Ping An Smart City and Chinese Research Hospital Association Co-Establish Intelligent Healthcare Ecosystem with Seven Academicians

On July 20, at the 2019 China Research-Oriented Hospital Summit, Ping An and the Chinese Association of Research-Oriented Hospitals officially launched their scientific research collaboration. The Special Committee of the Intelligent Medical Research Institute is composed of Academicians Sun Yinghao, Qiao Jie, He Jie, Wang Fusheng, Dong Jiahong, Liu Zhihong, Fan Jia, and more than 30 experts in clinical management and health information intelligence. This move represents a further deepening of cooperation between Ping An and the Association following the establishment of the Intelligent Medical Research Institute last year, aiming to share resources, promote industrial development, and jointly advance the growth of smart healthcare through collaborative efforts among industry, academia, research, and medical practice.

At the sub-forum of the Smart Medical Research Institute themed “Intelligent Translation in Smart Medicine,” Ping An Smart City and the Chinese Association of Research Hospitals jointly established the Council and Expert Committee of the Smart Medical Research Institute, and signed agreements to conduct research projects in three major fields: cardiovascular and cerebrovascular diseases, oncology, and diabetes.

Professor Mu Yiming from the First Medical Center of the Chinese PLA General Hospital, Professor Bai Yongyi from the Second Medical Center of the Chinese PLA General Hospital, and Professor Jiao Shunchang from the First Medical Center of the Chinese PLA General Hospital delivered presentations on diabetes, cardiovascular and cerebrovascular diseases, and oncology, respectively. VCBeat (WeChat ID: vcbeat) has summarized their speeches as follows.

In 2019, Premier Li Keqiang mentioned two chronic diseases in the Government Work Report: one was hypertension, and the other was diabetes.

The number of diabetic patients in China is rising rapidly, and preventive measures have not yielded satisfactory results. Many guidelines and treatment protocols adopted in China are based on existing international standards, while effective treatment models—particularly those tailored to the Chinese population—remain largely undefined, with clinical practice predominantly following foreign guidelines. Furthermore, social resources are fragmented. These factors collectively explain why diabetes control in China has not achieved optimal outcomes.

The primary objective of this platform is to fully leverage existing resources to build a more scientific and effective system. By analyzing big data, particularly dynamic big data, we aim to develop mechanisms for preliminary diagnosis and early warning to curb the progression of diabetes. Most importantly, we seek to establish a network of collaborative hospitals and a comprehensive, efficient big data platform, on which a series of initiatives will be carried out.

The ultimate goal of these efforts is to leverage big data to establish rational treatment models for diabetes and its complications, and to provide early warnings of future disease risk. Relying on the Chinese PLA General Hospital and other key medical institutions, this platform will gradually integrate major databases, ultimately forming a comprehensive and representative national-level database.

Meanwhile, we will develop risk assessment, prediction, clinical decision support, and chronic disease management platforms, along with software systems to facilitate effective management. The project comprises six working groups: 1) data acquisition; 2) big data platform construction and data standardization; 3) disease prediction; 4) clinical decision support and treatment assistance; 5) intelligent patient education and follow-up; and 6) technology transfer and commercialization platform.

The choice to partner with Ping An stems from its robust capabilities. Ping An has integrated over 200 hospitals in Chongqing, where it conducts mature operations in medical imaging data analysis and disease risk prediction.

This collaboration between Ping An and the Chinese Association of Research Hospitals will cover broader and more representative fields, enabling our big data repository to become a truly national-level database.

Cardiovascular and cerebrovascular diseases have long been the greatest threat to human health worldwide. According to estimates by the American Heart Association, global cardiovascular deaths will reach 25 million by 2030. In China, these diseases are also the leading cause of death among residents.

Whether in rural or urban areas, cardiovascular and cerebrovascular diseases account for nearly 50% of all deaths. The total number of patients with these conditions stands at 300 million, including 270 million with hypertension, while the remainder suffer from stroke and heart failure. Over the past decade, the mortality rate has shown a consistent upward trend. Although national efforts have slowed the rate of increase, cardiovascular and cerebrovascular diseases remain the greatest health burden in China.

Now entering the era of big data, data accumulation has brought new breakthroughs in cardiovascular and cerebrovascular diseases. China has a large base of patients, providing an opportunity to mine new and valuable information from data, offering data support for the prevention and control of cardiovascular and cerebrovascular diseases.

Regarding data, the following are the main issues currently:

The first issue is data silos. Different hospitals manage their own data, but interoperability between hospitals remains difficult, which limits our scalability.

The second issue is the bias in data from medical institutions at different levels. For example, primary care institutions mostly handle common diseases, while tertiary hospitals deal with some cancer cases. Therefore, the disease spectrum varies across data collected from different hospitals and for different diseases.

The third issue is the inconsistent quality of data, which stems from both the inherent quality of the raw data and the hospitals’ data processing capabilities. We previously collected hundreds of thousands of outpatient records for heart failure with the intention of developing a clinical decision support system. However, we later found that these outpatient data were largely unusable. Since physicians see a large number of patients each day, their medical documentation tends to be overly concise, often lacking comprehensive descriptions of essential symptoms and physical signs.

Fourth, data-driven research methodologies and frameworks remain underdeveloped. Many physicians still rely on traditional statistical methods when conducting clinical studies. However, in the era of big data, these conventional approaches are no longer adequate for handling massive datasets. Therefore, we need to leverage machine learning and natural language processing to facilitate new breakthroughs and advances in clinical research within the big data context.

To better address these challenges, it is essential to establish a multicenter platform for clinical research and translation. We need to leverage the influence of national-level centers such as the Chinese PLA General Hospital (301 Hospital) and its affiliated hospitals to engage more tertiary and secondary hospitals in this collaborative effort.

Specifically, we will progressively implement data governance and the structuring of electronic medical records; conduct AI-based clinical data analysis; perform precise patient stratification; enable intelligent analytical predictions; and establish health records. Clinicians will be involved in the execution of these initiatives, while Ping An will provide effective artificial intelligence technologies as support.

The first two experts discussed how to prevent chronic diseases such as cardiovascular disease and diabetes from affecting patients’ lives. Our approach, by contrast, is to transform cancer into a chronic disease.

At our hospital (the Chinese People's Liberation Army General Hospital), we admit approximately 20,000 inpatients annually, with cancer patients accounting for about 40% of this total.

Beyond oncology, departments such as pulmonology and gastroenterology—and indeed nearly all surgical specialties—are now heavily involved in cancer care. Many surgical teams rarely perform procedures other than tumor resections. Consequently, the number of cancer patients is rising, generating an ever-growing volume of data. We are increasingly recognizing the need to manage this data effectively.

Since 2000, we have made numerous attempts to establish a database, but most of them have essentially failed. The reasons are varied; some were due to funding constraints, while others stemmed from ineffective communication that failed to achieve the intended objectives.

So, how should we build the database? A critical factor is that IT professionals and physicians need to develop a common language; only on this basis can it be possible to construct an intelligent database that is truly usable.

Only with data can we leverage it to develop new applications and track patients’ health status. Therefore, the quality of medical records is key to the development of our entire platform, and the standardization of medical records is essential to ensuring their quality.

The process should begin with medical history collection. This is a particularly labor-intensive intermediate step for physicians, and it should be performed by machines rather than by doctors. Upon completion of data collection, electronic health records (EHRs) should be automatically generated. Physicians’ primary focus should be on treating patients and engaging in thorough communication with them.

The scalability of the database is also crucial. Healthcare reform in China has long been described as challenging; how can it succeed? I believe that this reform will only succeed by connecting the entire country through a standardized electronic medical record system.

Ping An Smart City has also played a significant role in the collaboration on the aforementioned initiatives. Gao Mengxuan, Co-General Manager and Chief Strategy Officer of Ping An Smart City, told VCBeat that Ping An will allocate resources to support artificial intelligence technologies and platform development. In the later stages, Ping An will also devote time and effort to facilitating the translation of scientific research into products, ensuring that the technology truly benefits people.

Xie Guotong, Chief Medical Scientist of Ping An Group, stated that Ping An began exploring the healthcare ecosystem a decade ago. Aligning closely with the national “Healthy China Action,” Ping An Smart City has implemented a comprehensive “Big Health” strategy, with its business activities covering most of the key areas of “Big Health” mentioned in the document. As part of Ping An Group’s medical and health ecosystem, Ping An Smart City’s smart healthcare services range from intelligent disease prediction and intelligent imaging screening to AskBob (an intelligent clinical decision support system), smart medical consortia, and intelligent quality control, extending further to smart patient services and chronic disease management. This approach creates an end-to-end integrated smart healthcare solution covering the entire process—pre-diagnosis, during diagnosis, and post-diagnosis—thereby achieving multi-dimensional interconnectivity among medical providers, patients, government entities, and industry stakeholders, and comprehensively enhancing the intelligence level of healthcare services and management.

Regarding the collaboration itself, Ping An will engage in deeper cooperation with the Society and medical experts to jointly promote the innovative development of smart healthcare through an integrated “industry-academia-research-clinical practice” model.