Financial Risk Management in Healthcare in the Provision of High-Tech Medical Assistance for Sustainable Development: Evidence from Russia
1
National Medical Research Center of Surgery Named after A. Vishnevsky, Moscow 117997, Russia
2
Russian Research Institute of Health, Moscow 127254, Russia
Risks 2024, 12(9), 134; https://doi.org/10.3390/risks12090134
Submission received: 29 June 2024
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Revised: 15 August 2024
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Accepted: 20 August 2024
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Published: 26 August 2024
(This article belongs to the Special Issue Managing Financial Risks Based on Corporate Social Responsibility for Sustainable Development II)
Abstract
:The research determines the level of financial risk in the Russian healthcare system and identifies prospects for improving the current Russian practice of financial risk management in healthcare when providing high-tech medical care for sustainable development (using Russia as an example). The author summarizes the advanced experience of the top 20 largest healthcare organizations in Russia by revenue in 2022. Based on this experience, the author developed an SEM model of the financial risks in healthcare during the provision of high-tech medical care in Russia from a sustainable development perspective. The theoretical significance of the developed model lies in uncovering the previously unknown causal relationships between the implementation of the ICT, sustainable development support, and financial risks in healthcare. The model reveals a new market dimension of financial risks for healthcare organizations in Russia. The main conclusion is that implementing the ICT and support for sustainable development helps to reduce the financial risks in healthcare. The identified potential for reducing financial risks in providing high-tech medical care in Russia until 2026 is practically significant. This prospect can be practically applied as a roadmap for the digital modernization and sustainable development of healthcare until 2026, enhancing the state healthcare policy in Russia. The established systemic relationship between ICT implementation, sustainable development support, and financial risks in healthcare is of managerial importance because it will increase the predictability of the financial risks in the market dimension of healthcare in Russia. The newly developed approach to risk management in healthcare during the provision of high-tech medical care in Russia has expanded the instrumental framework of risk management for healthcare organizations in Russia and revealed further opportunities for improving its efficiency.
1. Introduction
Healthcare is a top priority for socio-economic systems because the availability and quality of medical care directly affect the quality and longevity of life for the population and the attractiveness of regions for living. Furthermore, the recent experiences of economic systems, especially during the COVID-19 pandemic, one of the major global challenges of the early 21st century, have demonstrated that the quality of healthcare also affects the economic potential of countries.
Numerous recent studies, such as those by Park and Koch (2024), Saha et al. (2024), and Zhou et al. (2024), re-examined the experience of the COVID-19 pandemic and revealed a pattern: the higher the level of healthcare in a country, the more successfully its economy handles the challenges of epidemics and pandemics, demonstrating greater resilience.
The international practices of 2020–2021 demonstrated that the readiness of national healthcare systems for the pandemic and their successful adaptation (infection spread rate, morbidity, severity of diseases, recovery speed, and COVID-19 mortality rate) determined the social (e.g., self-isolation, strict mask mandates, and social distancing) and economic (e.g., production halts and closures and forced transition to remote work) restrictions.
While traditional healthcare development measures (e.g., increasing the number of medical professionals, revising norms and stimulating their labor, and expanding the number of medical facilities and their capacity) provide only limited positive effects, manifesting only in the long term, the pandemic has heightened interest in the technological modernization of healthcare as an innovative development measure.
The advantages of healthcare digitization include a sharp increase in labor productivity in providing medical services. For instance, the use of artificial intelligence (AI) helps to automate and significantly accelerate the processing of medical information with high accuracy in diagnostic support. The other benefits of healthcare digitization include the increased accessibility of medical care (e.g., through telemedicine). The quality of the medical care also improves with digitization because high-tech medical equipment enables more complex and precise procedures and surgeries.
Given the critical importance of healthcare and the drive to ensure its universal accessibility in many countries, including Russia, the state plays a central role in the public healthcare system. However, the consequences of a state-run public healthcare system are contradictory from a sustainable development perspective. On the one hand, the state addresses “market failures” by providing large-scale budgetary funds for financing infrastructure projects and national programs for the technological modernization of healthcare.
On the other hand, the pace of technological modernization in healthcare is slow because it is driven more by the budgetary capabilities of the state than by the needs of society. Limited and targeted funding, coupled with the low flexibility of management in state healthcare organizations, results in only isolated successes in providing high-tech medical care characterized by low service quality, convenience, and customer orientation.
Lastly, and perhaps even more significant than the previously mentioned drawbacks, state funding does not ensure a return on the investment in healthcare digitalization. The activity of public healthcare organizations is often unprofitable, reducing their competitiveness. This underscores the scientific and practical problem of attracting private investments for the digital modernization of healthcare.
To address this issue, this research proposes improving the financial risk management practices in healthcare when providing high-tech medical care. The novelty of this research lies in developing a new approach to the risk management in healthcare for high-tech medical care, where the key role is played by private businesses. The research aims to determine the level of financial risk in the Russian healthcare system and identify prospects for improving the current Russian financial risk management practices in healthcare during the provision of high-tech medical care for sustainable development.
The research is organized as follows. The author identified the financial risks in Russian healthcare (using the largest market players in healthcare as an example) and constructed a model of financial risks in healthcare during the provision of high-tech medical care in Russia from a sustainable development perspective. The research also reveals prospects for improving the financial risk management in healthcare during the provision of high-tech medical care in Russia to support sustainable development.
2. Literature Review
2.1. The Existing Approach to Risk Management in Healthcare When Providing High-Tech Medical Care in Russia
The fundamental basis of this research is the scientific concept of risk management in healthcare (Stancea and Muntean 2024; Yang et al. 2024). According to this concept, there are the following risks in healthcare when providing high-tech medical care:
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- Social risks, which relate to the accessibility and quality of the medical services and the level of patient satisfaction with these services (Przhedetsky et al. 2018);
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- Labor risks, involving changes in the workload of the medical staff and its functional designation, the need to fill gaps in digital competencies, and the release of certain medical personnel as medical care becomes automated (Umair et al. 2024);
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- Technological risks associated with the moral and physical depreciation of equipment, protection of personal data, ensuring cybersecurity, errors and disruptions in the operation of automation tools, and the ethics of using AI and big data in healthcare (Ishaq et al. 2024);
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- Epidemiological risks, which refer to the sharp increase in demand for medical services due to epidemics and pandemics (Arianpoor and Naeimi Tajdar 2024);
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- Financial risks are linked to the misuse (embezzlement) of budget funds allocated for technological modernization (Morozova et al. 2018).
The existing approach to risk management in healthcare when providing high-tech medical care in Russia assumes that the state acts as the subject of financing the healthcare digitalization. This approach enables the relatively successful management of the aforementioned risks but does not encompass financial risks in healthcare within its managerial measures.
2.2. Corporate Social Responsibility in Healthcare in Support of Sustainable Development
In the existing approach to risk management during the provision of high-tech medical care in Russia, leaders of public healthcare organizations bear corporate social responsibility
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- To consumers for the accessibility, quality, continuity, and ethical provision of high-tech medical care, in managing social, technological, and epidemiological risks in support of SDG 3 (Ding et al. 2024; Korah et al. 2023);
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- To healthcare workers for providing employment opportunities and fostering human potential, in managing labor risks in support of SDG 8 (Bolisetty et al. 2023; Chen et al. 2023; Udekwe et al. 2024);
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- To the state for the correct and targeted use of the budget funds allocated for technological modernization, in managing the financial risks in support of SDG 16 (Mohamad Taghvaee et al. 2023; Rahman et al. 2022; Shuyong et al. 2024).
However, there is no corporate social responsibility of healthcare organizations for the efficiency of financial resource expenditure and the return on investment in the technological modernization of healthcare. This results in a narrow interpretation of financial risks and limited management of these risks, enabling only partial mitigation.
2.3. Financial Risk Management in Healthcare: Theoretical Review and Gap Analysis
Frimpong et al. (2022) and Kahouli et al. (2024) highlight the risk of reducing the investment attractiveness of healthcare organizations for private investors as an additional dimension of financial risk in healthcare when providing high-tech medical care. This dimension considers the market nature of financial risks. The primary indicator of financial risk measurement in this market dimension is the decline in the value of stock indices (Wilson-Nash et al. 2024).
While the essence of financial risks in their market dimension is defined in existing publications by D’Amico et al. (2024) and Tong (2024), they do not explain the specifics of the financial risks in healthcare when providing high-tech medical care, nor do they reveal their connection to sustainable development. This gap in the literature hampers the management of market-related financial risks in healthcare. The research question is as follows:
RQ: How are ICT implementation and support for sustainable development interconnected with financial risks in healthcare?
Based on various sources that note the bidirectional links between the reduction in financial risks and an increase in the high-tech nature of medical care (Chen and Tang 2023; Geng and Shi 2024), the growth of healthcare sustainability as financial risks decrease (Bobylev et al. 2023; Wu et al. 2023), and the increase in healthcare sustainability as high-tech medical care becomes more widespread (Molleví Bortoló et al. 2023; Zhou and Jamaani 2023), the author proposes the following hypothesis:
H:
There is a close relationship between ICT implementation, support for sustainable development, and financial risks in healthcare.
This hypothesis is tested by establishing complex interconnections between the financial risk management in healthcare, the provision of high-tech medical care, and the sustainable development of healthcare.
3. Materials and Methods
The research subjects are the largest healthcare organizations in Russia in terms of revenue. This research is based on the systems approach, applying the methodology of systems analysis in economics. The author set and consistently addressed three research tasks.
The sample of this research includes the top 20 largest (by the level of revenue) healthcare organizations in Russia in 2022. According to the Ministry of Healthcare of the Republic of Tatarstan (2024), the volume of the total market of high-tech healthcare services in Russia exceeds RUB 6 billion. The Industry Consumer Sector Index as of 13.06.2024 was RUB 5.52501 billion (MOEX 2024a).
This indicates that the share of the top 20 largest (by the level of revenues) healthcare organizations in Russia in 2022 in the market of high-tech healthcare services in Russia is around 92.08%. This confirms the adequacy of the sample (20 largest healthcare organizations) to represent the entire system of high-tech healthcare of Russia.
According to the World Bank (2024), Russia’s GDP was USD 2,021,421.48 million, i.e., RUB 185,728.21 billion. According to Rosstat (2024), the share of healthcare in the structure of Russia’s GDP is 3.8%; i.e., the volume of the healthcare market in Russia equals RUB 7057.67 billion. Therefore, on the whole, the level of ICT adoption in healthcare organizations in Russia equals 0.08% (6 × 100%/7057.67).
In the materials of the IMD Business School (2024) in 2021, the level of the development of healthcare infrastructure is assessed at 4.64 points out of 10. Given the fact that infrastructure plays a decisive role in the development of high-tech healthcare and the provision of services, it is possible to state that ICT adoption in healthcare organizations in Russia is at the level of 4.64 points out of 10. According to BusinessStat (2024), the level of ICT adoption in the 20 largest (by the level of revenues) healthcare organizations in Russia in 2022 has this value and is uniform.
Thus, the compiled sample of the top 20 largest (by the level of revenues) healthcare organizations in Russia in 2022 is adequate to represent the entire system of Russia’s healthcare, and the final findings will have general applicability across all high-tech healthcare service organizations.
The research methodology involves the study of the dynamics of revenues of healthcare organizations from the sample. The indicator of financial risk is revenue reduction. It should be noted that change in the revenue of healthcare organizations is subject to the influence of a wide range of factors, which include the change in the volume of effective demand and consumer preferences, in particular, under the influence of the COVID-19 pandemic and its end; the volume of state financing of the system of mandatory medical insurance; the popularity of additional medical insurance and demand for the services of private medical organizations; and inflation.
To clear the research model from the influence of other factors and to characterize—most correctly—financial risks, this paper takes into account, during modeling, the data for a long period, which covers several years (three years): 2022–2024.
The first task is to determine the financial risks in Russian healthcare. For this, the author conducted a dynamic (horizontal) analysis of the revenue changes of the top 20 largest healthcare organizations in Russia in 2022 compared to 2021 based on Forbes statistics (Forbes 2024). A negative annual change in revenue indicates the occurrence of financial risks in the market dimension. A positive annual change in revenue indicates the prevention of financial risks in the market dimension.
The second task is to model financial risks in healthcare when providing high-tech medical care in Russia from a sustainable development perspective. The variables used in the modeling include the following official statistics indicators:
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- Sectoral Consumer Index, measured in billions of rubles, indicates the profitability of healthcare organizations as a reflection of their financial risk in the market dimension, denoted as HLT (MOEX 2024a);
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- Sectoral Information Technology Index (ICT), measured in billions of rubles, shows the activity of the ICT use in the economy and the return on investment, denoted as ICT (MOEX 2024b);
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- Sustainable Development Index, measured in billions of rubles, indicates the level of support for sustainable development by companies, denoted as SST (MOEX 2024c).
Empirical data are provided in Table A1. To reflect the systemic relationship between ICT implementation, support for sustainable development, and financial risks in healthcare, the author performed modeling using the structural equation modeling (SEM) method. First, the author conducted a regression analysis of the dependence of each variable on the other two variables. Then, the regression equations (showing the interdependencies of the indicators) are supplemented with variation coefficients (showing the model errors) and combined into a general SEM model. The research model is presented in Figure 1.
The third task is to determine the prospects for improving financial risk management in healthcare when providing high-tech medical care in Russia. First, based on the data from Table A1, the author applied a trend analysis method to determine the changes in the values of the variables ICT, SST, and HLT from 13 June 2024 compared to 14 June 2022 (a two-year trend).
Then, the forecast values of the variables ICT and SST are determined by finding the product of their values on 13 June 2024 with their identified two-year trend. These forecast values are substituted into the equation for HLT to determine its forecast value and projected two-year trend as of 13 June 2024. The prospect of reducing financial risks in healthcare when providing high-tech medical care in Russia until 2026 is also determined.
4. Results
4.1. Financial Risks in Russian Healthcare
In addressing the first task and determining the financial risks in Russian healthcare, the author conducts a dynamic (horizontal) analysis of the revenue changes among the top 20 largest healthcare organizations by revenue in Russia in 2022 compared to 2021. The statistical revenue data, which characterize the financial risks of the healthcare organizations, are presented in Table 1.
According to the results of the horizontal analysis from Table 1, only two of the top twenty largest healthcare organizations by revenue in Russia experienced a negative annual revenue change in 2021–2022. Consequently, the actual occurrence of financial risks in their market dimension is rare among the healthcare organizations in Russia despite overcoming the surge in demand for medical services due to the end of the COVID-19 pandemic.
The positive annual revenue change for most healthcare organizations in Russia indicates the prevention of financial risks in their market dimension in 2021–2022. However, financial risks in their market dimension persist and require management because the current risk management practices of Russian healthcare organizations cannot fully guarantee the avoidance of risky events.
4.2. A Model of Financial Risks in Healthcare during the Provision of High-Tech Medical Care in Russia from a Sustainable Development Perspective
In addressing the second task and modeling the financial risks during the provision of high-tech medical care in Russia from a sustainable development perspective, the author conducted a regression analysis of the data from Table A1. The results are compiled in Table 2.
The results obtained in Table 2 indicate that the profitability of the healthcare organizations is, by 49.66%, determined by the activity of the ICT implementation and support for sustainable development in Russia from 2022 to 2024. The profitability of the ICT organizations is, by 46.91%, determined by the consumption of high-tech medical care services and support for sustainable development in Russia from 2022 to 2024. The profitability of the organizations included in the “Sustainable Development Vector” index is, by 43.85%, determined by the activity of the ICT implementation and the consumption of high-tech medical care services.
All the standard errors are relatively small. Fisher’s F-test and Student’s t-test were passed at the highest significance level of 0.01, confirming the high quality, reliability, and validity of the regression statistics obtained and making it possible to include them in further modeling. To reflect the systemic relationship between ICT implementation, support for sustainable development, and financial risks in healthcare, this relationship was modeled using the structural equation modeling (SEM) method. The composed regression equations (showing the interdependencies of the indicators) were supplemented with variation coefficients (showing the model errors) and combined into an overall SEM model (Figure 2).
The SEM model from Figure 2 showed that, with an increase in the profitability of the ICT organizations by RUB 1 billion, the profitability of the organizations included in the “Sustainable Development Vector” index increases by RUB 0.0622 billion, and the profitability of the healthcare organizations grows by RUB 0.4553 billion. When the profitability of the organizations included in the “Sustainable Development Vector” index increases by RUB 1 billion, the profitability of the ICT organizations rises by RUB 0.7754 billion, and the profitability of the healthcare organizations grows by RUB 1.3633 billion.
With an increase in the profitability of the healthcare organizations by RUB 1 billion, the profitability of the organizations included in the “Sustainable Development Vector” index increases by RUB 0.0592 billion, and the profitability of the ICT organizations rises by RUB 0.2466 billion. The variation in the profitability of the ICT organizations is 92.62%, the variation in the profitability of the organizations included in the “Sustainable Development Vector” index is 47.95%, and the variation in the profitability of the healthcare organizations is 76.86%.
Thus, the developed SEM model highlighted the close systemic relationship between ICT implementation, support for sustainable development, and financial risks in healthcare. This opens up the possibility of further improving the financial risk management in healthcare through increased activity in providing high-tech medical care and supporting sustainable development in Russian healthcare.
4.3. Improving Financial Risk Management in Healthcare during the Provision of High-Tech Medical Care in Russia
In addressing the third task and determining the prospects for improving the financial risk management in healthcare during the provision of high-tech medical care in Russia, the author used a trend analysis method based on the data from
Table A1
to determine the changes in the values of the ICT, SST, and HLT variables by 13 June 2024 compared to 14 June 2022 (a two-year trend).
The forecast values of the ICT and SST variables were also determined by multiplying their values on 13 June 2024 with their identified two-year trend. These forecast values were substituted into the equation for HLT to determine its forecast value and projected two-year trend by 13 June 2024. The prospects for reducing the financial risks in healthcare during the provision of high-tech medical care in Russia until 2026 were also identified (Figure 3).
As demonstrated in Figure 3, the two-year trend in the profitability of the ICT organizations in 2024 compared to 2022 (as of mid-year, specifically 13 June) was 9.24%. Therefore, for 2026 (as of mid-year, specifically 13 June), a similar increase in the profitability of the ICT organizations is projected, which is forecasted to reach RUB 54.82 billion.
The two-year trend in the profitability of the organizations included in the “Sustainable Development Vector” index in 2024 compared to 2022 (as of mid-year, specifically 13 June) was 2.43%. Therefore, for 2026 (as of mid-year, specifically 13 June), a similar increase in the profitability of the organizations included in the “Sustainable Development Vector” index is projected, which is forecasted to reach RUB 165.19 billion.
The two-year trend in the profitability of the healthcare organizations in 2024 compared to 2022 (as of mid-year, specifically 13 June) was 9.24%. Therefore, by 2026 (as of mid-year, specifically 13 June), a similar increase in the profitability of the healthcare organizations can be achieved. However, this forecast does not consider the systemic connection between ICT implementation, support for sustainable development, and financial risks in healthcare identified in this research.
Considering this systemic connection, solely due to the projected growth in the profitability of the ICT organizations and organizations included in the “Sustainable Development Vector” index, the profitability of the healthcare organizations by 2026 will increase by 3.88%—to RUB 21.44 billion. This increase represents a synergistic effect that will complement the standard growth in the profitability of the healthcare organizations, resulting in a total increase of 13.65% (9.77 + 3.88), reaching RUB 75.48 billion (5.53 × 13.65).
5. Discussion
The contribution of this research to the literature (Stancea and Muntean 2024; Yang et al. 2024) lies in the development of the scientific concept of risk management in healthcare by substantiating the significance of a new market dimension of financial risks for improving the accessibility and quality of high-tech medical care and sustainable development of healthcare in Russia. This evidence forms the basis of the new approach to risk management in healthcare during the provision of high-tech medical care in Russia proposed in the research, which is compared with the current approach in Table 3.
As shown in Table 3, the new approach emphasizes the market dimension of financial risks (i.e., risks of obtaining and utilizing private investments) rather than the regulatory dimension (i.e., risks related to the provision and expenditure of budget funds), unlike Stancea and Muntean (2024). In contrast to Yang et al. (2024), the new approach identifies private investors, rather than the state, as the primary financers of healthcare.
Unlike Bolisetty et al. (2023), Ding et al. (2024), Korah et al. (2023), and Mohamad Taghvaee et al. (2023), the new approach expands the range of the beneficiaries of risk management beyond just consumers, healthcare workers, and state healthcare regulators to include investors in ICT and sustainable healthcare development.
In contrast to Arianpoor and Naeimi Tajdar (2024), Ishaq et al. (2024), Morozova et al. (2018), Przhedetsky et al. (2018), and Umair et al. (2024), the new approach does not limit the risks in healthcare when providing high-tech medical care to social, technological, epidemiological, labor, and regulatory financial risks and also includes financial risks in the market dimension.
Unlike Chen et al. (2023), Rahman et al. (2022), Shuyong et al. (2024), and Udekwe et al. (2024), the new approach does not support the SDGs individually and is not limited to SDG 3, SDG 8, and SDG 16, but it systemically supports SDG 3, SDG 9, and SDG 12. Accordingly, the risk management method involves ensuring the return on the private investments in ICT and sustainable healthcare development.
The theoretical contribution of this research to the literature lies in proving hypothesis H and confirming the existence of a close relationship between ICT implementation, support for sustainable development, and financial risks in healthcare, thus advancing the scientific discussion initiated by Bobylev et al. (2023), Chen and Tang (2023), Geng and Shi (2024), Molleví Bortoló et al. (2023), Wu et al. (2023), and Zhou and Jamaani (2023).
6. Conclusions
Thus, the main conclusion of this research is that implementing the ICT and support for sustainable development reduces the financial risks in healthcare. This conclusion is supported by the evidence gathered from summarizing the advanced experience of the top 20 largest healthcare organizations by revenue in Russia in 2022 and developing the SEM model of financial risks in healthcare during the provision of high-tech medical care in Russia from a sustainable development perspective.
The theoretical significance of the author’s model lies in uncovering the previously unknown causal relationships between ICT implementation, support for sustainable development, and financial risks in healthcare. This model highlights a new market dimension of financial risks for healthcare organizations in Russia.
The practical significance of the author’s findings and results is that they outline the prospect of reducing the financial risks in healthcare during the provision of high-tech medical care in Russia until 2026. This prospect can be practically applied as a roadmap for the digital modernization and sustainable development of healthcare until 2026, aimed at improving the state healthcare policy in Russia.
The established systemic relationship between ICT implementation, support for sustainable development, and financial risks in healthcare holds managerial significance because it will enhance the predictability of the financial risks in the market dimension of healthcare in Russia. The new approach to risk management in healthcare during the provision of high-tech medical care in Russia, proposed in this research, expands the toolkit for risk management in Russian healthcare organizations and improves its efficiency.
A limitation of this research lies in its focus on the Russian experience. Although many other countries also implement state-run public healthcare models and state financing of high-tech medical care, the Russian experience cannot be confidently generalized to other countries without further verification and refinement. Therefore, future research should include applied and case studies on the financial risk management in healthcare during the provision of high-tech medical care aimed at sustainable healthcare development in various countries worldwide.
Funding
This research received no external funding.
Data Availability Statement
The data presented in this study are available on request from the corresponding author. This research uses data from (Forbes 2024; IMD Business School 2024; Ministry of Healthcare of the Republic of Tatarstan 2024; MOEX 2024a, 2024b, 2024c; Rosstat 2024; World Bank 2024).
Conflicts of Interest
The author declares no conflict of interest.
Appendix A
Table A1.
MOEX trade data in 2022–2024.
| Trade Date | Sectoral Consumer Index, Billions of Rubles | Sectoral Information Technology Index, Billions of Rubles | Moscow Exchange Index—RSPP Sustainable Development Index, Billions of Rubles |
|---|---|---|---|
| 14 June 2022 | 0.56564 | 0.64172 | 27.99602 |
| 15 June 2022 | 0.85600 | 0.99115 | 28.38763 |
| 16 June 2022 | 1.04720 | 1.26425 | 30.57209 |
| 17 June 2022 | 0.53581 | 1.02014 | 18.63946 |
| 20 June 2022 | 0.57848 | 1.11919 | 30.49453 |
| 21 June 2022 | 0.66451 | 1.16708 | 42.99464 |
| 22 June 2022 | 0.97041 | 0.67681 | 39.50449 |
| 23 June 2022 | 0.90583 | 1.11728 | 44.13567 |
| 24 June 2022 | 1.24181 | 0.59856 | 28.92149 |
| 27 June 2022 | 0.96818 | 1.30667 | 26.97536 |
| 28 June 2022 | 1.16765 | 1.23594 | 31.98768 |
| 29 June 2022 | 0.92891 | 0.81410 | 31.40814 |
| 30 June 2022 | 1.26743 | 1.18954 | 105.31335 |
| 1 July 2022 | 0.60438 | 0.53426 | 45.17525 |
| 4 July 2022 | 0.68390 | 0.81579 | 34.83523 |
| 5 July 2022 | 0.85070 | 0.82329 | 41.39075 |
| 6 July 2022 | 0.81773 | 1.28210 | 37.24500 |
| 7 July 2022 | 1.65186 | 1.54083 | 26.15761 |
| 8 July 2022 | 1.10539 | 1.23308 | 19.50443 |
| 11 July 2022 | 0.74687 | 1.65477 | 26.57320 |
| 12 July 2022 | 0.75220 | 1.40440 | 29.53024 |
| 13 July 2022 | 0.84102 | 1.03455 | 25.20407 |
| 14 July 2022 | 0.66130 | 0.89866 | 22.47313 |
| 15 July 2022 | 0.76545 | 0.70207 | 21.24793 |
| 18 July 2022 | 0.92740 | 1.71826 | 17.86446 |
| 19 July 2022 | 1.17254 | 1.09276 | 19.11111 |
| 20 July 2022 | 0.88103 | 1.42590 | 22.11271 |
| 21 July 2022 | 0.69895 | 0.80945 | 22.54589 |
| 22 July 2022 | 0.70159 | 1.40052 | 19.81628 |
| 25 July 2022 | 0.77521 | 3.83234 | 22.08394 |
| 26 July 2022 | 1.47729 | 8.50538 | 24.54456 |
| 27 July 2022 | 1.54489 | 5.51935 | 27.67511 |
| 28 July 2022 | 2.33977 | 2.39189 | 23.34116 |
| 29 July 2022 | 2.02040 | 3.57636 | 19.45123 |
| 1 August 2022 | 2.20888 | 2.73880 | 28.02166 |
| 2 August 2022 | 2.02838 | 1.98029 | 23.45250 |
| 3 August 2022 | 1.71868 | 3.03637 | 22.90252 |
| 4 August 2022 | 2.10154 | 3.33784 | 17.75422 |
| 5 August 2022 | 1.69578 | 4.43926 | 29.39962 |
| 8 August 2022 | 1.27741 | 2.56122 | 23.67322 |
| 9 August 2022 | 2.23795 | 2.25912 | 22.29464 |
| 10 August 2022 | 1.27739 | 2.97512 | 21.50850 |
| 11 August 2022 | 2.11760 | 3.56801 | 23.18959 |
| 12 August 2022 | 1.48599 | 2.56042 | 17.25031 |
| 15 August 2022 | 1.55145 | 2.07321 | 18.17366 |
| 16 August 2022 | 1.24895 | 1.10302 | 23.34084 |
| 17 August 2022 | 1.78023 | 1.52101 | 23.61313 |
| 18 August 2022 | 1.24280 | 0.71282 | 16.88929 |
| 19 August 2022 | 2.51367 | 0.78137 | 16.19422 |
| 22 August 2022 | 1.45118 | 1.91230 | 18.78926 |
| 23 August 2022 | 1.24204 | 5.36600 | 25.71291 |
| 24 August 2022 | 1.55973 | 2.37783 | 17.99767 |
| 25 August 2022 | 2.35737 | 1.64941 | 19.59143 |
| 26 August 2022 | 1.04560 | 1.11703 | 14.80855 |
| 29 August 2022 | 1.03778 | 0.99082 | 22.13029 |
| 30 August 2022 | 1.18040 | 2.78910 | 43.91562 |
| 31 August 2022 | 1.43593 | 2.11641 | 96.64147 |
| 1 September 2022 | 0.91692 | 1.38927 | 52.40513 |
| 2 September 2022 | 0.99976 | 1.36919 | 52.12463 |
| 5 September 2022 | 1.16887 | 0.95697 | 41.14208 |
| 6 September 2022 | 1.68913 | 3.19358 | 56.24458 |
| 7 September 2022 | 1.00951 | 1.39237 | 34.05352 |
| 8 September 2022 | 1.20197 | 1.08533 | 29.09496 |
| 9 September 2022 | 0.73929 | 1.26160 | 25.11743 |
| 12 September 2022 | 1.22794 | 2.71228 | 28.36995 |
| 13 September 2022 | 1.23014 | 2.25742 | 21.60172 |
| 14 September 2022 | 1.38277 | 1.56780 | 28.85330 |
| 15 September 2022 | 1.33370 | 1.58798 | 30.64729 |
| 16 September 2022 | 1.11348 | 3.23267 | 32.05362 |
| 19 September 2022 | 0.84706 | 3.47291 | 19.55283 |
| 20 September 2022 | 3.63293 | 13.32335 | 104.77861 |
| 21 September 2022 | 2.60750 | 7.15776 | 64.97510 |
| 22 September 2022 | 1.52281 | 3.77186 | 61.05043 |
| 23 September 2022 | 1.89666 | 4.46229 | 47.75351 |
| 26 September 2022 | 2.58102 | 6.54512 | 67.68958 |
| 27 September 2022 | 1.32975 | 4.50788 | 43.08281 |
| 28 September 2022 | 1.09094 | 5.22437 | 40.03439 |
| 29 September 2022 | 1.34789 | 4.39201 | 34.26735 |
| 30 September 2022 | 1.68574 | 5.56868 | 89.29365 |
| 3 October 2022 | 2.23687 | 3.32388 | 36.43577 |
| 4 October 2022 | 1.53849 | 4.53730 | 38.01856 |
| 5 October 2022 | 2.08660 | 5.49099 | 41.35793 |
| 6 October 2022 | 1.09095 | 2.52666 | 28.70274 |
| 7 October 2022 | 0.95608 | 2.22062 | 35.74923 |
| 10 October 2022 | 1.57154 | 3.92483 | 48.34901 |
| 11 October 2022 | 1.49981 | 2.43774 | 26.59083 |
| 12 October 2022 | 1.13903 | 3.01489 | 22.33467 |
| 13 October 2022 | 1.00078 | 2.97931 | 19.46926 |
| 14 October 2022 | 0.84618 | 2.56637 | 18.99740 |
| 17 October 2022 | 1.65692 | 2.01766 | 27.66319 |
| 18 October 2022 | 1.21039 | 1.88368 | 29.17420 |
| 19 October 2022 | 1.58798 | 3.68031 | 29.66784 |
| 20 October 2022 | 1.25205 | 1.57402 | 30.96174 |
| 21 October 2022 | 1.09147 | 1.21582 | 30.17768 |
| 24 October 2022 | 1.20491 | 1.22123 | 28.45181 |
| 25 October 2022 | 1.52750 | 2.07819 | 36.76357 |
| 26 October 2022 | 1.38424 | 1.61688 | 37.07389 |
| 27 October 2022 | 1.63863 | 1.54762 | 35.73934 |
| 28 October 2022 | 1.07130 | 1.61884 | 38.62707 |
| 31 October 2022 | 1.04341 | 2.35022 | 26.24728 |
| 1 November 2022 | 0.81638 | 2.38163 | 16.55119 |
| 2 November 2022 | 0.68995 | 1.70034 | 18.57346 |
| 3 November 2022 | 0.97099 | 2.33200 | 21.26411 |
| 7 November 2022 | 4.17614 | 2.20051 | 33.49072 |
| 8 November 2022 | 8.50138 | 1.26182 | 26.47281 |
| 9 November 2022 | 2.70452 | 2.03576 | 25.76100 |
| 10 November 2022 | 2.28785 | 3.02502 | 41.78653 |
| 11 November 2022 | 2.29845 | 1.74529 | 27.43098 |
| 14 November 2022 | 4.84935 | 1.99227 | 29.68329 |
| 15 November 2022 | 4.53147 | 2.58411 | 26.66000 |
| 16 November 2022 | 1.81418 | 1.75715 | 23.04922 |
| 17 November 2022 | 2.38036 | 1.23500 | 19.53111 |
| 18 November 2022 | 2.02611 | 1.11443 | 15.08518 |
| 21 November 2022 | 2.70763 | 1.87574 | 21.53472 |
| 22 November 2022 | 1.50375 | 1.35385 | 17.65111 |
| 23 November 2022 | 1.21409 | 2.08254 | 26.61912 |
| 24 November 2022 | 1.12123 | 1.10951 | 16.90852 |
| 25 November 2022 | 0.83785 | 3.80554 | 13.31504 |
| 28 November 2022 | 0.83971 | 4.54777 | 18.91871 |
| 29 November 2022 | 1.11620 | 2.59338 | 17.06443 |
| 30 November 2022 | 0.56719 | 1.74357 | 12.65903 |
| 1 December 2022 | 0.94879 | 1.01136 | 18.02069 |
| 2 December 2022 | 1.94250 | 0.82041 | 18.19417 |
| 5 December 2022 | 2.74165 | 1.66701 | 31.08536 |
| 6 December 2022 | 3.58431 | 1.10214 | 18.87228 |
| 7 December 2022 | 3.54489 | 0.85702 | 24.30727 |
| 8 December 2022 | 1.62626 | 1.00717 | 19.26002 |
| 9 December 2022 | 1.03866 | 0.56230 | 12.26192 |
| 12 December 2022 | 1.94674 | 0.77740 | 15.42742 |
| 13 December 2022 | 2.32987 | 1.19454 | 21.13582 |
| 14 December 2022 | 1.46664 | 1.86509 | 17.30160 |
| 15 December 2022 | 1.90034 | 1.73442 | 25.66545 |
| 16 December 2022 | 0.99874 | 0.67712 | 16.88950 |
| 19 December 2022 | 1.60466 | 1.51515 | 25.97777 |
| 20 December 2022 | 1.62387 | 1.29106 | 29.75309 |
| 21 December 2022 | 1.32982 | 1.58644 | 25.85237 |
| 22 December 2022 | 1.17881 | 1.18354 | 18.20114 |
| 23 December 2022 | 1.19028 | 1.47653 | 14.15360 |
| 26 December 2022 | 1.32786 | 1.06997 | 18.25181 |
| 27 December 2022 | 1.20099 | 1.07514 | 18.19703 |
| 28 December 2022 | 1.19643 | 0.93339 | 15.02767 |
| 29 December 2022 | 0.88125 | 0.69445 | 12.39644 |
| 30 December 2022 | 1.66064 | 0.89920 | 13.45710 |
| 3 January 2023 | 0.57530 | 0.71791 | 10.78736 |
| 4 January 2023 | 0.51277 | 0.62826 | 9.87648 |
| 5 January 2023 | 0.69901 | 0.42901 | 8.18847 |
| 6 January 2023 | 0.41239 | 0.25867 | 6.56940 |
| 9 January 2023 | 0.80345 | 0.71788 | 15.39118 |
| 10 January 2023 | 0.96101 | 0.71643 | 11.78893 |
| 11 January 2023 | 1.21427 | 1.66466 | 30.57844 |
| 12 January 2023 | 3.88817 | 1.25746 | 18.20563 |
| 13 January 2023 | 1.85107 | 1.02875 | 24.40286 |
| 16 January 2023 | 1.77578 | 2.00457 | 21.29005 |
| 17 January 2023 | 2.69430 | 1.73179 | 24.66017 |
| 18 January 2023 | 1.54559 | 1.40703 | 20.28858 |
| 19 January 2023 | 1.79549 | 0.86372 | 21.29277 |
| 20 January 2023 | 1.15994 | 0.91835 | 9.52385 |
| 23 January 2023 | 1.09099 | 1.68344 | 10.57057 |
| 24 January 2023 | 1.22863 | 1.69219 | 12.94293 |
| 25 January 2023 | 0.63337 | 1.22476 | 12.81807 |
| 26 January 2023 | 0.70169 | 0.98869 | 13.30416 |
| 27 January 2023 | 0.75281 | 0.88454 | 12.31145 |
| 30 January 2023 | 1.06616 | 1.58108 | 14.14406 |
| 31 January 2023 | 1.17126 | 3.58161 | 15.28480 |
| 1 February 2023 | 1.14620 | 4.35791 | 20.12608 |
| 2 February 2023 | 1.48894 | 1.34241 | 18.65590 |
| 3 February 2023 | 0.98823 | 1.62998 | 29.02999 |
| 6 February 2023 | 1.31816 | 2.14556 | 21.33761 |
| 7 February 2023 | 1.09174 | 1.43553 | 18.87847 |
| 8 February 2023 | 2.10517 | 1.55650 | 21.31050 |
| 9 February 2023 | 0.83059 | 1.00782 | 15.07022 |
| 10 February 2023 | 0.85377 | 0.89993 | 11.30958 |
| 13 February 2023 | 0.70518 | 1.15355 | 10.02770 |
| 14 February 2023 | 1.13512 | 3.32459 | 14.34248 |
| 15 February 2023 | 1.43457 | 4.59882 | 21.20682 |
| 16 February 2023 | 1.23817 | 2.00466 | 17.14709 |
| 17 February 2023 | 0.70103 | 1.08127 | 11.89729 |
| 20 February 2023 | 0.67748 | 1.39596 | 15.82409 |
| 21 February 2023 | 0.94701 | 2.94527 | 20.59059 |
| 22 February 2023 | 0.56492 | 0.75146 | 10.63734 |
| 24 February 2023 | 040861 | 0.70712 | 7.90013 |
| 27 February 2023 | 1.07575 | 2.02470 | 13.09937 |
| 28 February 2023 | 0.94847 | 1.32406 | 18.06792 |
| 1 March 2023 | 1.77585 | 1.59726 | 26.00092 |
| 2 March 2023 | 1.30379 | 3.14597 | 27.38074 |
| 3 March 2023 | 0.62026 | 0.91806 | 14.45207 |
| 6 March 2023 | 1.35357 | 2.20413 | 16.28397 |
| 7 March 2023 | 1.21133 | 1.15560 | 11.31256 |
| 9 March 2023 | 2.51397 | 1.43792 | 10.90823 |
| 10 March 2023 | 2.13075 | 1.31926 | 12.57054 |
| 13 March 2023 | 2.44969 | 2.42765 | 20.03938 |
| 14 March 2023 | 1.12588 | 2.24654 | 17.50683 |
| 15 March 2023 | 2.56471 | 2.33912 | 20.24978 |
| 16 March 2023 | 1.38695 | 4.01596 | 17.07031 |
| 17 March 2023 | 3.00191 | 2.05282 | 24.59690 |
| 20 March 2023 | 2.14647 | 2.03230 | 41.03922 |
| 21 March 2023 | 1.86507 | 1.45513 | 35.19507 |
| 22 March 2023 | 1.08435 | 0.98278 | 17.22208 |
| 23 March 2023 | 2.56448 | 0.79660 | 13.82263 |
| 24 March 2023 | 1.37773 | 0.71599 | 11.52473 |
| 27 March 2023 | 2.90358 | 1.75976 | 21.71998 |
| 28 March 2023 | 2.20870 | 1.59849 | 19.64052 |
| 29 March 2023 | 2.66244 | 1.66066 | 18.12083 |
| 30 March 2023 | 1.84511 | 1.46170 | 13.80070 |
| 31 March 2023 | 4.45127 | 1.50084 | 23.28605 |
| 3 April 2023 | 4.66643 | 1.40704 | 23.67021 |
| 4 April 2023 | 3.80897 | 2.18507 | 30.68943 |
| 5 April 2023 | 3.63350 | 1.52631 | 20.13571 |
| 6 April 2023 | 3.37912 | 3.87533 | 21.22918 |
| 7 April 2023 | 1.69743 | 1.46509 | 15.16627 |
| 10 April 2023 | 3.38592 | 4.00315 | 21.74651 |
| 11 April 2023 | 5.97882 | 3.99625 | 46.89453 |
| 12 April 2023 | 2.21434 | 1.43572 | 22.50166 |
| 13 April 2023 | 1.93256 | 1.15460 | 19.27121 |
| 14 April 2023 | 1.65103 | 0.92950 | 20.88768 |
| 17 April 2023 | 4.80924 | 1.32981 | 24.54848 |
| 18 April 2023 | 4.28223 | 1.78360 | 26.98133 |
| 19 April 2023 | 4.27173 | 2.97348 | 34.01326 |
| 20 April 2023 | 4.16997 | 4.21780 | 41.25602 |
| 21 April 2023 | 1.55890 | 3.48114 | 17.20861 |
| 24 April 2023 | 2.84951 | 1.74963 | 21.20463 |
| 25 April 2023 | 3.68548 | 1.23394 | 15.28662 |
| 26 April 2023 | 2.53491 | 3.17438 | 14.28672 |
| 27 April 2023 | 2.59207 | 4.78749 | 22.42026 |
| 28 April 2023 | 2.35701 | 2.08409 | 22.79354 |
| 2 May 2023 | 3.99983 | 3.03882 | 29.78406 |
| 3 May 2023 | 3.41860 | 2.59602 | 26.67694 |
| 4 May 2023 | 1.87763 | 2.36310 | 18.22405 |
| 5 May 2023 | 1.31342 | 2.50396 | 14.02016 |
| 8 May 2023 | 0.51376 | 0.71457 | 7.66551 |
| 10 May 2023 | 1.65239 | 2.16414 | 28.80501 |
| 11 May 2023 | 1.99162 | 2.36986 | 30.59091 |
| 12 May 2023 | 2.98444 | 1.19717 | 17.10445 |
| 15 May 2023 | 7.75829 | 2.71891 | 21.74550 |
| 16 May 2023 | 3.92478 | 1.88910 | 25.27799 |
| 17 May 2023 | 1.97714 | 1.51534 | 16.87974 |
| 18 May 2023 | 1.75583 | 1.74856 | 17.52580 |
| 19 May 2023 | 2.15398 | 16.10343 | 23.35445 |
| 22 May 2023 | 2.34975 | 9.70191 | 20.39987 |
| 23 May 2023 | 1.42378 | 3.78757 | 45.80178 |
| 24 May 2023 | 14.56595 | 4.50004 | 38.26146 |
| 25 May 2023 | 8.80410 | 8.28989 | 29.68610 |
| 26 May 2023 | 6.20869 | 4.17126 | 23.58286 |
| 29 May 2023 | 3.98096 | 5.30610 | 31.93380 |
| 30 May 2023 | 7.11065 | 5.84559 | 42.80909 |
| 31 May 2023 | 3.82569 | 4.11303 | 25.10469 |
| 1 June 2023 | 5.32097 | 2.56265 | 23.62914 |
| 2 June 2023 | 3.47547 | 3.17490 | 32.79456 |
| 5 June 2023 | 3.85901 | 6.20907 | 39.63808 |
| 6 June 2023 | 2.56478 | 4.56193 | 37.05465 |
| 7 June 2023 | 2.51702 | 7.81229 | 21.01130 |
| 8 June 2023 | 1.65396 | 8.70722 | 14.56558 |
| 9 June 2023 | 1.28561 | 5.20677 | 14.46054 |
| 13 June 2023 | 2.77519 | 4.47376 | 24.14832 |
| 14 June 2023 | 2.65749 | 4.68455 | 21.39645 |
| 15 June 2023 | 7.31429 | 4.82923 | 36.18466 |
| 16 June 2023 | 2.63578 | 7.03400 | 21.99463 |
| 19 June 2023 | 15.11721 | 3.73983 | 39.55293 |
| 20 June 2023 | 7.25275 | 3.52057 | 29.59675 |
| 21 June 2023 | 4.05879 | 3.19511 | 24.13828 |
| 22 June 2023 | 3.43386 | 1.92665 | 19.61967 |
| 23 June 2023 | 3.04046 | 6.09768 | 20.46504 |
| 26 June 2023 | 3.66380 | 4.40467 | 22.81709 |
| 27 June 2023 | 3.62073 | 3.38508 | 21.64746 |
| 28 June 2023 | 7.27142 | 2.71049 | 20.70826 |
| 29 June 2023 | 7.03941 | 1.69154 | 21.91114 |
| 30 June 2023 | 3.84716 | 1.60963 | 17.32246 |
| 3 July 2023 | 6.81877 | 2.22449 | 23.30072 |
| 4 July 2023 | 4.59776 | 2.14037 | 23.13697 |
| 5 July 2023 | 4.57284 | 1.78105 | 23.63743 |
| 6 July 2023 | 3.04988 | 1.80630 | 27.82185 |
| 7 July 2023 | 3.17596 | 1.87626 | 20.91706 |
| 10 July 2023 | 5.53516 | 2.41296 | 59.15426 |
| 11 July 2023 | 7.86891 | 2.32459 | 25.10622 |
| 12 July 2023 | 6.58049 | 2.48489 | 26.33379 |
| 13 July 2023 | 5.86878 | 2.72432 | 26.00497 |
| 14 July 2023 | 3.43560 | 6.87780 | 18.76778 |
| 17 July 2023 | 6.47134 | 6.95208 | 26.52058 |
| 18 July 2023 | 9.62757 | 4.45097 | 43.44609 |
| 19 July 2023 | 9.90037 | 3.44592 | 32.27638 |
| 20 July 2023 | 8.62700 | 5.04933 | 34.10129 |
| 21 July 2023 | 7.45200 | 2.67444 | 24.40583 |
| 24 July 2023 | 9.73560 | 7.27157 | 23.35038 |
| 25 July 2023 | 8.57833 | 7.45036 | 26.74706 |
| 26 July 2023 | 15.92018 | 8.05605 | 29.54624 |
| 27 July 2023 | 8.71293 | 7.49585 | 22.71470 |
| 28 July 2023 | 5.84854 | 4.77405 | 23.89610 |
| 31 July 2023 | 7.39261 | 5.35818 | 36.80181 |
| 1 August 2023 | 5.93881 | 6.04149 | 34.80229 |
| 2 August 2023 | 5.46829 | 5.94114 | 32.72633 |
| 3 August 2023 | 8.23029 | 8.23198 | 36.00280 |
| 4 August 2023 | 13.30669 | 20.50265 | 60.86068 |
| 7 August 2023 | 8.32649 | 6.07264 | 33.74518 |
| 8 August 2023 | 8.13521 | 7.04919 | 33.13210 |
| 9 August 2023 | 7.58379 | 4.30160 | 26.61889 |
| 10 August 2023 | 5.68283 | 12.07647 | 29.59444 |
| 11 August 2023 | 5.65054 | 6.61310 | 24.07441 |
| 14 August 2023 | 11.93216 | 7.53668 | 79.04724 |
| 15 August 2023 | 7.41423 | 6.36706 | 48.29234 |
| 16 August 2023 | 6.19428 | 8.15020 | 43.96706 |
| 17 August 2023 | 5.36138 | 5.88626 | 26.47765 |
| 18 August 2023 | 5.09195 | 3.95719 | 21.95660 |
| 21 August 2023 | 10.39923 | 6.96901 | 32.64076 |
| 22 August 2023 | 7.39240 | 7.20449 | 51.46474 |
| 23 August 2023 | 6.71331 | 11.21990 | 38.59205 |
| 24 August 2023 | 3.64143 | 3.83989 | 20.30456 |
| 25 August 2023 | 5.39051 | 3.01511 | 19.09267 |
| 28 August 2023 | 6.65614 | 3.45192 | 27.01241 |
| 29 August 2023 | 9.77710 | 4.64408 | 48.80436 |
| 30 August 2023 | 12.66598 | 4.39860 | 40.42660 |
| 31 August 2023 | 12.62782 | 4.26942 | 30.71677 |
| 1 September 2023 | 5.39738 | 2.94253 | 22.26889 |
| 4 September 2023 | 11.65340 | 6.36640 | 31.56825 |
| 5 September 2023 | 13.58297 | 4.39443 | 37.59155 |
| 6 September 2023 | 5.97287 | 4.37156 | 34.12973 |
| 7 September 2023 | 11.81410 | 7.98046 | 57.00610 |
| 8 September 2023 | 8.53163 | 4.48975 | 34.48844 |
| 11 September 2023 | 11.00327 | 6.90842 | 30.98824 |
| 12 September 2023 | 5.93023 | 6.87661 | 27.02650 |
| 13 September 2023 | 4.65719 | 5.67690 | 21.24406 |
| 14 September 2023 | 7.80477 | 5.48714 | 36.57079 |
| 15 September 2023 | 5.25325 | 3.44509 | 24.32628 |
| 18 September 2023 | 5.59146 | 3.86619 | 22.29665 |
| 19 September 2023 | 8.03151 | 4.35061 | 42.14926 |
| 20 September 2023 | 9.74435 | 5.69623 | 43.47706 |
| 21 September 2023 | 8.25702 | 3.55030 | 41.74437 |
| 22 September 2023 | 7.20766 | 4.14944 | 37.45400 |
| 25 September 2023 | 4.09699 | 2.41078 | 23.23195 |
| 26 September 2023 | 4.40787 | 2.36040 | 27.07138 |
| 27 September 2023 | 6.05282 | 3.99154 | 22.56257 |
| 28 September 2023 | 5.28281 | 3.36098 | 24.90930 |
| 29 September 2023 | 6.24424 | 3.03747 | 24.99228 |
| 2 October 2023 | 4.23526 | 3.60317 | 29.09208 |
| 3 October 2023 | 4.69920 | 2.62133 | 23.31801 |
| 4 October 2023 | 3.25517 | 3.10001 | 22.21755 |
| 5 October 2023 | 2.24713 | 5.49401 | 16.62019 |
| 6 October 2023 | 2.32597 | 4.36537 | 19.26818 |
| 9 October 2023 | 2.63193 | 2.59883 | 26.44235 |
| 10 October 2023 | 4.00781 | 2.90472 | 18.96142 |
| 11 October 2023 | 5.45834 | 2.88615 | 43.88311 |
| 12 October 2023 | 3.51059 | 2.24261 | 38.06281 |
| 13 October 2023 | 5.27470 | 4.35632 | 28.11967 |
| 16 October 2023 | 4.96613 | 4.51877 | 32.16102 |
| 17 October 2023 | 6.34171 | 12.08303 | 28.59320 |
| 18 October 2023 | 4.32713 | 7.37922 | 41.27950 |
| 19 October 2023 | 5.73365 | 10.54316 | 25.50750 |
| 20 October 2023 | 5.76026 | 18.92229 | 29.78248 |
| 23 October 2023 | 8.45968 | 10.39348 | 27.06937 |
| 24 October 2023 | 11.82479 | 7.06260 | 22.44506 |
| 25 October 2023 | 8.15685 | 6.07476 | 24.28254 |
| 26 October 2023 | 6.19704 | 7.37764 | 39.96625 |
| 27 October 2023 | 5.96325 | 8.66856 | 32.75320 |
| 30 October 2023 | 3.58149 | 4.63347 | 20.14883 |
| 31 October 2023 | 4.76843 | 5.03759 | 25.36375 |
| 1 November 2023 | 2.28197 | 3.66541 | 16.32683 |
| 2 November 2023 | 2.66016 | 4.15101 | 22.74401 |
| 3 November 2023 | 1.65354 | 5.09496 | 23.50983 |
| 6 November 2023 | 1.67305 | 3.79787 | 15.61257 |
| 7 November 2023 | 6.44331 | 4.38902 | 17.71759 |
| 8 November 2023 | 6.42032 | 3.83915 | 19.34456 |
| 9 November 2023 | 3.56202 | 4.03756 | 19.57507 |
| 10 November 2023 | 3.26795 | 3.48781 | 19.21993 |
| 13 November 2023 | 5.96856 | 3.86816 | 15.48535 |
| 14 November 2023 | 4.61907 | 7.79587 | 22.91810 |
| 15 November 2023 | 5.86054 | 4.70930 | 20.06964 |
| 16 November 2023 | 3.76387 | 8.16897 | 13.54996 |
| 17 November 2023 | 3.85692 | 3.85311 | 22.16339 |
| 20 November 2023 | 6.00354 | 5.97355 | 13.30881 |
| 21 November 2023 | 5.15819 | 6.45787 | 17.26859 |
| 22 November 2023 | 3.75636 | 7.08385 | 19.47197 |
| 23 November 2023 | 3.63900 | 3.18204 | 17.84675 |
| 24 November 2023 | 7.87793 | 4.61305 | 25.65666 |
| 27 November 2023 | 5.76383 | 6.76428 | 31.82678 |
| 28 November 2023 | 4.08773 | 3.77426 | 26.89677 |
| 29 November 2023 | 3.30567 | 3.77904 | 16.27984 |
| 30 November 2023 | 4.48273 | 3.80571 | 20.92147 |
| 1 December 2023 | 4.37627 | 5.03807 | 16.14825 |
| 4 December 2023 | 4.78943 | 4.91568 | 20.86479 |
| 5 December 2023 | 4.01359 | 2.99350 | 17.16020 |
| 6 December 2023 | 4.49379 | 3.62595 | 18.11537 |
| 7 December 2023 | 4.06570 | 4.34876 | 24.25215 |
| 8 December 2023 | 2.77642 | 2.49450 | 14.26969 |
| 11 December 2023 | 3.87421 | 7.89706 | 25.63163 |
| 12 December 2023 | 3.65508 | 6.84020 | 25.21609 |
| 13 December 2023 | 2.33804 | 4.26527 | 13.81412 |
| 14 December 2023 | 2.06563 | 3.32956 | 17.04763 |
| 15 December 2023 | 5.05855 | 5.94605 | 31.22134 |
| 18 December 2023 | 7.00075 | 5.09179 | 27.69312 |
| 19 December 2023 | 5.05861 | 3.33306 | 24.05775 |
| 20 December 2023 | 5.99303 | 5.96328 | 25.74727 |
| 21 December 2023 | 4.29841 | 3.54917 | 31.50374 |
| 22 December 2023 | 3.27177 | 2.83142 | 19.47991 |
| 25 December 2023 | 5.98365 | 11.29861 | 22.51077 |
| 26 December 2023 | 4.66696 | 4.91746 | 21.61347 |
| 27 December 2023 | 5.26761 | 6.75403 | 21.67783 |
| 28 December 2023 | 4.65682 | 7.33297 | 18.51277 |
| 29 December 2023 | 4.28980 | 3.54289 | 13.53212 |
| 3 January 2024 | 2.61483 | 1.64263 | 8.63431 |
| 4 January 2024 | 3.19638 | 2.18452 | 7.94484 |
| 5 January 2024 | 2.29583 | 1.46313 | 7.47576 |
| 8 January 2024 | 3.79251 | 2.74255 | 13.02943 |
| 9 January 2024 | 4.57191 | 5.95937 | 21.47083 |
| 10 January 2024 | 7.53011 | 4.08227 | 20.74534 |
| 11 January 2024 | 9.78801 | 3.25485 | 41.15712 |
| 12 January 2024 | 4.33776 | 7.09724 | 23.71312 |
| 15 January 2024 | 5.46085 | 6.99762 | 19.24384 |
| 16 January 2024 | 6.59570 | 5.29545 | 17.27628 |
| 17 January 2024 | 5.45634 | 2.79564 | 13.97520 |
| 18 January 2024 | 6.75250 | 4.09971 | 20.50263 |
| 19 January 2024 | 7.14290 | 4.44495 | 28.64306 |
| 22 January 2024 | 3.87411 | 6.55212 | 25.82746 |
| 23 January 2024 | 3.26985 | 9.13538 | 27.71361 |
| 24 January 2024 | 4.01593 | 4.11811 | 30.90297 |
| 25 January 2024 | 5.34895 | 7.28930 | 25.81393 |
| 26 January 2024 | 5.13325 | 17.20864 | 20.49367 |
| 29 January 2024 | 3.50272 | 10.99028 | 27.32711 |
| 30 January 2024 | 6.37799 | 19.32037 | 36.97106 |
| 31 January 2024 | 4.97154 | 10.66033 | 39.61441 |
| 1 February 2024 | 6.09260 | 10.69214 | 31.15784 |
| 2 February 2024 | 4.05943 | 7.34145 | 39.47374 |
| 5 February 2024 | 4.43060 | 34.16081 | 32.81532 |
| 6 February 2024 | 5.56662 | 11.66409 | 26.52416 |
| 7 February 2024 | 5.86050 | 22.39007 | 37.26940 |
| 8 February 2024 | 6.95607 | 34.16597 | 41.06956 |
| 9 February 2024 | 4.53124 | 9.35346 | 29.73620 |
| 12 February 2024 | 4.18223 | 9.34600 | 31.64175 |
| 13 February 2024 | 3.77529 | 18.27113 | 30.82587 |
| 14 February 2024 | 4.43517 | 16.34683 | 31.41288 |
| 15 February 2024 | 6.02485 | 13.86580 | 30.53398 |
| 16 February 2024 | 5.10615 | 15.21716 | 44.04792 |
| 19 February 2024 | 3.47664 | 6.72738 | 35.23351 |
| 20 February 2024 | 3.86048 | 10.13651 | 42.37994 |
| 21 February 2024 | 6.34098 | 13.82801 | 60.10240 |
| 22 February 2024 | 4.01727 | 6.27459 | 42.05992 |
| 26 February 2024 | 4.43185 | 7.68888 | 42.96056 |
| 27 February 2024 | 4.35548 | 5.51469 | 35.39979 |
| 28 February 2024 | 8.52547 | 6.47950 | 39.85000 |
| 29 February 2024 | 5.84495 | 4.45758 | 33.85668 |
| 1 March 2024 | 4.24058 | 12.28615 | 36.61440 |
| 4 March 2024 | 9.81114 | 18.36694 | 52.99509 |
| 5 March 2024 | 6.15705 | 11.83079 | 42.31176 |
| 6 March 2024 | 4.93081 | 7.13453 | 33.13119 |
| 7 March 2024 | 5.27587 | 7.91604 | 26.40379 |
| 11 March 2024 | 8.11371 | 13.42180 | 37.63339 |
| 12 March 2024 | 7.34867 | 6.37997 | 38.54861 |
| 13 March 2024 | 4.16745 | 8.73012 | 40.07410 |
| 14 March 2024 | 5.70191 | 8.12997 | 48.73914 |
| 15 March 2024 | 3.13766 | 8.26409 | 30.74037 |
| 18 March 2024 | 4.28734 | 10.36144 | 28.57374 |
| 19 March 2024 | 6.79873 | 22.17802 | 59.55451 |
| 20 March 2024 | 7.75655 | 17.22795 | 53.88659 |
| 21 March 2024 | 6.42314 | 19.26992 | 63.02834 |
| 22 March 2024 | 7.78432 | 5.10142 | 59.02223 |
| 25 March 2024 | 7.06777 | 4.96461 | 44.55016 |
| 26 March 2024 | 5.70045 | 7.48321 | 34.76662 |
| 27 March 2024 | 8.07895 | 5.96386 | 30.08404 |
| 28 March 2024 | 7.89635 | 4.87030 | 38.99496 |
| 29 March 2024 | 6.78527 | 3.43871 | 34.03644 |
| 1 April 2024 | 24.22461 | 5.62158 | 64.09039 |
| 2 April 2024 | 12.05216 | 4.70861 | 44.55150 |
| 3 April 2024 | 9.98448 | 5.52375 | 56.70100 |
| 4 April 2024 | 6.03883 | 5.29414 | 56.80292 |
| 5 April 2024 | 4.32873 | 5.08334 | 39.79676 |
| 8 April 2024 | 6.41328 | 3.97277 | 48.35494 |
| 9 April 2024 | 6.25021 | 7.33220 | 61.55309 |
| 10 April 2024 | 2.93819 | 4.87061 | 48.10075 |
| 11 April 2024 | 3.16317 | 2.29580 | 36.49345 |
| 12 April 2024 | 3.87669 | 3.38428 | 45.49791 |
| 15 April 2024 | 5.20539 | 4.48404 | 46.24613 |
| 16 April 2024 | 5.79870 | 4.65314 | 36.68424 |
| 17 April 2024 | 3.67385 | 5.68555 | 42.05185 |
| 18 April 2024 | 3.72720 | 7.90142 | 33.91920 |
| 19 April 2024 | 3.71848 | 11.25784 | 30.78121 |
| 22 April 2024 | 4.13263 | 6.95367 | 51.04292 |
| 23 April 2024 | 4.66947 | 3.84350 | 63.43663 |
| 24 April 2024 | 4.49464 | 5.87537 | 33.89852 |
| 25 April 2024 | 5.30457 | 4.58229 | 28.93323 |
| 26 April 2024 | 6.33021 | 4.20146 | 32.27588 |
| 27 April 2024 | 4.82089 | 3.31165 | 29.65086 |
| 29 April 2024 | 5.74703 | 2.45711 | 19.73130 |
| 30 April 2024 | 2.80715 | 2.89596 | 15.86041 |
| 2 May 2024 | 8.40346 | 4.19546 | 43.14447 |
| 3 May 2024 | 5.16578 | 3.39034 | 35.97426 |
| 6 May 2024 | 5.77787 | 4.05558 | 44.13898 |
| 7 May 2024 | 5.51569 | 3.67204 | 36.70393 |
| 8 May 2024 | 3.64399 | 7.12354 | 28.03095 |
| 10 May 2024 | 2.09359 | 2.62937 | 19.92765 |
| 13 May 2024 | 9.17881 | 5.24258 | 35.13101 |
| 14 May 2024 | 6.46150 | 6.33617 | 34.60034 |
| 15 May 2024 | 5.23796 | 5.30118 | 43.10770 |
| 16 May 2024 | 6.14284 | 2.66626 | 38.25822 |
| 17 May 2024 | 3.93645 | 6.00279 | 42.96502 |
| 20 May 2024 | 5.39441 | 5.73458 | 47.56864 |
| 21 May 2024 | 6.03922 | 3.14811 | 65.79149 |
| 22 May 2024 | 3.46741 | 2.27181 | 36.89973 |
| 23 May 2024 | 4.46215 | 3.75456 | 53.23467 |
| 24 May 2024 | 7.43856 | 5.46506 | 52.99610 |
| 27 May 2024 | 5.46399 | 6.99586 | 72.57305 |
| 28 May 2024 | 4.61167 | 6.03839 | 51.21970 |
| 29 May 2024 | 4.31897 | 2.92489 | 43.17849 |
| 30 May 2024 | 6.51543 | 2.12355 | 33.70793 |
| 31 May 2024 | 5.60449 | 7.15739 | 48.65263 |
| 3 June 2024 | 17.67538 | 7.59950 | 78.23399 |
| 4 June 2024 | 6.72695 | 6.63777 | 46.92253 |
| 5 June 2024 | 7.16001 | 6.54042 | 44.87761 |
| 6 June 2024 | 3.78574 | 2.99996 | 30.90057 |
| 7 June 2024 | 5.97407 | 8.19336 | 52.18511 |
| 10 June 2024 | 4.75593 | 7.34871 | 43.78174 |
| 11 June 2024 | 4.60656 | 5.83556 | 48.10045 |
| 13 June 2024 | 5.52501 | 5.93135 | 68.00503 |
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Figure 1.
Financial risks of healthcare in the SEM model. Source: Calculated and developed by the author.
Figure 1.
Financial risks of healthcare in the SEM model. Source: Calculated and developed by the author.
Figure 2.
SEM model of financial risks in healthcare during the provision of high-tech medical care in Russia from a sustainable development perspective. Source: Calculated and developed by the author.
Figure 2.
SEM model of financial risks in healthcare during the provision of high-tech medical care in Russia from a sustainable development perspective. Source: Calculated and developed by the author.
Figure 3.
Prospects for reducing financial risks in healthcare during the provision of high-tech medical care in Russia until 2026, billions of rubles. Source: Calculated and developed by the author.
Figure 3.
Prospects for reducing financial risks in healthcare during the provision of high-tech medical care in Russia until 2026, billions of rubles. Source: Calculated and developed by the author.
Table 1.
Revenue of the top 20 largest healthcare organizations in Russia by income in 2021–2022 and analysis of its change.
Table 1.
Revenue of the top 20 largest healthcare organizations in Russia by income in 2021–2022 and analysis of its change.
| Healthcare Organizations | Revenue in 2022, Billions of Rubles | Revenue in 2021, Billions of Rubles | Annual Change, % |
|---|---|---|---|
| Medsi | 35.98 | 30.09 | 19.57 |
| Mother and Child | 25.22 | 25.22 | 0.00 |
| European Medical Center (EMC) | 23.20 | 25.23 | −8.05 |
| SM-Clinic | 17.20 | 15.70 | 9.55 |
| MedInvestGroup | 14.25 | 12.42 | 14.73 |
| Dr. Sergey Berezin Medical Institute (MIBS), St. Petersburg | 10.09 | 9.61 | 4.99 |
| Medscan | 8.46 | 4.31 | 96.29 |
| Scandinavia and Scandinavia AVA-PETER Clinics | 8.14 | 6.86 | 18.66 |
| Expert | 7.66 | 6.44 | 18.94 |
| Private medical centers “Ekaterininskaya” | 7.59 | 7.01 | 8.27 |
| MedSwiss | 6.94 | 6.68 | 3.89 |
| Medholding | 6.05 | 4.17 | 45.08 |
| Medicine | 6.03 | 5.34 | 12.92 |
| Semeyanya | 5.81 | 5.10 | 13.92 |
| Family Doctor Medical Network | 5.50 | 4.64 | 18.53 |
| My Medical Center Corporate Group | 5.14 | 5.96 | −13.76 |
| Bud Zdorov Medical Network | 4.27 | 3.94 | 8.38 |
| New Hospital | 3.88 | 3.67 | 5.72 |
| UMMC-Health | 3.69 | 3.37 | 9.50 |
| XXI Century Medical Center | 3.30 | 3.01 | 9.63 |
Source: Developed by the author based on Forbes’ materials (Forbes 2024).
Table 2.
Regression statistics and reliability tests.
| Type of Analysis | Element of Analysis | HLT | ICT | SST |
|---|---|---|---|---|
| Correlation analysis | Multiple R | 0.4966 | 0.4691 | 0.4385 |
| Multicollinearity Test (R2) | HLT | 1.00 | - | - |
| ICT | 0.4249 | 1.00 | - | |
| SST | 0.3890 | 0.3484 | 1.00 | |
| Variance analysis and Fisher’s F-test | Significance F | 6.6 × 10−32 | 4.4 × 10−28 | 3.1 × 10−24 |
| Significance level | 0.01 | 0.01 | 0.01 | |
| k1 = m | 2 | 2 | 2 | |
| k2 = n – m − 1 = 510 − 2 − 1 | 507 | 507 | 507 | |
| Table F | 4.6473 | 4.6473 | 4.6473 | |
| Observed F | 82.9916 | 71.5062 | 60.3411 | |
| F-test | passed | passed | passed | |
| Regression coefficients | Y-intercept | 1.1174 | 0.7444 | 20.2775 |
| HLT | - | 0.4553 | 1.3633 | |
| ICT | 0.2466 | - | 0.7754 | |
| SST | 0.0592 | 0.0622 | - | |
| Standard error | Y-intercept | 0.2703 | 0.3720 | 0.9638 |
| HLT | - | 0.0569 | 0.2044 | |
| ICT | 0.0308 | - | 0.1530 | |
| SST | 0.0089 | 0.0123 | - | |
| t-statistics | HLT | - | 8.0075 | 6.6708 |
| ICT | 8.0075 | - | 5.0671 | |
| SST | 6.6708 | 5.0671 | - | |
| Student’s t-test | Table t | 2.5855 | 2.5855 | 2.5855 |
| t-test | passed | passed | passed |
Source: Calculated and developed by the author.
Table 3.
Comparison of alternative approaches to risk management in healthcare in the provision of high-tech medical care.
Table 3.
Comparison of alternative approaches to risk management in healthcare in the provision of high-tech medical care.
| Comparison Criteria | The Current Approach in Russia | Proposed New Approach for Russia | ||||
|---|---|---|---|---|---|---|
| The main dimension of financial risks | Regulatory (Stancea and Muntean 2024) | Market-based | ||||
| Healthcare funding entity | State (Yang et al. 2024) | Private investors | ||||
| Beneficiaries of risk management to whom healthcare organizations are accountable | Consumers (Ding et al. 2024; Korah et al. 2023) | Healthcare workers (Bolisetty et al. 2023) | State healthcare regulators (Mohamad Taghvaee et al. 2023) | Investors in ICT and sustainable health development | ||
| Principal risks | Social risks (Przhedetsky et al. 2018) | Technological risks (Ishaq et al. 2024) | Epidemiological risks (Arianpoor and Naeimi Tajdar 2024) | Labor risks (Umair et al. 2024) | Financial risks in the regulatory dimension (Morozova et al. 2018) | Financial risks in the market dimension |
| Supported SDGs | Separately (Chen et al. 2023; Rahman et al. 2022; Shuyong et al. 2024; Udekwe et al. 2024) | systemically: SDG 3, SDG 9, and SDG 12 | ||||
| SDG 3 | SDG 8 | SDG 16 | ||||
| Risk management method | Ensuring accessibility, quality, continuity, and ethical provision of high-tech medical care | Providing jobs and opportunities for realizing the potential of healthcare workers | Correctness and purposefulness of spending of budget funds allocated for technological modernization | Ensuring a return on private investment in ICTs and sustainable health development | ||
Source: Developed and compiled by the author.
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Chililov, A.M. Financial Risk Management in Healthcare in the Provision of High-Tech Medical Assistance for Sustainable Development: Evidence from Russia. Risks 2024, 12, 134. https://doi.org/10.3390/risks12090134
AMA Style
Chililov AM. Financial Risk Management in Healthcare in the Provision of High-Tech Medical Assistance for Sustainable Development: Evidence from Russia. Risks. 2024; 12(9):134. https://doi.org/10.3390/risks12090134
Chicago/Turabian StyleChililov, Abdula M. 2024. "Financial Risk Management in Healthcare in the Provision of High-Tech Medical Assistance for Sustainable Development: Evidence from Russia" Risks 12, no. 9: 134. https://doi.org/10.3390/risks12090134
APA StyleChililov, A. M. (2024). Financial Risk Management in Healthcare in the Provision of High-Tech Medical Assistance for Sustainable Development: Evidence from Russia. Risks, 12(9), 134. https://doi.org/10.3390/risks12090134
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