Editor's Note: At the International Lung Cancer Conference (CLC 2024) held from August 9-11, Dr. Yuehong Wang from The First Affiliated Hospital, Zhejiang University School of Medicine delivered a keynote presentation titled "Exploring a New Model for Comprehensive Lung Cancer Management in the AI Era." This article provides a brief overview of her report.Current State of Comprehensive Lung Cancer Management
The advent of targeted therapies and immunotherapies has significantly extended the survival of lung cancer patients, making the chronic management of non-small cell lung cancer (NSCLC) increasingly a reality. For the chronic management of lung cancer, healthcare providers should adopt a comprehensive management approach, ensuring patient care both within and outside the hospital. This involves timely monitoring and management of drug-related adverse events, real-time personalized adjustments to treatment plans, and enhanced patient education, psychological interaction, and nutritional interventions to maximize patient benefits.
However, there are several challenges in chronic disease management in China, including uneven distribution of medical resources, imperfect management models, inadequate integrated medical services, insufficient health education, and variability in the medical skills of healthcare providers, leading to inconsistent treatment outcomes. Due to these factors, comprehensive lung cancer management in China faces the following pain points:
- Data Collection and Management: Fragmented data, insufficient data standardization, difficulties in real-time data acquisition, and lack of out-of-hospital data.
- Adverse Event Management: Inadequate adverse event reporting, lack of systematic support, and significant individual variability.
- Follow-up Management: Heavy follow-up burden on doctors, low follow-up rates, and insufficient telemedicine technology.
- Collaboration and Communication: Insufficient patient education, poor information transmission, and difficulties in multidisciplinary collaboration.
Application and Prospects of AI in Chronic Disease Management
Technological advancements are driving the development of medicine, ushering in the era of artificial intelligence (AI). AI refers to systems or machines capable of performing tasks that require human intelligence, offering intelligent solutions across various application scenarios. AI has already found multiple applications in healthcare, such as AI-driven diagnostics, surgical robots, telemedicine, VR surgical simulation, smart health monitoring, AI-generated personalized treatment plans, and medical GPT.
AI holds great potential in chronic disease management, including achieving precise predictions and early warnings, real-time monitoring and treatment adjustments, data-driven medical decision-making, and the establishment of health management platforms. Tools change the world, from predicting disease progression to achieving precise prevention, optimizing resource allocation, and improving public health efficiency. AI technology will continue to drive chronic disease management to deeper levels and broader scopes, opening a patient-centered, AI-driven future.
Data collection and integration are the foundation of AI’s application in chronic disease management. China’s healthcare system is transitioning from informatization to digitalization. The 14th Five-Year Plan emphasizes accelerating the development of digital healthcare centered on “universal well-being,” creating a patient-centered health system, and simultaneously building a smart ecological healthcare system. Innovative technology is key to achieving “digital healthcare.” Digital healthcare (Digital Health) applies modern computer and information technology to the entire medical process, encompassing informatization, mobile applications, AI, and digital therapeutics. According to the Stanford Digital Health Center, digital healthcare includes five types of digital healthcare technologies:
- AI, machine learning (ML), and various AI algorithms including deep learning, image processing, and advanced analytics.
- Medical informatization, infrastructure, and data management systems including electronic health records (EHR).
- Mobile applications and web applications including SaaS platforms, cloud-based software tools, and social applications.
- Emerging clinical care models including telemedicine, patient engagement, and doctor-patient interaction.
- Wearable devices, sensors, and other IoT hardware devices.
Digital healthcare optimizes the entire diagnosis and treatment process through the generation, collection, analysis, and application of health data, setting the direction and management goals for public healthcare development. By integrating digital healthcare into the entire disease diagnosis and treatment process, it holds the potential to resolve the “impossible triangle” of healthcare.
Exploring a New Model for Comprehensive Lung Cancer Management
In 2016, Professor Chunxue Bai’s team innovatively proposed the concept of “Internet of Things (IoT) Medicine,” establishing a smartphone-based IoT chronic disease management platform to achieve homogeneous and high-quality medical care. In 2022, Professor Chunxue Bai’s team further proposed the concept of “Metaverse Medicine,” aiming to use metaverse technology to revolutionize disease prevention and treatment! The expanded concept of Metaverse Medicine, building on IoT Medicine, could bring new diagnostic and management models to medicine.
Building on these theoretical foundations, we aim to explore a new digitalized model for comprehensive lung cancer management. The following is the construction of the technical system for this model, which focuses on improving the efficiency of doctors’ work, assisting in the accumulation of real-world data, and enhancing the consistency of lung cancer diagnosis and treatment among doctors. It emphasizes the promotion of new chronic disease treatment concepts, achieving co-management of multiple diseases and integrated lung cancer care. The model also stresses the involvement of patients and their families, enhancing patients’ self-management capabilities, improving disease management, reducing the societal burden of disease, and positively impacting China’s healthcare security system, aligning with the requirements of “new productive forces.”
Looking to the future, we need to refine and further expand digital chronic disease management in the following areas: developing AI-driven big data analysis to deeply explore the scientific value of data; accumulating large amounts of real-world data to further improve guidelines; analyzing patient-reported adverse event data to aid in drug development and structural optimization; and further exploring the application of Metaverse Medicine in disease management.
Dr. Yuehong Wang
- MD, Chief Physician
- Deputy Director of Respiratory and Critical Care Medicine, First Affiliated Hospital, Zhejiang University School of Medicine
- Visiting Scholar at MD Anderson Cancer Center, USA
- Member of the Lung Cancer Group, Respiratory Medicine Branch, Chinese Medical Association
- Member of the Lung Cancer Working Group, Respiratory Physician Branch, Chinese Medical Doctor Association
- Vice President of the IoT Medical Branch, Chinese Association of Non-Public Medical Institutions
- Deputy Chair of the Lung Cancer Immunotherapy Committee, China Lung Cancer Prevention Alliance
