Hessian Health Files IPO Prospectus: Defining the Value Height of Medical AI and Big Data Through Core Technology Innovation
The development of the medical AI big data industry has been advancing by leaps and bounds in recent years.
From a technological perspective, the data explosion, algorithm upgrades, and enhanced computing power have continuously fueled industry momentum. On the policy front, China’s “New Infrastructure” initiative, first proposed in 2018, along with the “Opinions on Improving the Institutional Mechanisms for Market-Based Allocation of Production Factors” released this April, have both explicitly emphasized strengthening the development of emerging technologies such as big data and artificial intelligence. In terms of capital, the integration of healthcare with AI and big data has become one of the hottest sectors in the capital market.
Prior to 2020, the market afforded companies ample time for growth; now, it is time for them to “bear fruit.”
As one of the earliest enterprises to enter the medical AI and big data sector in China, Haisen Health has consistently attracted significant industry attention by leveraging its “home-field advantage” in data resources.
Haisen Health is a member enterprise of the Jiahemeikang Group. One of its predecessors was the Medical Big Data Division of Beijing Jiahemeikang Information Technology Co., Ltd. (hereinafter referred to as “Jiahemeikang”), established in 2016. In 2019, after three years of incubation, Haisen Health was spun off and officially incorporated, rapidly completing a RMB 200 million Series A financing round by the end of that year.
As is well known, Jiahe Meikang is the largest electronic medical record (EMR) system vendor in China. According to 2020 data from IDC China, Jiahe Meikang’s EMR market share ranked first in China for six consecutive years, with its products deployed in more than 1,300 hospitals across the country. Haisen Health has inherited Jiahe Meikang’s unique data advantages, technological expertise, and mature, stable practical experience, effectively possessing an inherent “medical DNA” and truly being born with a “silver spoon.”
Since its inception, Haisen Health has clearly defined its mission: to forgo exploratory applications and instead focus on developing high-value medical AI big data solutions. By establishing in-depth collaborations with leading domestic general or specialized healthcare institutions that boast top-tier clinical capabilities and advanced health informatics infrastructure, Haisen Health leverages its industry expertise and technical prowess. In synergy with the core strengths of these premier institutional partners, the company has systematically refined a comprehensive ecosystem of proprietary medical AI big data applications spanning clinical care, medical education, and scientific research.
To date, Haisen Health has garnered widespread recognition from numerous top-tier hospital clients. Its partnerships span dozens of provinces across China and include more than 100 Grade A tertiary hospitals. The company holds a market share of over 20% among the top 100 hospitals listed in the Fudan University Hospital Rankings. These clients feature leading medical institutions with absolute advantages in comprehensive or specialized fields, such as Peking Union Medical College Hospital, the Chinese PLA General Hospital, Xijing Hospital, Peking University Third Hospital, and the First Affiliated Hospital of Zhejiang University School of Medicine.
In recent years, a large number of enterprises have flooded into the medical AI and big data sector. While this surge has heated up the industry, it has also trapped it in an awkward predicament of blindly chasing concepts, with few companies settling down to build foundational technologies.In fact, the reliance on raw medical record data and the constraints imposed by unstructured data, which lead to low recall rates and coarse retrieval granularity in related search and retrieval engines, are common challenges faced by healthcare AI and big data vendors in the market.
“Core underlying technologies determine the value ceiling of application products. For medical AI products to achieve substantial breakthroughs, strengthening foundational technologies is the only viable path to overcoming industry bottlenecks.”Haisen Health stated. Guided by this clear-headed understanding, Haisen Health not only refused to be constrained by the impetuous market environment but also plunged headfirst into the field of medical AI and big data, maintaining a low public profile.
After four years of refinement, Haisen Health has stepped into the spotlight with three major research achievements: its independently developed intelligent medical decision-making engine, real-time clinical big data search engine, and AI-based medical big data governance platform.
In light of the unique attributes of healthcare, Haisen Health has innovatively proposed a “dual-engine” intelligent medical decision-making architecture, which combines a deep learning-based intelligent decision model with rule-based systems derived from expert experience. This approach not only leverages information from deep learning models and authoritative knowledge bases but also enables timely iteration of both models and rules based on medical big data, thereby fundamentally ensuring the continuous evolution of AI-driven decision-making capabilities in healthcare.
Unlike the keyword-based underlying logic commonly adopted in the industry, Haisen Health, leveraging its profound understanding of the healthcare sector, has pioneered a structured full electronic medical record (EMR) data model based on natural language processing (NLP) technology and a terminology normalization technique based on knowledge graphs to build a real-time clinical big data search engine. This engine not only enables efficient storage of ultra-granular underlying diagnostic and treatment data but also supports tens of thousands of structured and semi-structured dimensions, maximizing the preservation and restoration of authentic medical record information, thereby providing stronger support for innovative medical applications.
The Haisen Health Medical Big Data Governance Platform is truly a “game-changer” in data governance. Leveraging business data from fully electronic medical records, the platform enables rapid ingestion of any healthcare data, performing automated cleaning, processing, transformation, entity and relationship extraction, terminology normalization, and patient master indexing to deliver standardized, governed data. It offers significant advantages, including minimal manual intervention, high processing efficiency, superior data quality, and enhanced accuracy.
Building on the three core achievements mentioned above, Haisen Health has engaged in deep collaboration with leading domestic medical institutions—whether general or specialized—that boast top-tier capabilities and are at the forefront of healthcare informatization. By leveraging its own industry advantages and technical expertise, and integrating the strengths of its premier medical institution partners,Through meticulous refinement and strategic, low-profile deployment, we have established a comprehensive, closed-loop medical AI ecosystem centered on an intelligent medical data middle platform. This ecosystem spans diverse application scenarios, including clinical decision-making, research support, medical record quality control, and patient engagement services. It has formed a full-spectrum product application matrix comprising Clinical Decision Support Systems (CDSS), big data research analysis platforms, intelligent disease-specific databases, AI-powered follow-up systems, AI-driven semantic quality control systems for medical records, single-disease process quality management platforms, intelligent VTE prevention and treatment systems, intelligent triage systems, and intelligent pre-consultation systems. This achieves a closed-loop application of full-volume data across the entire “pre-diagnosis, during-diagnosis, and post-diagnosis” workflow, thereby realizing the corporate mission of “Understanding Data, Empowering Healthcare.”
Clinical Practice and Scientific Research are the two key entry points chosen by Haisen Health for its mission of “Cognitive Data, Empowering Healthcare.”
China faces an overall scarcity and uneven distribution of medical resources. Clinically, medical AI can effectively enhance the overall level and efficiency of diagnosis and treatment in China. In scientific research, it can further strengthen the core foundational competitiveness of large hospitals and boost the overall strength of healthcare institutions. The combination of these two aspects can maximize the improvement of the overall service level and capacity of China’s healthcare system from the supply side.
In terms of clinical application, Haisen Health has pioneered the “dual-engine” driven Clinical Decision Support System (CDSS) in China, creating an evolved next-generation CDSS that advances from knowledge assistance to decision support, thereby achieving full-process decision support from consultation to treatment.
Taking the application of CDSS at Peking University Third Hospital (hereinafter referred to as “PUTH”) as an example, Haisen Health’s CDSS was launched at PUTH in 2018 and has been operating stably for two years. Built upon nearly ten years of accumulated real-world clinical data comprising over 30 million medical records from the hospital’s electronic medical record system, and integrating BMJ Best Practice as evidence-based medical support, the system establishes a dual-engine decision-making architecture that combines “local best clinical practices” with “evidence-based best practices.” On this basis, artificial intelligence technologies are leveraged to develop high-precision decision-support models covering the entire diagnosis and treatment workflow, thereby fully realizing clinical decision support functionalities. Evaluations indicate that the CDSS deployed in selected departments at PUTH demonstrates robust decision-support capabilities, achieving a maximum diagnostic accuracy rate of 91.7%, reducing the average time to confirmed diagnosis by 0.98 days, and shortening the average length of hospital stay by 2.02 days.
In scientific research applications, addressing prevalent data challenges in clinical studies—such as high duplication and low utilization rates in data collection, fragmented storage with inconsistent structures, lack of unified monitoring for data quality and completeness, and complex data query logic—Haisen Health has developed a big data research analysis platform. This platform is driven by artificial intelligence technologies and supported by real-world diagnostic and treatment data from both within and outside hospitals. It automates the integration of massive volumes of medical data and employs algorithmic models for deep mining and multidimensional analysis. By significantly optimizing research workflows, the platform effectively enhances research efficiency and quality, facilitates the translation of research findings, supports the validation and optimization of research models based on real-world evidence, and promotes the integrated development of clinical practice and scientific research. Consequently, it drives simultaneous improvements in both the diagnostic and treatment capabilities and the research capacities of healthcare institutions.
From a comprehensive ecosystem of medical AI products to closed-loop data applications across entire workflows, healthcare institutions represent just one application scenario. Haisen Health’s vision extends far beyond this. Leveraging medical AI and big data technologies, Haisen Health has been actively exploring and piloting initiatives in areas such as health insurance management, drug research and development, commercial insurance forecasting, and public health decision-making. Haisen Health states that by diligently strengthening its core underlying technologies and defining the high value of medical AI and big data, it aims to deliver tangible, practical benefits to the general public and create greater social value.