Frost & Sullivan releases the 'White Paper on the Healthcare Intelligence Industry'

Mr. Mao Hua, Partner and Managing Director of Frost & Sullivan Greater China, was invited to attend the seminar and deliver a speech.Mr. Mao Hua said, "The 'White Paper on the Healthcare Intelligence Industry' defines the scope of the healthcare intelligence industry and further divides the market based on the main participants in the healthcare sector. It provides a comprehensive and in-depth analysis from dimensions such as pain points at each link of the industrial chain and enablement application scenarios. Frost & Sullivan believes that in the future, healthcare intelligence will develop into a healthcare system centered around improving decision-making efficiency, meeting precision needs, and providing high-value traceable services."

The healthcare intelligence industry is centered around five core capabilities: big data, cloud computing, technical capabilities (AI), medical knowledge and scenario experience, and high-frequency iteration of scenarios + algorithms. It provides intelligent solutions tailored to real-world application scenarios for regulatory bodies, providers, and payers in the healthcare industry, achieving industrial upgrading across all links of the supply chain in areas such as digital economy and intelligent decision-making.In the future, medical intelligence will develop into a healthcare system centered around improving decision-making efficiency, meeting precision needs, and providing highly valuable traceable services.

China's healthcare industry is gradually evolving from 1.0 medical informatization to 3.0 medical intelligence.

Medical informatization includes the construction of hospital IT systems such as Hospital Management Information System (HIS) and Clinical Management Information System (CIS), as well as the regional medical and health service informatization system (GMIS). It is an information system infrastructure that enables digitalization and networking of medical services. The online digitalization stage of medical services aims to digitize business operations and processes for all parties involved in the healthcare industry, thereby providing online services to end consumers and improving process efficiency. However, there are still issues with data silos at this stage, and a large amount of accumulated medical data is not standardized and cannot be calculated and analyzed by machines.

Entering the 3.0 phase, medical intelligence relies on the application of big data, artificial intelligence, and other technologies. It takes multi-dimensional, high-quality, machine-analyzable big data as its entry point to produce indicators and evidence that can objectively measure medical behavior and outcomes. This enhances the decision-making efficiency and accuracy of healthcare providers, achieving cost reduction and efficiency improvement across all aspects of the healthcare industry.

Achieving the medical intelligence of industries requires five core elements. Only under the combined action of these core elements can intelligent decisions that can be applied to real-world scenarios be produced.

Firstly, a massive, multi-source, traceable, and machine-computable entry point for medical big data is the foundation for building medical intelligence. Cloud computing provides basic capabilities for the storage, rapid processing, analysis, and mining of big data, ensuring privacy and security. Technical capabilities (AI) are the engine that enables data processing, analysis, mining, and industrial application implementation. Medical knowledge and scenario experience serve as a bridge between data models and practical applications, ensuring the applicability, accuracy, and interpretability of models in specific scenarios. High-frequency iterations of scenarios + algorithms can enhance the depth and reliability of algorithm models and the knowledge and insights generated through closed-loop feedback on data, thereby improving the intelligence of solutions.

Due to the fragmented data within the healthcare industry, participants lack effective exploration and application of its value. Traditional methods relying on manual labor are difficult to break through the shackles of efficiency. Medical intelligence, based on big data and artificial intelligence technologies, combines deeply with medical logic and experience to provide cost reduction and efficiency improvement solutions for industry regulators, suppliers, and payers across multiple scenarios.

The essence of medical intelligence, which differs from medical informatization, is the ability to transform multi-source heterogeneous raw data into high-quality, standardized, and structured data through emerging technologies such as artificial intelligence. This supports continuous generation of insights and evidence in the real world, enables decision-making and behavior to be quantifiable, measurable, and traceable, thereby improving efficiency and accuracy.

Based on medical intelligence, it can provide applications and solutions covering multiple scenarios for the five major stakeholders in the industry. For example, public health monitoring and population health management solutions for regulatory authorities, real-world research, safety monitoring, and research solutions for pharmaceutical and medical device companies.

In the future, medical intelligence will empower the healthcare industry, building an efficient, personalized, precise, accessible, value-oriented healthcare system that achieves industrial upgrading.

Efficient:The maturity of big data, cloud computing, and artificial intelligence technologies enables industry participants to continuously generate real-world evidence through large-scale analysis, computation, and prediction. This has led to the establishment of objective evaluation and result measurement systems, thereby enhancing regulatory, research, and diagnostic and treatment efficiency.

Personalized, Precise:Based on fine data granularity and continuously expanding application scenarios, we continue to refine patient and disease stratification for precision medicine and behavioral decision-making.

AccessibilityEfficiency improvements and precise decision-making have avoided waste, reducing costs on the supply side such as drugs and hospital operations. At the same time, dynamic risk pricing based on disease and patient models has enhanced payment capabilities.

Value-based healthcare system:By providing value-oriented solutions for healthcare industry participants and building a system that can objectively measure effectiveness and quality evaluation, we ensure that pay-per-effect is based on solid evidence.

Medical intelligence is based on big data, cloud computing, and artificial intelligence technology capabilities. It deeply integrates medical logic and experience into the construction, training, and optimization of models and algorithms, forming a market for precise, objectively measurable applications and solutions that reduce costs and improve efficiency for participants in the healthcare industry. It mainly covers the intelligentization of basic medical insurance for government agencies, public health and population management, intelligent markets for medical institutions, R&D and marketing intelligence for pharmaceutical and medical device companies, real-world studies (RWS), and clinical CXO, commercial insurance intelligence for insurance companies, and health management service intelligence for patients/end-users.

The market scale of China's healthcare intelligence industry is expected to exceed 1.1 trillion yuan by 2030.

Government agencies face pain points such as low data utilization, insufficient emergency response capabilities, and low cost control efficiency. Medical intelligence is based on data integration and governance, combined with deep learning models and other algorithm technologies, to provide regulatory institutions with solutions for population health management, public health monitoring and disease traceability prediction, and intelligent medical insurance supervision. Its application scenarios include: population health management, public health monitoring, disease control management, and intelligent medical insurance.

The pain points of medical institutions lie in the lack of internal medical data governance capabilities and low efficiency in diagnosis, treatment, and research. Medical intelligence provides solutions for medical institutions and doctors to improve scientific research, clinical diagnosis, and operational management efficiency through technologies such as knowledge graphs, natural language processing, deep learning, and computer vision. Its application scenarios include: data processing platforms, specialized disease databases, patient follow-up systems, image-assisted diagnosis, clinical decision support (CDSS), clinical trial management, and more.

In the macro environment of healthcare cost control and the abolition of drug markups, pharmaceutical and medical device companies face greater pressure in R&D, production, sales, and other aspects. There is an urgent need to improve R&D efficiency and success rates, as well as the precision of patient care. Medical intelligence is based on big data, combined with artificial intelligence technologies such as knowledge graphs and disease models, to provide full lifecycle solutions covering clinical development to commercialization of drugs and medical devices. Its application scenarios include: drug discovery, registered clinical research, medical strategy plans and research designs, real-world studies, comparative effectiveness studies, digital marketing consulting, etc.

Insurance companies lack the accumulation of medical data and the application of artificial intelligence technology, making it difficult to achieve precise design and risk control of insurance products, resulting in low operational efficiency. Medical intelligence enables real-world insights to realize precise commercial insurance design, pricing, underwriting, and claims based on risk and disease burden, as well as personalized and precise health management services based on the insured's health status. Its application scenarios include: product design for urban benefit insurance programs, risk management and smart operations, innovative insurance design, intelligent underwriting, intelligent claims processing, etc.

Due to the increase in the number of chronic disease patients and the intensification of aging, the burden on basic medical insurance has been exacerbated. At the same time, traditional health/disease management struggles to meet consumers' personalized and precise needs. Medical intelligence, based on technologies such as in-hospital and out-of-hospital patient data and AI algorithms, constructs models for disease volume-effectiveness and risk prediction, enabling the prediction and assessment of diseases, thereby further meeting patients' personalized and precise needs for disease prevention, intervention, and management. Its application scenarios include: disease screening, health scoring, digital diagnosis and treatment, intelligent consultation, remote monitoring and management.

In the healthcare intelligence market targeting regulators,Medical intelligence companies such as Med66, Shenzhou Medical, and LifePoint provide solutions for government agencies for population health management, public health monitoring, and disease control management scenarios.

In the healthcare intelligence market targeting the supply side,Medical intelligence companies such as Med66 and SenYi Intelligence provide solutions for medical institutions in scenarios related to medical research, clinical diagnosis and treatment, and hospital operation management. Medical intelligence companies like Taimai Medical and Messe Medical, as well as some traditional CROs that offer intelligent services, provide solutions for pharmaceutical and medical device companies in scenarios related to R&D and post-market digital marketing.

In the payer-facing healthcare intelligence market,Medical intelligence companies such as Sipai and Miaokang Health provide solutions for insurance companies, including innovative risk design, intelligent review and compensation, and the design and operation of public welfare health insurance scenarios. Medical intelligence companies like Zhiyun Health and Yilian offer intelligent health and chronic disease management services for patients.

Med66 Technology ranks first in market share across all segments including the medical intelligence market, healthcare institutions and regulatory bodies, as well as emerging medical intelligence companies.

At the same time, the company is at the forefront of the industry in big data, cloud computing, technical capabilities (AI), medical knowledge and scenario experience, as well as the ability for high-frequency iteration of scenarios and algorithms (the 5 elements), driving the overall improvement of artificial intelligence technology, big data, cloud computing, and other capabilities in the healthcare intelligent industry.

As a leading enterprise in medical intelligence, Med66 possesses industry-leading 5E capabilities.

As a leading enterprise in the healthcare intelligence industry, companies within the sector take MedRec as a benchmark and focus on building five key capabilities, including enhancing data governance capabilities and expanding the coverage of disease knowledge graphs. This leads to the development of intelligent solutions that cover more scenarios.