Xu Ruiping, President of Anyang Cancer Hospital: Big Data Is the Key to the "Comeback" of Prefectural-Level Hospitals

As the tiered diagnosis and treatment system advances, high-quality medical resources from provincial and even national-level hospitals are gradually being decentralized to the grassroots level, steadily enhancing the healthcare service capacity at the county level.

In the new healthcare landscape, prefecture-level hospitals find themselves in an awkward position. As medical resources gradually shift toward primary care institutions and more provincial-level hospitals leverage internet technologies to benefit a broader population, these mid-tier hospitals must confront the critical challenge of carving out “a niche” amid intense competition and enhancing their core competitiveness. At the recently held “Second Conference on Medical Big Data Application and Development & The Third China Hospital Development Conference Informatics Forum,” Xu Ruiping, President of Anyang Cancer Hospital, stated that big data is the key to the “counterattack” and revitalization of prefecture-level hospitals.

Anyang Cancer Hospital is a specialized oncology hospital at the prefecture-level city in China and among the earliest batch of Grade A tertiary hospitals. It ranks first in China in the prevention and treatment of esophageal cancer. However, after a long period of rapid development, it has faced challenges in recent years.

New Healthcare Reform: Advancing Tiered Diagnosis and Treatment Policies, Strengthening Primary Care, and Requiring 90% of Patients to Remain Within County-Level Jurisdictions; As Provincial Hospitals Leverage Internet Technology to Decentralize Medical Resources, How Can Prefecture-Level Hospitals, the “Sandwich Layer,” Continue to Achieve Healthy Development?

Xu Ruiping’s answer is to embrace big data and seek new development.

In April this year, the General Office of the State Council issued the “Guiding Opinions on Promoting the Development of ‘Internet Plus Medical Health,’” clearly demonstrating strong support for the development of “Internet Plus Medical Health,” encouraging medical and health institutions to collaborate with internet companies, and strengthening the integration of regional health information resources. In November, the National Health Commission released the “Assessment Indicators for the Action Plan to Further Improve Medical Services (2018–2020),” which explicitly included the establishment of smart hospitals as a key component. The plan proposed leveraging big data and information technology to carry out medical quality control, standardize diagnosis and treatment practices, evaluate rational drug use, optimize service processes, and allocate medical resources, thereby providing clear direction for hospital development.

Xu Ruiping stated that, as a hospital that has been an early explorer in the application and management of medical big data, Anyang Cancer Hospital has been actively exploring and leveraging big data in recent years to enhance its management and research capabilities, improve medical services, respond to national policy directives, strengthen institutional capacity, and ultimately deliver higher-quality medical care to patients.

Standardized and structured medical records enable more flexible and precise documentation of large volumes of clinical observational data, thereby transforming clinical data resources into valuable assets for scientific research. Therefore, to fully leverage hospital medical records, generate research outputs, present findings at national and even international academic conferences, and establish a benchmark position in esophageal cancer treatment, Anyang Cancer Hospital has partnered with LinkDoc Technology, a leading Chinese medical big data and artificial intelligence company, to launch a “Three-Step” strategy.

1. Standardize big data and establish a standardized database

Currently, Anyang Cancer Hospital records 2,000 to 2,500 esophageal cancer cases annually, making it the hospital with the highest volume of esophageal cancer patients in China. This indicates that the large-scale medical record data for this single disease entity holds significant scientific research value. However, despite serving as a “vanguard” in the application of medical big data, the hospital faces challenges related to the cumbersome organization and difficult entry of vast amounts of data. Relying solely on manual data entry by physicians is not only inefficient but also fails to ensure accuracy. Meanwhile, due to heavy clinical workloads and limited time dedicated to research, studies often rely on sampled, localized, and biased data, resulting in low research output. Furthermore, post-treatment patient follow-up success rates remain unsatisfactory.

To this end, the hospital has leveraged big data as a strategic entry point to enhance its scientific research capabilities. By standardizing medical record collection and establishing a hospital-wide standardized clinical database, it has effectively addressed challenges in medical record entry through methods such as automated machine recognition, photographic capture of records, and manual verification. Currently, Anyang Cancer Hospital has fully digitized 200,000 medical records spanning 18 years. Building on this foundation, the hospital spearheaded the establishment of the Anyang Tumor Hospital & China Anyang Esophageal Cancer Taihang Big Data Center, and has correspondingly set up a Clinical Data Center, Biobank Center, Molecular Diagnostic Center, Clinical Treatment Center, and Follow-up Tracking Center.

Second, focus on scientific research and contribute to its advancement.

It is well known that high-quality publications serve as a key metric for international peer assessment of the research caliber of medical institutions, reflecting their scientific research capabilities and academic influence.

To enhance the research influence of Anyang Cancer Hospital and translate its research capabilities and achievements into tangible outcomes, thereby further achieving the goals of leveraging big data to support research, using research to drive disciplinary development, and improving patient survival through such advancements, the hospital has established precise disease models based on a standardized database. Physicians can efficiently retrieve required data—including each patient’s basic information, disease treatment course, surgical timing and procedures, lymph node dissection details, and specific dissection sites—and then process this information using the scientific research analysis functions of the data platform.

This significantly streamlines the research process, saving physicians time and energy so they can better devote themselves to clinical work and address tangible patient care issues.

3. Intelligent Follow-up: Strengthening Patient Engagement

Follow-up is a critical component and data source in clinical research. The follow-up system based on a big data platform integrates actual medical record conditions to intelligently push standardized, automated, and fully guided follow-up tasks, enabling patients to receive follow-up care from professional teams during the optimal and most reasonable window period. This approach effectively improves follow-up rates and success rates. Currently, Anyang Cancer Hospital achieves a follow-up rate of approximately 90%, significantly higher than the effective follow-up rates at the vast majority of hospitals.

The follow-up function of the Big Data Center can also intelligently push follow-up tasks, record detailed audio throughout the entire follow-up process, and automatically link the recordings with patients, ensuring that every data point in the follow-up is “traceable and verifiable.” Additionally, through APP interactions, it strengthens communication with patients, effectively guarantees the accuracy of follow-up data, and serves as the final safeguard for clinical research.

President Xu firmly believes: “In the current information age, medical institutions can only remain invincible amid the tide of reform by keeping pace with the times to recognize and reflect on the updated perspectives and concepts brought about by the information era, understanding the development trends of big data, and establishing a research mindset grounded in big data.”