Major Announcement! Yidu Tech Wins Two Major Research Projects from the National Healthcare Security Administration, Demonstrating National Recognition of its "AI+Healthcare Security" Capabilities!

On November 5th, the Big Data Center of the National Healthcare Security Administration (NHSA) officially announced the list of organizations selected to undertake its 2025 research projects. In a highly competitive evaluation process, Yidu Tech, in collaboration with the National Center for Health Development and Research (NCHDR) under the National Health Commission (NHC) and Peking University Cancer Hospital, scored top marks and successfully secured two major research projects: Feasibility Study on AI-Assisted Classification of Medical Consumables for Healthcare Security and Study on the Construction Plan and Application Scenarios of "One Disease, One Record."

This announcement coincides with the release of the Implementation Opinions on Promoting and Standardizing the Application and Development of "Artificial Intelligence + Healthcare" (hereinafter referred to as the Implementation Opinions) by the NHC and four other government departments. The focus areas of Yidu Tech's winning projects are highly aligned with the core requirements outlined in the Implementation Opinions, which call for "promoting coordinated development and governance of healthcare, healthcare security, and pharmaceuticals, and advancing the integration of deepening healthcare reform with digital and intelligent empowerment." This not only strongly validates the company's profound capabilities in practical application within this field but also demonstrates its significant potential to further enhance service efficacy and expand application scenarios under policy guidance.

Addressing National Strategic Needs to Promote Intelligent Healthcare Security Data Governance

In June 2025, the Big Data Center of the NHSA publicly solicited proposals for four major research projects. With the NHSA and relevant departments actively exploring application scenarios for healthcare security data, Yidu Tech proactively responded. The company organized its Innovative Medicine & Real-World Evidence (RWE) Department and Data Science teams to jointly apply for these projects in partnership with the National Center for Health Development and Research (NCHDR) and Peking University Cancer Hospital.

The two winning projects focus on "Intelligent Classification of Medical Consumables" and "Standardized Construction of Disease Records," respectively. Both address current hotspots and challenges in healthcare security reform and medical data application, holding significant policy implications and practical value. Yidu Tech's extensive experience and deep expertise in these related fields will provide crucial support for the high-quality advancement of both projects.

Project One: Feasibility Study on AI-Assisted Classification of Medical Consumables for Healthcare Security

This project aims to utilize real-world data and intelligent algorithms to establish a new collaborative model of "AI + Human Expertise" for the classification and evaluation of medical consumables covered by healthcare security. The research will build upon the Report on Value Assessment and Practical Application of High-Value Medical Consumables, which was released by Yidu Tech at the 5th China International Import Expo (CIIE). It will focus on establishing an intelligent decision support system around six key value dimensions. This initiative aims to shift review and decision-making processes towards a model supported by big data evidence, enabling precise identification and quantitative assessment of innovative value.

The outcomes of this project are expected to support various applications, including formulary inclusion, payment standard management, and volume-based procurement. By enabling a full-process data-driven regulatory model, it will contribute to the refined management of healthcare security funds and the healthy development of the industry ecosystem. This not only facilitates the modernization of healthcare security governance capabilities but also actively fosters an industrial environment characterized by "High Quality at a Fair Price" and "Innovation-Driven" principles.

Project Two: Study on the Construction Plan and Application Scenarios of "One Disease, One Record"

This project focuses on unlocking the value of medical data elements and addressing the needs of whole-disease-cycle management. Its core objective is to build a standardized, structured, and intelligent disease record system. The project will initially conduct a pilot study using colorectal cancer as the entry point. Key efforts will include breaking down data silos between multi-source, heterogeneous data systems and establishing unified data standards and processing protocols. Concurrently, the project will develop intelligent analytical models adapted to disease characteristics. A major focus will be validating the practical efficacy of the "One Disease, One Record" system in various scenarios, such as enabling precise policy measures for healthcare cost control, dynamically optimizing diagnosis and treatment protocols, scientifically evaluating medical quality, and providing intelligent early warnings for fraud and abuse.

This research not only explores technical pathways for the standardized governance and scalable application of medical data but also aims to provide a robust data foundation and methodological support. By leveraging large-scale, continuous, and traceable disease data, it will facilitate tracking drug efficacy, evaluating expanded indications, and constructing a high-quality evidence chain covering the entire lifecycle of diseases from prevention and treatment to rehabilitation. This contributes to transforming healthcare security and medical health data from a mere "resource" into a valuable "asset."

Technical Foundation Supports Project Research; Ecosystem Collaboration Promotes Results Translation

The Implementation Opinions explicitly calls for actions to "enrich the supply of medical data, promote data sharing across 'the three healthcare components' and between departments, improve data annotation in the healthcare field, promote the compliant, efficient, secure, and orderly interconnection and interoperability of data elements, and strengthen application."

With over a decade of deep cultivation in the field of medical big data and AI, Yidu Tech has processed and analyzed over 6 billion authorized medical records based on its self-developed YiduCore technology platform. The company's hospital network covers more than 4,000 medical institutions across China, encompassing data related to 1.15 billion patients. Yidu Tech has accumulated insights into tens of thousands of diseases, with its disease knowledge graph covering essentially all known conditions and featuring deep expertise in key disease areas such as solid tumors, hematology, ophthalmology, immunology, cardiology, and endocrinology. This systematic capability provides solid support for the coordinated development of "the three healthcare components" and data interconnection.

Winning these projects further demonstrates the company's exceptional capabilities in data governance for healthcare security big data, modeling methodology, and AI application. Looking ahead, Yidu Tech will continue to deepen its strategic focus in areas such as healthcare security big data, real-world research, and artificial intelligence. The company is committed to translating innovative research outcomes into practical applications, continuously contributing technological strength to building a scientific, efficient, and intelligent new model of healthcare security governance.