADRs. A number of pharmacoeconomic (PE) methodological approaches can be used. In this case, the main stages of the analysis, can be divided into two large blocks (or directions): pharmacoeconomic and pharmacoarithmetic ones. In the first block, after assessing the economic and clinical components and their synthesis, the sustainability of the results should be assessed, a sensitivity analysis should be carried out, and after these stages, the conclusions are to be drawn and recommendations oriented towards decision-making in the healthcare sector are to be made. In the second block, the economic component (costs of pharmacotherapy) is assessed, and after assessing the sustainability of the results and the sensitivity analysis, the conclusions are drawn. Unlike the first approach, the conclusions are not prioritized in decision-making for the entire system of public healthcare.

Estimating the costs of ADRs obviously requires a more systematic approach, with an assessment of possible outcomes and a detailed patient routing. The route of a patient in PE models can be outlined using either the decision tree model or the Markov model (or a combination of these two methods). All the three approaches have certain advantages and limitations. Thus, the “decision tree” model considers the state of the system (in this case, the patient’s condition) at the input and output, and its final state, i.e., the exit from the model is determined by the sum of initially specified events developing sequentially and having a certain degree of occurrence probability. In the final assessment, a number of factors, e.g. temporal, are excluded. Unlike models of the “decision tree” type, which consider the state of the system at the input and output, Markov models (Fig. 1) take into account the probability of the system transition from one state to another during the so-called Markov cycle, i.e. in a given time interval [13, 14].


Figure 1 – An example of a possible Markov cycle, where Px are the probabilities of transition from one condition to another


Fig. 1 shows the graph of the Markov model, possible in our case. Several states of the patient are presented: “Health”, “ADR”, “Death” and the “Disease” is known, as well as the probabilities of transition from one state to another (Px) during a given time interval. This Markov cycle can be extended by adding additional states. The duration and frequency of cycles depend on a specific clinical situation. Additional factors taken into account in the process of the model building, make possible evaluating predictions more accurately [14].

The models described above were originally developed to predict the outcomes of infectious diseases. Subsequently, these methodologies were successfully applied in PE modeling of various therapeutic and surgical outcomes, as well as in the assessment of the effectiveness of health technologies. Such modeling algorithms, which include findings from existing databases indicating the frequency and quality of outcomes, can be extrapolated to the prediction and course of ADRs.

When assessing the ADR cost, it seems reasonable to use the European DRP PCNE (Drug Related Problems of Pharmaceutical Care Network Europe) system, which makes it possible to systematize the events related to pharmacological safety issues in validated reports. The versions of the PCNE system, are regularly updated through periodic revisions by a working group of experts. The PCNE approach is based on the coding of problems into several categories: problems, causes, interventions, and outcomes, which in turn are divided into subcategories [11, 15, 16]. It is necessary to take into consideration the fact that modeling, aimed specifically at assessing economic costs during the evaluation of the “global burden of disease” (GBD), also requires keeping account of such indicators as the cost/utility ratio, the analysis of the impact on the budget as well as discounting with a planning time horizon of more than one year. When using the time factor, the following indicators can be used: mortality, maternal mortality ratio (MMR), years lived with disability (YLD), years lost for life (YLL), healthy life expectancy (HLE), disability-adjusted life year (DALY), etc. [17].

As seen from the description of the approaches for collecting information about ADRs, these methodologies do not imply an assessment of the time factor, and therefore, forecasting the ADRs “burden” in the Russian Federation has a number of limitations. Expenditures on diagnostics, treatment, and prolongation of hospitalization, all in relation to a specific nosology, should be taken into account in the assessment of the economic costs of ADRs. In addition, the indirect costs associated with missing working days, disability, and a decrease in the quality of life, should be also taken into consideration.


At the federal level, the Russian Federation maintains a unified safety database. The information is recorded on the basis of Federal Law No. 61-FZ dated 12 April 2010 (as amended on 03.04.2020) “On Circulation of Medicinal Products” and Article 64 “Pharmacovigilance”. Since April 2019, coding of ADRs in the Automatic information system of Roszdravnadzor is carrying out using the MedDRA (Medical Dictionary for Drug Regulatory Affairs) classifier with obligatory indicating of the system-organ class of the reaction that has arisen. In addition, the contact person who provided the information, the international non-proprietary name that caused the ADR, its dosage, start and end dates, the causal relationship type for the drug-event pair, the concomitant therapy, de-challenge and re-challenge results for the suspected drug (if applicable), are indicated. According to WHO recommendations, the minimum information to be reported also includes the severity and seriousness of ADR.

Since 2013, the Russian Federation has introduced a system for calculating the reimbursement of medical care from the state foundation of compulsory medical insurance based on diseases classification according to the so-called “Clinical and statistical groups” (CSG). They represent the groups of diseases belonging to the same profile of medical care, and similar in the methods used for diagnosing and treating patients, as well as in average resource intensity (cost, cost structure and set of resources used).

A concept of “clinical profile group” (CPG) which is a group of CSGs and/or individual diseases, united by one profile of medical care”, can also be used for such calculations [19]. The group of CPGs includes conditions that require hospitalization. Tariffs to assess the complications of pharmacotherapy, were developed for CPG.

The formation of such groups is carried out on the basis of the parameters that determine the relative capacity of treatment costs: diagnosis, type of health technology or intervention used, patient’s age, gender, concomitant pathology or complications of the disease, duration and treatment regimen, duration of staying on artificial lung ventilation (ALV) if necessary. The results of assessing the patient’s condition according to clinical scales (for example, the scale for assessing the organ failure in the patients in the intensive care department (Sequential Organ Failure Assessment (SOFA), rehabilitation routing scale, etc.), are also taken into consideration. The average weight factor (AWF) which is calculated according to the given formula and the number of cases in the previous year, are used to calculate the amount of expected similar cases in the next year. The quantity of financial support for a medical organization by each CSG or CPG, is calculated as the sum of the costs of all hospitalizations in a hospital.

According to the data for 2019, Table 1 represents the data on the costs of severity grade 3 ADRs (CTCAE v. 4.03 classification) in medical institutions in St. Petersburg.


Table 1 – Cost of adverse drug reactions for 2019, calculated on the basis of the CSG

Adverse events

The cost of drug A therapy, ADR ≥ Stage 3 (roubles)

The cost of drug B therapy, ADR ≥ Stage 3 (roubles)

GTA of Saint-Petersburg

26 849,22

26 196,37

Basic tariff of SGBP

36 790,16

35 593,73

Federal CSG

70 613,19

76 218,45

Note: GTA – General Tariff Agreement; SGBP – Program of state guarantees for free provision of medical care to citizens; CSG – clinical and statistical group; ADR – Adverse Drug Reaction


It should be notified that in the Russian Federation a unified methodology for assessing the costs of ADRs, has not been developed yet. As a rule, the results of the observational studies and/or database data are analyzed by an expert group, which then interprets the results based on their assessment.

Thus, a standardized approach to assessing pharmacoeconomic costs in connection with the ADRs development in the Russian Federation, has not been developed, either. The existing methodologies are applicable only to a limited number of nosological forms, and only to those events that require hospital observation. Therefore, it is impossible to take into account the time factor and indirect health care costs provoked by ADRs. In addition, extrapolation of results even during hypothetical planning can be difficult due to the fact that different systems for coding clinical manifestations and diseases, are used in pharmacovigilance and pharmacoeconomics (MedDRA and ICD 10).

In the healthcare system of some countries in Latin America, for example, in Brazil (the approach to burden assess in this country is well represented in the literature). A different approach using the DRPs concept (a system that evaluates all medical adverse events caused by ineffective pharmacotherapy and/or non-adherence to recommended treatments) is applied. For example, to assess DRPs, the Brazilian healthcare system SUS (Sistema Unico de Sau) uses a methodology originally developed by Jonson and Butman. It is based on a “decision tree” model representing potential clinical outcomes and direct economic costs. Herewith, direct economic costs also take into account the development of “new diseases” associated with the use of drug therapy (Drug-Related Morbidities; DRM). Costs can be direct, i.e. costs for the ADRs correction, and indirect ones such as lost working days or a period of reduced work ability [19, 20]. The model of ADRs assessment is based on 8 basic characteristics: untreated clinical conditions, inappropriate drug choices, subtherapeutic doses, drug refusals, overdoses, ADRs, drug interactions, and a drug use without appropriate indications. Further modeling involves analyzing the probabilities and costs, associated with the following therapeutic outcomes: 1) no need in additional treatment; 2) additional treatment; 3) visiting a doctor (visiting a medical specialist); 4) emergency department visit with a hospital stay less than 24 hours; 5) hospitalization or hospitalization with a stay in hospital for more than 24 hours; 6) long-term treatment or preliminary hospitalization with a minimum stay of 30 days in hospital or hospitalization to the intensive care unit; 7) death.

Further on, when analyzing an event, the “decision tree” can be represented by several branches. In the first branch of the “optimal outcome,” DRMs are divided into three axes of mutually exclusive, sequential negative events: 1) Treatment Failure (TF); 2) New Medical Problem (NMP); 3) a combination of new medical problems and treatment failure (NMP/TF). A New Medical Problem (NMP) represents effects that are superior to those expected after pharmacotherapy (or undesirable effects of pharmacotherapy), including ADRs, dependence, and overdose. Treatment failure (TF) includes inadequate therapeutic effects arising from inappropriate treatment or dose selection, drug and food interactions, inappropriate drug prescription, medication errors, unnecessary drug use, and inadequate adherence to the drug regimen as well. The second part of the “decision tree” estimates the supposed proportion of DRMs, and the third one consists of clinical negative results from previous DRMs (NMPs, TFs, and NMPs/TFs) [19, 20].

The branches of the tree are mutually exclusive. Therefore, the score should represent the worst scenario for the patient. For example, a patient who is hospitalized due to DRMs has probably already been consulted for treatment adjustments during previous consultations by a healthcare professional. However, this patient should be allocated to those who had been “hospitalized” and should not be taken into account in other branches (“additional treatment” or “visiting a specialist”).

The method has been refined through the involvement of clinical experts using a double-stage Delphi approach. At the first stage, the model can be presented to clinical experts, each of whom assesses the likelihood of the results development described above, in accordance with their own practical and clinical kinds of experience. At the second stage, clinical experts review the predictions of all other participants. If the prognosis of a particular medical expert differs, it explains such a position in order to reach a consensus [21].

An example is the cost estimate of the ADRs, was carried out in one of the hospitals in accordance with the methodology described above by de Freitas et al. [20].

48 medical specialists were recruited as experts. 44 of them were clinical pharmacologists. The results of assessing the ADR costs in the various scenarios, calculated by the authors, are presented in Table 2.


Table 2 – Results of an expert assessment of ADRs costs in various scenarios according to the data de Feritas [19]


Base analysis

Best scenario

Worst scenario

Costs (USD)

Costs (USD)

Costs (USD)

Without additional treatment

Visiting a doctor and primary prescription of drugs


Primary prescription of drugs


Visiting a doctor and primary prescription of drugs


Additional therapy prescribed

Visiting a doctor and primary prescription of drugs + additional therapy prescribed


Primary prescription of drugs + additional therapy prescribed


Visiting a doctor and primary prescription of drugs + additional medical consultation + additional therapy prescribed


Consultation of specialist needed

Visiting a doctor and primary prescription of drugs + additional medical consultation + additional therapy prescribed


Visiting a doctor and primary prescription of drugs


Special medical consultation and primary prescription of drugs + additional special consultation + additional therapy prescribed


Urgent care required

Visiting a doctor and primary prescription of drugs + 2 days of in-hospital treatment


Visiting a doctor and primary prescription of drugs + 1 days of ICU treatment


Visiting a doctor and primary prescription of drugs + 5 days of in-hospital treatment


Hospitalization or prolongation of hospitalization

Visiting a doctor and primary prescription of drugs + 6 days of in-hospital treatment


Visiting a doctor and primary prescription of drugs + 3 days of in-hospital treatment


Visiting a doctor and primary prescription of drugs + 9 days of in-hospital treatment


Long-term follow-up in a medical facility

Visiting a doctor and primary prescription of drugs + 30 days of in-hospital treatment


Visiting a doctor and primary prescription of drugs + 10 days of ICU treatment


Visiting a doctor and primary prescription of drugs + 30 days of ICU treatment



Visiting a doctor and primary prescription of drugs


Visiting a doctor and primary prescription of drugs


Visiting a doctor and primary prescription of drugs


Note: USD – USA dollars; ICU – intensive care unit


It should be notified that this study is representative of 36% of the Brazilian population [21]. By the group of clinical experts, it was determined that more than half (59%) of patients had DRMs when using at least one drug after a visit to a medical organization/certified physician. The research also shows that the result of an outpatient visit is a prescription for at least one drug. This estimate is consistent with other Brazilian and global data, which indicate that from 50% to 86% of consultations lead to drug prescriptions [22]. Based on the “decision tree” model and the expert review, the average prediction costs of the various ADRs were as follows: NMP, TF, and NMP/TF ratios were 216, 240, and 282 USD, respectively. The results show that among the patients, who received outpatient care and at least one drug, were as follows: 19.5%, 26.8%, and 13% had NMP, TF, and NMP/TF, respectively. These data are comparable to other studies that used the same method (NMP: 10.3%, 28.7%; TF: 16.0%, 23.4%; and NMP/TF: 6.5%, 14. 0%). The cost of medical care for a patient with ADRs was 155 USD. Brazil’s average annual costs for ADRs services, range from 9.1 billion USD to 27.2 billion USD (the best and worst-case scenarios, respectively). Of these costs, 3 billion USD will be spent on hospitalization, 10.8 billion USD – on prolongation of hospitalization, which will be the main outcome of ADR. Additional consultations by specialists, as well as the stay of patients in the ICU, will cost 2 billion USD and 900 million USD, respectively [19–21].

The reasons for the aforementioned problems can be explained by failures in treatment monitoring, difficulties with therapeutic adherence, and issues related to the choice or prescription of MPs. According to the experts’ estimates, from 53% to 60% of new medical problems (NMPs) and treatment failures (TFs), could have been avoided, in case patients received pharmaceutical care service out of hospital.

The current literature data confirm that ADRs are an urgent problem of modern pharmacoeconomics. Unfortunately, the current pharmacovigilance systems cannot solve a number of problems, such as a low activity of researchers in relation to the ADRs detection, recording, and transmission of information about ADRs, low awareness of the population about the potential risk of ADRs, a low quality of the sent spontaneous reports, etc.

One of the priority-oriented areas of the Russian healthcare system over the past few years has been monitoring the effectiveness, safety, and quality of drugs used at various stages of the clinical and diagnostic process. The experience of the Brazilian drug safety system demonstrates that the introduction of a pharmacologist/clinical pharmacologist consultation prior to prescribing drugs in a specific clinical situation, is cost-effective. Inappropriate prescriptions and lack of patients’ follow-up, are the most common causes of ADRs. New diseases and deterioration of existing conditions requiring hospitalization associated with MPs could often be avoided.

Most of ADRs are explained by communication impairments (between patients, caregivers, and healthcare providers), poor adherence to treatment, and lack of knowledge about MPs, their dosages, dosing regimens, and potential drug interactions. The leading task for medical professionals is comprehensive counseling of patients in relation to the prescribed drugs. Sufficient knowledge of health professionals in the field of drug safety will allow them to reduce the frequency of SUSARs, as well as to prevent negative drug-related conditions.

Comprehensive analysis of the information related to drug safety issues, can be an effective economic tool for optimizing costs in the healthcare system. When assessing economic costs, various modeling methodologies or their combinations can be used. However, when predicting, it is important to take into account not only direct and indirect costs but also the ADRs outcomes, which, in turn, can seriously affect a further quality of life. The methods of the economic assessment of ADRs, are almost not used in Russian practice, with the exception of the cases of the CSG/CPG classification of the diseases, used for the calculation of the reimbursement for medical care from the state foundation of compulsory medical insurance. In general, the number of studies on this issue is limited, and requires active development.


The models used in the Russian Federation for the analysis of economic value and further prediction of costs, in contrast to the Brazilian approach, do not take into account the time factor. Respectively, during the planning of the analysis of ADRs potential costs, it is necessary to strengthen the methods with such PE tools as QALY, YLL, YLD, etc.

The introduction of methods for assessing the ADRs economic burden into the Russian routine medical practice, will reduce the direct and indirect costs associated with complications of pharmacotherapy. As shown by the review of Brazilian practice, the analysis of the economic feasibility of prescribing a particular drug should be also subjected to a critical analysis, and the final decision should be made by the teams involving a clinical pharmacologist. This approach will make it possible not only to predict the costs of medical interventions, but also to take into account the potential costs of modifying pharmacotherapy due to the development of ADRs.


This work did not have funding from outside organizations.


The authors declare no conflict of interest.


G.I. Syraeva – carrying out a literary search, writing the original text of the article and the resume; A.S. Kolbin – the formulation of the aim and objectives of the study, text editing; A.V. Matveev – article editing, preparing the English language text, preparing illustrations; V.S. Panezhina – carrying out a literary search, preparing the “Materials and Methods” section.


About the authors

Gulnara I. Syraeva

First St. Petersburg State Medical University named after academician I.P. Pavlov; Research Center ”Eco-safety”

Author for correspondence.
ORCID iD: 0000-0001-6635-9786

clinical pharmacologist, the head of the department of quality control and quality assurance of clinical trials; postgraduate student of the Department of Clinical Pharmacology

Russian Federation, 6–8, Lev Tolstoy St., St. Petersburg, 197022; 65, Yuri Gagarin Ave., St. Petersburg, 196143

Aleksey S. Kolbin

First St. Petersburg State Medical University named after academician I.P. Pavlov; Medical Academy named after S.I. Georgievsky (structural unit) of “Crimean Federal University named after S.I. Vernadsky”

ORCID iD: 0000-0002-1919-2909

Doctor of Sciences (Medicine), Professor, the Head of the Department of Clinical Pharmacology and Evidence-Based Medicine; Professor of the Department of Pharmacology, Faculty of Medicine

Russian Federation, 6–8, Lev Tolstoy St., St. Petersburg, 197022; 5/7, Lenin Bul., Simferopol, Republic of Crimea, 295007

Alexander V. Matveev

Medical Academy named after S.I. Georgievsky (structural unit) of “Crimean Federal University named after S.I. Vernadsky”; Russian Medical Academy of Continuing Professional Education (RMA CPE)

ORCID iD: 0000-0002-6636-3950

Candidate of Sciences (Medicine), Associate Professor of the Department of Internal Medicine No. 1 with a course in Clinical Pharmacology; Associate Professor of Clinical Pharmacology and Therapy department

Russian Federation, 5/7, Lenin Bul., Simferopol, Republic of Crimea, 295007; Bld. 1, 2/1, Barrikadnaya St., Moscow, 125993

Vera S. Panezhina

Research Center ”Eco-safety”

ORCID iD: 0000-0002-5602-5536

a general practitioner, a doctor of functional diagnostics

Russian Federation, 65, Yuri Gagarin Ave., St. Petersburg, 196143


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Supplementary files

Supplementary Files
1. Figure 1 – An example of a possible Markov cycle, where Px are the probabilities of transition from one condition to another

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