Adoption of AI in Kazakhstan’s healthcare system

She had planned to become a physician and earned a degree in biology, but taught herself information technology to help digitize an entire national healthcare system. In this article El.kz reviews the story of Akzhan Zhanseitova - story of how the challenges of the COVID-19 pandemic gave rise to technologies that quietly improve the lives of citizens every day.

Today, approximately 300 physician experts across Kazakhstan use AI on a daily basis to support the quality assessment of healthcare services. Each month, AI processes large volumes of data and generates around 10,000 draft expert responses, reducing administrative workload and minimizing the risk of human error.

Behind this quiet transformation at the Social Health Insurance Fund (SHIF) stands Akzhan Zhanseitova, a graduate of the School of Sciences and Humanities at Nazarbayev University. She entered the healthcare sector from an academic background and has since become one of the key drivers of its digital transformation.

Code written in response to COVID-19

For Akzhan, as for the rest of the world, the turning point came in 2020. During the COVID-19 pandemic, the Social Health Insurance Fund became the analytical backbone of the Ministry of Health. The Fund was responsible for calculating healthcare financing requirements in real time, forecasting the development of the epidemic, and planning the required volumes of medical services.

The situation was critical. Standards were changing almost daily, while data became outdated faster than reports could be compiled. At the time, Akzhan was responsible for analyzing healthcare service utilization and quickly realized that manually processing such volumes of information was unsustainable. Rather than waiting for dedicated IT specialists, the trained biologist independently mastered data analytics and business intelligence platforms, including KNIME, Apache Superset, Microsoft Power BI, and Qlik Sense.

“There were moments when the complexity of approval procedures became discouraging,” she recalls. “But the pandemic fundamentally changed the way I viewed statistical reports. I realized that behind every figure, every table, and every analytical model are real people. Since then, that understanding has become my primary guiding principle.”

Technology ceased to be merely a set of tools. Instead, it became a language through which the healthcare system could be understood, improved, and made more effective.

How AI supports clinical decision-making

Today, Akzhan serves as Head of the Internal Process Automation Department at the Social Health Insurance Fund. Her colleagues jokingly refer to her as a “crisis manager” because she is often brought into projects that have stalled, identifies operational bottlenecks, and restores momentum. Under her leadership, two landmark digital initiatives have been successfully implemented.

The first major achievement was the establishment of the Situation and Analytics Center. As the country’s single purchaser of publicly funded healthcare services, the Fund possessed an enormous volume of data but lacked a unified analytical framework. Information was dispersed across multiple reports, and producing comprehensive analytics required months of work.

Together with her colleague Asset Slambekov, Akzhan designed the architecture and analytical framework of the new center from the ground up. The results exceeded expectations: analytical reporting processes that previously required months were reduced to just a matter of hours. As a result, the Fund gained the ability to make evidence-based management decisions using real-time data rather than relying on outdated reports.

The second flagship initiative introduced AI-powered monitoring of medical quality reviews. The quality of healthcare should not depend on the fatigue or subjective judgment of an individual reviewer. To address this challenge, the team deployed AI algorithms that now process tens of thousands of electronic medical records.

“Artificial intelligence does not replace healthcare professionals,” Akzhan emphasizes. “It enables them to analyze information more efficiently and identify potential issues that require attention. AI takes over routine tasks, allowing physician experts to focus on the most complex clinical cases.”

“The average citizen of Kazakhstan will most likely never see the code behind these systems,” she concludes. “What they should experience, however, is the outcome: a more equitable, consistent, and higher-quality healthcare system, regardless of the region in which they live.”