How Penglai Data Navigated the DRG Pathway with Over 300 Tier-3 Hospital Clients and Sustained 50%+ Annual Growth for Four Consecutive Years

With the National Healthcare Security Administration and provincial and municipal healthcare security bureaus successively releasing the “New Three-Year Tasks” for DRG/DIP (the “Three-Year Action Plan for Payment Method Reform of DRG/DIP”) in 2021, the high-quality development of healthcare insurance, centered on the comprehensive implementation of DRG/DIP payment reform, has been accelerated. Furthermore, in accordance with the State Council’s deployment requiring all public medical institutions to implement zero markup on medical consumables, healthcare institutions have begun shifting their focus from volume-driven growth to quality- and efficiency-oriented development.

Amid the dual pressures of payment and procurement reforms on the supply side, along with external regulatory demands such as the National Performance Evaluation and high-quality development initiatives, the era of extensive, scale-driven operations in healthcare institutions has come to an end. With health insurance reimbursement entering the DRG/DIP era, hospital management has fully transitioned into a phase of refined, precision-based management.

Currently, refined and digital-intelligent hospital operations have become an urgent priority, creating a pressing market need for productized software that integrates healthcare management methodologies, data, and algorithms.

The direction is already clear, but for healthcare IT vendors, the challenge lies precisely therein.

Although multiple factors, including policy support, enhanced management capabilities, and advancements in informatization, continue to drive the standardization of hospital-side management, there remains substantial room for improvement in lean hospital management. This is due to several challenges: the dynamic nature and complexity of hospital management scenarios, the high barrier to acquiring medical knowledge, the lack of linkage between cost reduction and efficiency gains from refined management and the performance evaluation of hospital administrators, limited application of deep analytical techniques for leveraging medical data in operational management, and the scarce adoption of commercially available, productized operational management software in hospital settings.

Shanghai Palline Data Technologies Co., Ltd. (hereinafter referred to as “Palline Data”), which has maintained an annual growth rate of over 50% for four consecutive years and serves more than 400 hospital clients (80% of which are Grade III hospitals), is undoubtedly a leader in this field.

Wang Zhigang, founder of Palline Data, began his career as a clinician and has held positions such as Executive Director of a public hospital and senior executive in medical groups. Since 2003, he has been engaged in practical work in the fields of hospital performance management, operational management, and hospital informatization. In 2007, he began leading his team in the research, development, application, and promotion of hospital data integration platforms, and participated in the technical architecture and implementation of hospital-side data consolidation during Phase I of the Shanghai Medical Union Project.

Years of research, practice, and reflection have enabled Wang Zhigang to develop a deep understanding of the policy direction for deepening healthcare reform and how data technology can be applied to refined hospital management, while also accumulating relevant technical expertise in hospital operations management. As healthcare reform policies are successively implemented, Wang has gradually realized that the era of expanding scale through external investment and driving internal incentives toward excessive examinations and overtreatment is over. Improving the efficiency of hospitals and physicians, and adjusting business structures, have become imperative paths forward.

What Palline Data aims to do is to enter the market through the niche segment of performance management, applying mature and systematic management methods and tools from other industries and overseas markets to domestic healthcare scenarios.Data-driven, deeply cultivating a new generation of intelligent operations management platforms based on data, models, and AI-powered algorithms.By assisting hospitalsEstablish a comprehensive operational system and reconstruct the operational management infrastructure for various types of medical institutions, enabling a shift from improving personnel efficiency to enhancing asset efficiency, thereby adapting to the changing direction of China’s new healthcare reform.Ultimately, enabling domestic hospitals to rapidly elevate their management standards to a level commensurate with China’s economic development.

Having clarified its strategic direction, Palline Data leveraged policy insights and the current state of hospital management to forecast industry trends. It proactively initiated localized research on RBRVS (Resource-Based Relative Value Scale; a refined performance allocation method that evaluates and labels each diagnostic and therapeutic procedure by assessing factors such as resource consumption, technical difficulty, and risk coefficients), while simultaneously refining its products and continuously validating market demand through practical application.

Since its establishment in 2014, Palline Data has completed product demonstrations and deliveries at provincial-level general hospitals, provincial-level cancer hospitals, provincial-level traditional Chinese medicine hospitals, provincial-level maternal and child health hospitals, and children’s hospitals. The applicability of its products has been validated through practical applications across various types of hospitals. In 2017, the company comprehensively upgraded its offerings and launched a high-barrier “Performance Evaluation System Integrating RBRVS and DRGs.” According to bid award announcements on China Bidding Network, this product has maintained a leading position in the number of successful bids since 2017.

Healthcare represents a relatively complex scenario. While the primary variables in industrial analysis for other sectors include supply and demand dynamics, upstream supply chains, industrial policies, and technological factors, the interplay between supply and demand in healthcare is notably more intricate. The supply side comprises hospitals and physicians, whereas the demand side consists of patients and payers. Technological advancements often influence industrial structure through the supply chain, and regulatory oversight is significantly stricter than in other industries. The multitude of variables within the healthcare landscape is one of the key factors contributing to an exponential increase in management complexity, making it considerably more challenging to forecast the industry’s evolutionary trajectory and development trends. However, for health IT vendors,The key to maintaining product applicability lies precisely in guiding continuous product iteration by industry development trends, while expanding the product portfolio to achieve rapid scalable replication and build competitive moats.。

Palline Data’s first step in entering the hospital management sector was to lay the foundation by establishing the product system framework.

Wang Zhigang told VCBeat that only by identifying common issues among hospitals and gaining a deep understanding of hospital operational dynamics can a stable product framework be established, which serves as the foundation for the company’s future development. With this solid foundation in place, the company can continuously iterate and optimize its products to better suit medical scenarios, enabling rapid large-scale replication in the future and addressing pain points in hospital management.

Palline Data has assembled a team ofHospital Management, Mathematical Statistics, Clinical Medicine, Data Governance, and AI Engineeringa multidisciplinary team with technical expertise, ultimately establishing a hospital-wide operational analytics and management decision-support product ecosystem powered by technology and data.

Core terminal application products include the Lean Performance Management System, Dynamic Cost Accounting System, Departmental Operation Management System, Hospital Operations Management Platform, National Performance Examination Supervision Platform, Hospital-wide Quality Control Platform, Human Resources System, and Medical Insurance Cost Control System, as well as intelligent operation management systems such as quality control and resource allocation platforms. These systems are designed to drive lean, high-quality hospital development, optimize industrial resource allocation, and alleviate financial operational pressures on hospitals.

Among these, the Lean Performance Management System integrates multiple performance evaluation tools, including RBRVS, DRGs, CCHI, and APGs, to construct a new performance framework. The system establishes a bonus/point rule engine capable of recording the labor intensity, technical difficulty, and risk associated with each clinical encounter by healthcare professionals. Furthermore, it accurately manages drivers of resource consumption and precisely controls the costs of clinical processes. Through actuarial analysis, the system uses cost as an economic lever to encourage healthcare staff to proactively control expenses. Additionally, based on its rule engine, the system records the unit revenue generated by each medical service provided by healthcare personnel, facilitating KPI management and enhancing unit economic efficiency.

The reason why a comprehensive product system has been built, achieving coverage in over 30 provinces and municipalities, more than 100 cities, and over 400 hospitals, along with a 75% repurchase rate,Derived from Palline Data’s theoretical innovations, hospital management scenario modeling capabilities, core technology middle-platform development expertise, and underlying database infrastructure.

First, Palline Data possesses a deep understanding of the logical chains and hospital management methodologies spanning from front-end operations, such as outpatient services and surgeries, to back-end functions, including finance, asset management, and human resources. Notably, its performance management methodology has been incorporated into official documents issued by the National Health Commission, enabling it to effectively guide and manage clients’ fragmented, customized requirements.

Secondly, the company employs mathematical models to articulate hospital management methodologies, effectively transforming software usability into a rule engine. By leveraging its independently developed algorithmic rule engine to ensure productization, it constructs statistical and economic AI algorithms based on hospital management principles—such as causal inference—on the foundation of automated data annotation, concept mapping, and transformation compilation. Meanwhile, the company’s proprietary technologies for automated medical big data annotation and data cross-verification achieve an accuracy rate of up to 95%.

Finally, the company possesses a massive database accumulated over seven years, including baseline benchmark data from more than 30 provinces and municipalities and over 400 hospitals; more than 186,000 RBRVS/DRGs items mapped to Chinese codes; over 14,000 self-developed performance evaluation rule engines; and more than 35,000 entries in its self-built master database of diagnostic and treatment items. It has cleaned, annotated, and constructed a multi-dimensional, multi-modal, and multi-scale hospital database within the industry, ensuring data continuity, accuracy, and completeness.

In fact, the core pain points facing hospitals today lie in the lack of professional hospital management teams, immature operational management systems, and relatively fragmented operational management tools. Little attention has been paid to the organized production of medical services and resource allocation. Hospitals need systematic products that integrate medical management philosophies, data, and rules to address these issues and optimize existing resources.

The informatics solutions launched by Palline Data undoubtedly address the critical pain points of hospitals. In the future, Palline Data will further leverage its strengths in data, AI technology, and hospital management to build an industry-grade digital twin platform for medical groups with decision-making capabilities. This platform will enable dynamic perception, prediction, analysis, decision-making, and optimization of industry-level medical resources, thereby achieving optimal in-hospital economic benefits, resource allocation, tiered diagnosis and treatment, and overall industrial efficiency.