Lilian Cognitive Files IPO Prospectus: Leveraging AI-Powered CDSS to Enable Standardized Management of Infectious Diseases
“Diseases with high treatment costs and returns, such as tumors and chronic diseases, have received significant attention under China’s current healthcare landscape. In contrast, some foundational hospital departments that play a critical role in ensuring medical quality and patient safety have long been marginalized, overlooked, and forgotten. This is the case for departments such as Hospital Infection Control, Infectious Diseases, and Fever Clinics. The outbreak of the COVID-19 pandemic has fully exposed this major weakness.”
In 2015, Niu Yaojun, the founder of Lilian Cognition, was still an executive at IBM. During collaborations with top-tier tertiary hospitals in China, he observed this phenomenon. He found that hospital-acquired infections were frequent in domestic hospitals, and cross-infections occurring during and after surgery led to poor postoperative healing outcomes for patients, even posing life-threatening risks.
Drawn by the substantial business opportunities and growth potential in the healthcare industry, coupled with his deep familiarity with the domestic healthcare market and concerns over the quality of care and patient safety environment in China, he turned down IBM’s high salary and attractive benefits. Instead, he gathered a group of like-minded partners to embark on entrepreneurship—a path that offers a greater sense of accomplishment.
In late 2016, Shanghai Lilian Information Technology Co., Ltd. (hereinafter referred to as "Lilian Cognitive") was established in Shanghai, and set up branches in Beijing and Chengdu in 2018, respectively.
2003 marked a significant milestone in the development of infectious diseases as a discipline in China. In the aftermath of the SARS outbreak, initiatives to establish departments of infectious diseases and infection prevention and control (IPC) units were launched. Regrettably, within just three years, these efforts gradually lost momentum. Over the following decade and more, despite repeated outbreaks of serious healthcare-associated infections, departments of infectious diseases and IPC services were largely marginalized. It was not until the onset of the COVID-19 pandemic that infectious diseases and hospital infection control once again took center stage.
“This outbreak has had a far greater impact on infectious diseases, infection prevention and control (IPC), and public health in China than the SARS epidemic.” Niu Yaojun believes that the pandemic has propelled the management of infectious diseases and hospital IPC into an era of “comprehensive IPC,” shifting from in-hospital infection management toward broader, whole-process, and standardized control of infectious diseases.
Infectious diseases refer to conditions in which microorganisms (bacteria, viruses, fungi) and parasites infect the human body, causing varying degrees of damage to tissue cells and resulting in a series of clinical symptoms and signs. Due to their inherent infectious and transmissible nature, infectious diseases often pose significant challenges and pressure to clinicians and healthcare institutions; improper or delayed diagnosis and treatment can lead to poor prognosis.
According to data released by the World Health Organization in 2018, three of the top ten causes of death worldwide in 2016 were infectious diseases (lower respiratory infections, diarrheal diseases, and tuberculosis). Relevant studies indicate that 30% of cancers are triggered by infections, and more than 50% of cancer patients die from severe infections caused by superbugs. The widespread abuse and misuse of antibiotics for infectious diseases will lead to a scenario where no effective drugs are available.
China’s foundation in the diagnosis and treatment of infectious diseases is relatively weak. Many hospitals lack dedicated departments for infectious diseases, and physicians across various specialties possess outdated knowledge in this field, resulting in a significant gap compared to international standards. Due to the scarcity of infection control professionals and relevant expertise in healthcare institutions, as well as insufficient mastery of knowledge and techniques for the rational use of antimicrobial agents, issues of “overtreatment and underdiagnosis” frequently arise in anti-infective clinical practice.
The diagnosis and treatment of infectious diseases are closely intertwined with antimicrobial resistance, exhibiting a dynamic “wax-and-wane” relationship. This interplay makes precise, timely surveillance and early warning, as well as standardized diagnosis and treatment, significant challenges. To address these issues, there is an urgent need to leverage artificial intelligence technologies to provide decision support for early warning of infectious diseases, assistance in diagnosis and treatment, and precision use of antimicrobials. This will help medical institutions at all levels, particularly primary care facilities, enhance their capacity to diagnose and treat complex and refractory infections, improve the application and management of antimicrobial agents, strengthen specialized prevention and control capabilities against drug-resistant bacteria and healthcare-associated infections, and increase comprehensive response capabilities for sudden or major infectious disease events.
Clinical Decision Support (CDS) is the most effective means to standardize and enhance the quality of diagnosis and treatment. Traditional clinical guidelines suffer from low adherence in practice, making it difficult to effectively standardize and improve care quality. Relevant studies indicate that it takes an average of more than 10 years for clinical guidelines to be homogenously applied in clinical practice. Therefore, providing intelligent decision support to healthcare professionals through Intelligent Clinical Decision Support Systems (CDSS) is the optimal approach to improving healthcare quality, ensuring patient safety, and achieving standardized enhancements in diagnostic and therapeutic capabilities. In 2018, 74% of healthcare institutions in the United States adopted CDSS to improve clinical quality, saving each hospital an average of $4 million annually.
The challenges in developing Clinical Decision Support Systems (CDSS) for infectious diseases lie in the broad spectrum of such diseases, the high dimensionality of patient data involved, the numerous departments concerned, and the complexity of usage scenarios. Leveraging artificial intelligence technology, Lilian Cognitive deeply mines the value of clinical data and provides intelligent solutions with infectious disease CDS as the entry point.
Lilian Cognitive is a provider of smart healthcare solutions that leverage medical big data and artificial intelligence technologies. Its R&D efforts are dedicated to designing solutions aimed at improving the quality of clinical decision-making through standardization, while ensuring the safety of both patients and healthcare providers. By employing technologies such as data governance, natural language processing, machine learning, and knowledge engineering to process clinical big data and medical literature, Lilian Cognitive has built an evidence-based medicine knowledge base. Through its AI inference and computing engine, it assists in the diagnosis and treatment of clinical diseases, effectively identifies clinical risks during the diagnostic and therapeutic processes, and enables real-time intervention along with post-event statistical analysis. This provides clinicians and medical staff with effective tools to enhance quality, prevent errors, and ensure safety.
The company's core products include:
iMedRisk: Intelligent Early Warning and Monitoring System for Hospital Infections and Infectious Disease Public Health; Intelligent Assistant for Intensive Care Unit (ICU);
iHDR: Clinical Data Center, Clinical Data Resource Processing Platform;
mDataCube: An integrated tool for data and analytics that performs “3D reconstruction” of medical data, providing rapid data exploration and mining services to stakeholders;
Niu Yaojun, Founder and CEO of Lilian Cognitive, has been deeply engaged in the IT industry for over two decades. He has held senior positions including General Manager of IBM GCG IM & Analytics Services and General Manager of IBM GCG Smarter Healthcare Lab, accumulating extensive experience in healthcare informatization construction. He led IBM teams to pioneer the domestic market for medical big data and cognitive computing, achieving annual performance growth exceeding 40% for consecutive years and repeatedly receiving IBM’s OTAA (Outstanding Technical Achievement Award). The company’s core team comprises chief healthcare industry consultants, top-tier big data analytics experts, and technical specialists who previously served at Fortune 500 technology companies such as IBM and HP.
Informatization of hospital infection management is a crucial component of current hospital information system development and an essential requirement for hospital accreditation and upgrading at all levels. The Intelligent Early Warning and Monitoring System for Infection Control, developed by Lilian Cognitive, incorporates AI-based clinical decision support technology. It pioneeringly integrates clinical diagnostic expertise with medical big data in China, enabling real-time, accurate, and comprehensive early warning, monitoring, intra-event intervention, and post-event statistical analysis for healthcare-associated infections and infectious diseases. The product’s sensitivity and specificity for disease risk identification and early warning both exceed 90%, reducing the workload of relevant departments and clinical staff by two-thirds. It has already been implemented on a paid basis in hundreds of hospitals across China.
Lilian Cognitive has also extended its AI-based clinical decision support technology to intensive care units (ICUs), developing the ICU Assistant product. This system integrates real-time clinical data from ICU patients, providing dynamic risk monitoring, early warnings, and related decision support. Notably, it features specialized capabilities for identifying and issuing early warnings of sepsis, a condition prevalent in ICU settings.
Traditional infection control and critical care informatics products typically digitize paper-based workflows in the clinical process, focusing primarily on data entry and report generation, thereby offering limited assistance in standardizing and improving the quality of clinical diagnosis and treatment.
Lilian Cognitive Care leverages its strengths in AI-powered Clinical Decision Support System (CDSS) technology, data integration and governance, as well as extensive data accumulation in specific disease domains to seamlessly integrate medical knowledge and intelligent decision-support capabilities into clinical workflows. This has led to qualitative improvements in alert accuracy, clinical adherence, and data precision. By supporting disease diagnosis, real-time monitoring and early warning of clinical risks, intervention and management, and automated execution of process quality PDCA (Plan-Do-Check-Act) cycles, it provides a robust tool for clinical and healthcare administration to effectively enhance the quality of disease diagnosis and treatment while strengthening patient safety management.
Lilian Cognitive plans to expand the application scenarios of its CDSS product series, extending from infectious diseases and public health to other specialized departments such as ICU, obstetrics and pediatrics, and respiratory medicine. Meanwhile, it will further explore the added value of clinical data and seek innovative collaboration models with IVD companies and pharmaceutical enterprises.
To date, Lilian Cognitive’s market presence has expanded to cover hundreds of hospitals across more than 20 provinces and municipalities nationwide. This year, Lilian Cognitive plans to aggressively expand its domestic market, facilitating the deployment of its clinical decision support and medical big data product suites in a broader range of hospitals. Furthermore, Lilian Information will actively participate in regional public health infrastructure development, including the construction and maintenance of provincial-level big data platforms for hospital infection control and public health surveillance based on regional hospital networks.
Since completing its Series A financing in 2018, Shanghai Lilian Information Technology Co., Ltd. is planning to launch a new round of fundraising.