Announcement of the adjustment of the Disease-Based Payment 3.0 plan. What impact does this have on the pharmaceutical industry?

On March 20, the National Healthcare Security Administration announced the adjustments to the version 3.0 of the disease-based payment grouping scheme.

In July 2024, the National Healthcare Security Administration issued the version 2.0 of the disease-based payment grouping scheme, which optimized the version 1.0 released in 2020. In August 2025, the National Healthcare Security Administration formulated the “Interim Measures for the Management of Disease-Based Payment for Medical Security,” clarifying that the disease grouping scheme should be adjusted approximately every two years.

Journalists from the “Daily Economic News” (hereinafter referred to as “Daily Economic News reporters”) noted that this adjustment merged or split certain disease categories, while also considering the needs of medical development and the application of new technologies. To adapt to the widespread application of robot-assisted orthopedic surgery, the newly proposed disease category includes a dedicated code for “17.4100 Open Robot-Assisted Procedures,” establishing corresponding groups for clinically concentrated disease categories such as “M17 Knee Joint Disease,” “S32 Lumbar and Pelvic Fractures,” and “S72.0 Femoral Neck Fractures.”

According to the latest news from the National Healthcare Security Administration, the version 3.0 of the disease-based payment grouping scheme is expected to be released in July this year, with formal implementation planned for January 2027.

What impacts will this have on the industry?

What adjustments are worth paying attention to? What impacts will this adjustment have on the pharmaceutical industry?

Senior healthcare security expert Tian Haoling pointed out in an interview with Daily Economic News reporters that the underlying logic of the adjustment to disease-based payment 3.0 remains unchanged. By refining disease grouping (such as types of diseases, treatment methods, and severity), it maximizes the interests of all major stakeholders in medical insurance payment, allowing the fund’s benefits to be maximized. The two-year cycle adjustment of groups, along with iterative upgrades of grouping versions, not only promotes the rapid implementation of policies but also reflects the precise dynamic adjustment of the value of medical technologies.

She believes that there are several noteworthy directions in this disease group adjustment.

First, the refined grouping of surgeries forces innovation in high-value consumables and surgical techniques.

Separating unilateral and bilateral/combined surgeries into distinct groups (such as bilateral knee replacement, combined liver and pancreas resection, etc.) avoids a one-size-fits-all approach for high-resource-consuming cases and ordinary cases. This means that high-value consumable companies need to develop more suitable products for complex surgical scenarios, such as specialized prosthetics for bilateral joint replacement; hospitals will be more inclined to choose cost-effective consumables, driving the industry from “price competition” to “value competition”; the value of advanced technologies like surgical robots will be recognized more accurately, and related companies are expected to gain more market space.

Second, comprehensive disease management is included in the grouping, bringing new opportunities for innovative drugs and the outpatient market.

Including the entire path of malignant tumor treatments such as radiotherapy, chemotherapy, targeted therapy, and immunotherapy into the grouping considerations allows the product value of innovative drug companies to extend from “hospital use” to “comprehensive disease management,” which is beneficial for the promotion of anti-tumor drugs; services can be provided through designated outpatient pharmacies to insured individuals in need.

Third, the weighting of disease types is segmented based on different populations such as children, chronic diseases, the elderly, rare diseases, and critical illnesses, while severely ill and critical cases are grouped in detail. The R&D enthusiasm of related pharmaceutical companies will be stimulated to better focus on product value.

Exploring the integration of DRG and DIP

Ying Yazhen, head of the DIP technical guidance group, introduced that DIP stands for the regional point system budget and disease-based value payment, which is a method of settling inpatient costs for designated medical institutions by medical insurance. It is a medical insurance payment management system established using the advantages of big data, including a series of technical methods such as regional total budget, disease combinations, payment standards, cost settlement, and supervision assessment. It has significant characteristics and advantages in theoretical systems and grouping strategies and represents a medical insurance payment method that is original to China, with Chinese characteristics and contemporary features.

This adjustment is based on real settlement list data from recent years, maintaining the original basic rules of “primary diagnosis + primary operation (+ related surgical operations),” with about 80% of the diseases grouped directly and automatically according to this basic rule. Meanwhile, the grouping process is optimized, following the overall requirement of “coarse where coarse is needed, fine where fine is needed,” exploring the integration of DRG (Diagnosis-Related Group) and DIP, studying the absorption of exclusion lists from DRG groupings, preliminary groupings, and optimizing grouping rules, including “merging, subdividing, and auxiliary” for diagnoses and operations.

“Coarse where coarse is needed” means merging related surgical operations and diagnoses into groups; “fine where fine is needed” refers to grouping some conditions based on more refined diagnoses as dictated by clinical realities, or using individual characteristics as auxiliary factors for group refinement. Specifically, this includes four aspects: first, merging surgical operations, i.e., combining related surgical disease types that are hospitalized concurrently and meet clinical diagnosis and treatment norms, or merging surgical operations with similar clinical treatment methods and similar resource consumption within the same disease category. Second, merging diagnoses, i.e., combining certain diagnoses with similar surgical operation paths and similar or close resource consumption. Third, subdividing diagnoses, i.e., for a few disease types where significant resource consumption differences arise due to severity, precise splitting enhances the granularity and adaptability of groupings. Fourth, grouping based on auxiliary factors, where certain main diagnoses cannot fully reflect the medical resource consumption based on disease coding reporting rules; grouping is conducted according to other diagnoses or related factors (such as age, complications, severity, etc.).

Tian Haoling pointed out that the implementation of disease-based payment 3.0 will promote medical institutions to transition towards lean operations: through precise clinical path management, disease cost accounting, and case data quality control, reshaping a performance system centered on “quality first, cost controllable.” For pharmaceutical companies, it will mark a complete farewell to the “price war” era—innovative drugs must prove their clinical value with real-world data, gaining market access and payment through dynamic national negotiations, special case discussions, and commercial insurance catalogs; mature drugs will need to focus on advantageous disease groups and optimize product structure in collaboration with clinical practices. Ultimately, patients will enjoy transparent medical costs and balanced medical resources, the medical insurance fund will achieve sustainable development, medical institutions will enhance service efficiency, and pharmaceutical companies will return to the essence of innovation, maximizing the extraction of win-win points among medical insurance, healthcare, pharmaceuticals, and patients.