Saudi Arabia is Moving to Anticipate Health Risks Before They Occur

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The Chairman of the Health Founding Council for the Northern Sector and a member of the International Development Council at Harvard University, Engineer Abdullah bin Ibrahim Al-Rakhis, revealed to "Al Arabiya.net" that Saudi Arabia is heading towards a new phase of health transformation that focuses on anticipating risks before they occur, by employing data, artificial intelligence, and predictive analytics in planning, prevention, and decision-making.

Al-Rakhis stated that the health transformation within Saudi Vision 2030 has shifted from the traditional therapeutic model to a system that places prevention and human health at its core priorities, noting that the upcoming phase requires the integration of data and existing digital capabilities within a connected national system, capable of early detection of health risks and directing resources according to the actual needs of the population.

Al-Rakhis explained that the efficiency of modern health systems is no longer measured solely by the number of hospitals, beds, and equipment, but by their ability to read the health map of the population, monitor the spread of diseases and risk factors, and the disparities between regions and groups, then intervene before they turn into greater health and economic burdens.

He pointed out that the average life expectancy in Saudi Arabia has risen to 79.7 years, while in the Hail region it has reached 83.6 years, alongside the coverage of primary care reaching 97.5%, coinciding with the expansion of health clusters, digital services, and virtual care.

In this context, the role of the "Population Health Observatory" emerges as one of the enabling factors supporting this transformation, by integrating health data and linking it with social, economic, environmental, and genetic variables, and converting it into usable knowledge for planning and decision-making.

Al-Rakhis described the observatory as "not a data repository, nor an electronic dashboard for displaying indicators, but rather an analytical mind and an institutional memory of the health system."

He explained that its role begins with monitoring data and analyzing it, building evidence, and then converting the results into actionable and measurable decisions and interventions, allowing for a shift from delayed reports to real-time monitoring and early warning.

This proposal is based on a recent study involving researchers including Dr. Maryam Al-Essa, Dr. Shakir Al-Omari, and Dr. Abdullah Al-Asiri, which presented a preliminary framework for measuring the maturity of population health observatories through an exploratory comparison that included 21 national and regional experiences.

The model is based on 7 areas, including governance and strategic leadership, data integration and digital infrastructure, statistics and surveillance, artificial intelligence and predictive analytics, research and innovation and translating knowledge into policies, preventive health and screening programs, and population health outcomes and health equity.

The model divides the development of observatories into 5 levels, starting with the foundation, then the experimental phase, followed by operational, reaching systemic integration, and finally the most advanced level based on real-time data, precise prevention, and rapid response.

According to the exploratory assessment of the study, Saudi Arabia scored 52.5 points and was placed in the third operational level, in light of the progress in digital transformation, health records, the use of artificial intelligence, the establishment of the national observatory, and the beginnings of developing biobanks.

In contrast, the assessment indicated that many of these capabilities are still distributed among different initiatives and platforms, making integration between them one of the most prominent requirements for transitioning to more advanced levels.

In the same comparison, Singapore scored 81.5 points, the Netherlands 81, Finland 79, and South Korea 78.5, while the United Kingdom and Sweden each scored 77 points.

Researchers emphasized that these results do not represent a final international classification, but rather an exploratory assessment that requires independent verification, testing, and periodic reviews.

Al-Rakhis believes that the next phase does not necessarily require more separate applications and experimental projects as much as it needs to link the existing capabilities within a unified and sustainable national system.

This includes standardizing data criteria, enhancing interoperability between systems, and linking the outputs of the observatory to planning, funding, workforce distribution, and health resource decisions.

It also requires, according to Al-Rakhis, building an institutional pathway that transfers the results of studies and analyses from scientific papers to applicable health policies and interventions and measuring impact.

The study proposes a phased development roadmap starting in 2026 and 2027 with the unification of governance and standards and enhancing the linkage of health records, followed by the integration of genomic data, biobanks, and social and environmental determinants of health from 2027 to 2029.

In later stages, it suggests expanding data from wearable devices, automated alert systems, and precision prevention models, reaching automated and regulated health responses by 2031-2033, while maintaining human and legal accountability.

The proposed indicators also include achieving 95% coverage for real-time monitoring and the completion of health records, and at least 90% for interoperability, along with auditing the artificial intelligence models used.

Al-Rakhis emphasized that these percentages are not a technical goal in themselves, stressing that the real value lies in the system's ability to detect risks early, improve resource distribution, reduce disease and mortality rates, and narrow health disparities.

The vision presented by the model concludes that the development of the population health observatory is not measured solely by the volume of data or the number of algorithms, but by its ability to transform data into knowledge, knowledge into decisions, and decisions into measurable health interventions.

In this role, the observatory can be one of the enablers of the next phase of health transformation in Saudi Arabia, by gradually shifting from responding to diseases to predicting risks and preventing them before they occur.