Vision 2030 Healthcare Transformation
Healthcare Transformation in Saudi Arabia
The article “Healthcare Transformation in Saudi Arabia: An Overview Since the Launch of Vision 2030″ byAl-Rashed ..etc, published in 2022, provides an overview of the healthcare transformation in Saudi Arabia since the launch of Vision 2030¹². The study identifies issues that need to be addressed and steps taken towards the provision of health systems transformation. (Al-Rashed etc …2022)
The authors conducted a literature review based on extensive review of published and unpublished articles, using key words such as ‘Saudi Healthcare’, ‘Healthcare transformation’, ‘Saudi vision: 2030’, ‘Public-Private Partnerships’ and ‘Privatization’. They also used secondary data as published in government reports, policy, government strategy documents and pertinent press releases. (Al-Rashed..etc 2022)
The study found that Saudi Arabia’s Vision 2030 has taken a center stage in the development of its healthcare sector through privatization adopting Public Private Partnerships (PPPs). The national transformation programme driven by social and economic factors has implemented strategic steps to develop its private healthcare system that includes: establishing health clusters, National Centre for Privatization & PPP – an official enabler for privatization of all government sectors and recently approved Private Sector Participation (PSP) Law involves several legislative enablers designed to enhance investor confidence in the privatization process. (Al-Rashed…etc 2022)
In terms of additional tools, considering the complexity and multifaceted nature of healthcare transformation, tools like flowcharts could have been used to visualize the process of transformation. Cause-and-effect diagrams could help identify potential factors causing an effect or problem. Pareto charts could be useful in identifying the most significant factors in a data set. And run charts could help in displaying process performance over time. These tools can provide visual aids for better understanding and decision making.
It’s important to note that while these tools can be very useful, their effectiveness would depend on the specific context and objectives of the study. Therefore, it’s crucial to choose the right tool based on the nature of the data and the specific questions being addressed.
Health economic burden of COVID-19 in Saudi Arabia”
The article “Health economic burden of COVID-19 in Saudi Arabia” by Baig., et al., published in Frontiers in Public Health in May 2022, provides real-world data on the health economic burden of COVID-19 on the Saudi health sector¹². The study was conducted based on data collected from patients hospitalized with COVID-19 across ten institutions in eight different regions in Saudi Arabia
The study calculated the direct medical costs of all cases during the study period by using SAS statistical analysis software(Baig…etc 2022) These costs included costs directly related to medical services, such as the health care treatment, hospital stays, laboratory investigations, treatment, outcome, and other related caree(Baig…etc 2022)
A total of 5,286 adult patients admitted with COVID-19 during the study period were included in the study¹². The average age of the patients was 54 years, and the majority were malee(Baig…etc 2022) The total medical costs for general ward and ICU patients were 14,585,640 SAR and 90,776,250 SAR, respectively². The total laboratory investigations ranked as the highest-cost services (22,086,296 SAR), followed by treatment (14,574,233.1 SAR)². Overall, the total cost of all medical services for patients hospitalized with COVID-19 was 193,394,103.1 SARe(Baig…etc 2022)
The study used retrospective cohort study design and SAS statistical analysis software to analyze the data. These tools are appropriate for this type of research as they allow for a comprehensive analysis of large datasets and can handle complex statistical models.
In addition to these tools, I would recommend using data visualization tools such as bar charts or pie charts to present the cost distribution among different services (e.g., laboratory investigations, treatment). These visual aids can make it easier for readers to understand the distribution of costs. Furthermore, a time-series analysis could be beneficial to understand how these costs have evolved over time.
Regarding the Saudi Vision 2030 healthcare goals, this study provides valuable insights into the economic impact of COVID-19 on the healthcare sector. However, it would be interesting to see more research focusing on how these costs impact the broader goals of improving healthcare quality and accessibility under Vision 2030
“Digital health transformation in Saudi Arabia:
The article “Digital health transformation in Saudi Arabia: A cross-sectional analysis using Healthcare Information and Management Systems Society digital health indicators” by Aljohani, N. K., et al., published in August 2022, aims to measure the readiness for digital health transformation at different hospitals in the Eastern Province, Saudi Arabia in relation to Saudi Vision 2030(Aljohani…etc 2022)
The study was conducted with a cross-sectional design using data collected through an online questionnaire from 10 healthcare settings(Aljohani…etc 2022)
. The questionnaire consists of four digital health indicators: person-enabled health, predictive analytics, governance and workforce, and interoperability(Aljohani…etc 2022)
These indicators were developed by the Healthcare Information and Management Systems Society for the purpose of assessing the level of digital maturity in healthcare settings(Aljohani…etc 2022)
The results showed that private healthcare facilities scored higher in digital health transformation indicators compared to public facilities¹². The ‘governance and workforce’ was the most implemented dimension among the healthcare facilities in the study, while predictive analytics was the least frequently implemented(Aljohani…etc 2022)
While the Authors didn’t mention the use of specific tools such as flowcharts, cause-and-effect diagrams, Pareto charts, or run charts, these tools could be useful in visualizing and understanding the data collected. For example, a Pareto chart could help identify which areas of digital health transformation are most lacking and should be prioritized for improvement. Similarly, a run chart could show how these indicators change over time as efforts are made to improve digital health transformation.
In addition to these tools, I would recommend using a heatmap to visualize the scores of different healthcare facilities across the four digital health indicators. This would provide a quick and easy way to compare performance across different facilities and indicators. Furthermore, decision tree models could be used to understand which factors are most influential in determining a facility’s score on each indicator.
These tools would not only help present the results of the study in a more visually appealing and understandable way but also provide valuable insights for policymakers and healthcare administrators as they work towards achieving the Saudi Vision 2030 healthcare goals.
References
Al-Rashed, R. S., Al-Angari, A. A., Alkharfy, M., Al-Khenaizan, A., Al-Ghamdi, M., Alsaif, M., Al-Raddadi, R., Al-Mazrou, Y., Al-Jasser, A., &Al-Omar, A. O. (2022). Healthcare transformation in Saudi Arabia: An overview since the launch of Vision 2030. PMC, 9080562.
https://read.qxmd.com/read/35959196/digital-health…
Baig, M. A., Al-Zahrani, M. A., Al-Omar, A. O., Al-Kharfy, M., Al-Raddadi, R., Al-Mazrou, Y., Al-Jasser, A., Al-Angari, A. A., Alkharfy, M., &Al-Rashed, R. S. (2022). A retrospective descriptive analysis of the Saudi clinical trials registry from 2010 to 2021. Saudi Journal of Health Systems Research.
Aljohani, N. K., Alrawiai, S., Al-Zahrani, B. M., Abumadini, R. A., Aljaffary, A., Hariri, B., Alissa, K., Alakrawi, Z., &Alumran, A. (2022). Digital health transformation in Saudi Arabia: A cross-sectional analysis using Healthcare Information and Management Systems Society digital health indicators. PMC, 9358341.
https://journals.sagepub.com/doi/pdf/10.1177/20552…
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