Data-driven intelligence: How China is working to make its residents healthier

The development of data-driven intelligence – integration of big data and AI-assisted decision-making – has emerged as a key driver of China's evolving healthcare landscape. By leveraging technologies like the Internet of Things (IoT) and cloud computing, China is systematically reshaping its health services and governance to move toward more proactive care. This shift is particularly significant as the nation enters the 15th Five-Year Plan period (2026-2030), a critical window for achieving the goal of building a Healthy China by 2035.

Bridging healthcare gaps through technology

As China manages a large population with urban-rural divides, digital tools are increasingly used to optimize resource distribution. According to the National Health Commission, county-level remote medical imaging diagnostics exceeded 68 million sessions in 2025, establishing AI as a key support for primary care.

In Shanghai, medical institutions are using AI-powered wearable diagnostic devices to monitor the health of remote patients in real-time. This technology also extends to providing medical support for patients in distant, partner-assisted areas such as Zhongba county in Xigaze, southwest China's Xizang Autonomous Region, helping to implement tiered diagnosis and optimize the distribution of medical resources.

Similarly, in Chengdu's Shiling community, a chronic disease management system uses big data to analyze lifestyle and family history, allowing for early intervention in risks like hypertension and stroke.

Zhao Hong, deputy director of Hepatobiliary Surgery at the Cancer Hospital Chinese Academy of Medical Sciences, told the China Media Group (CMG) that digital healthcare effectively restructures medical resources.

"It creates a more efficient and precise interaction between doctors and patients," Zhao noted, adding that these tools can equalize the quality of diagnosis across different levels of medical institutions.

However, the transition also brings concerns from the public. Jiao Youfang told China Media Group (CMG) about the potential lack of physical interaction, noting, "I worry about accuracy since the system hasn't actually 'seen' me." Other citizens, such as Zheng Zhongxia, expressed concerns regarding the privacy of sensitive health data and potential platform fees.

Market growth and clinical challenges

China's core AI sector reached a valuation of over 1.2 trillion yuan in 2025, and Chinese-developed AI models is now the top spot for worldwide downloads, according to the Ministry of Industry and Information Technology. The medical field has become a primary beneficiary of this surge, evidenced by the release of nearly 300 medical-specific large language models by May 2025.

Despite these gains, medical experts emphasize that technology must be applied with caution. Li Haichao, president of Beijing Chaoyang Hospital, Capital Medical University, told CMG that a clear boundary for AI's role is necessary.

"While accessibility to knowledge has increased, clinical logic remains essential. Without understanding the underlying logic, a doctor might fail to identify potential 'hallucinations' or errors in AI-generated plans," Li said.

Wu Nan of Peking University Cancer Hospital further noted that while AI provides technical support, it cannot yet replace the emotional and psychological communication that is core to patient care.

Furthermore, Liu Lianxin, chief of The First Affiliated Hospital of University of Science and Technology of China, said that current medical AI is largely focused on diagnosis and treatment rather than disease prevention. He noted that AI tools currently rely on existing data environments without a unified national database.

"While AI is widely used in large hospitals, its adoption at the grassroots level remains limited," Liu said. "AI should more effectively assist frontline doctors in diagnosis and treatment to provide the best possible service to patients."

Future applications in biopharmaceuticals

Beyond the hospital setting, data-driven intelligence is revolutionizing drug development. Ding Lieming, chairman of Betta Pharmaceuticals Co., Ltd., noted that while the biopharmaceutical industry is characterized by long cycles and high risks, AI can significantly shorten R&D timelines and reduce costs while improving quality.

Ding recommended deepening the integration of AI within the sector to support enterprises in high-tech stages such as target screening, molecular design and the optimization of synthesis pathways.

"By boosting intelligence levels in clinical trials, industrialization and supply chain management," Ding noted, "we can make new drug R&D more efficient and accelerate the delivery of innovative results to the public."

The advancement of data-driven intelligence in healthcare is a practical application of merging technological innovation with industrial growth. As China navigates the challenges of an aging population and chronic disease management, the integration of AI from laboratory benches to bedside care will serve as the new engine for making quality healthcare more accessible nationwide.