Winning Health: Deep Integration of Big Data and Electronic Medical Records as a Unified Entity [EMR and Healthcare Big Data Series]

With the implementation of national policies on health and medical big data, electronic medical records (EMRs), as one of the foundational databases, are playing an increasingly prominent role in hospital information systems. Both startups and publicly listed companies are actively exploring and experimenting with technologies in this field.To address the development of electronic medical records (EMRs) within the context of big data in healthcare, VCBeat (WeChat Official Account: vcbeat) conducted exclusive interviews with industry experts from several of China’s most representative EMR companies.

Winning Health Technology Group Co., Ltd. was established in 1994 and is the first listed company in China dedicated to healthcare informatization.

Winning Health holds a substantial share in China’s healthcare IT market,China's 29 provinces, municipalities, and autonomous regions"Equipped with Various Types of Medical and Health Institutions"Over 4,000 users, with over 200 clients being tertiary hospitals or above.

The company's multiple electronic medical record (EMR) products have obtained computer software copyrights, includingEmergency Structured Electronic Medical Record System V5.0，Outpatient Structured Electronic Medical Record System V5.0，Inpatient Structured Electronic Medical Record System [Abbreviation: EMR] V5.0.

While rapidly developing its traditional healthcare IT business, Winning Health is also actively expanding into the “Internet + Healthcare Services” sector through its “4+1” strategy (Cloud Medicine, Cloud Wellness, Cloud Insurance, Cloud Pharmacy, plus an Innovation Service Platform),Promoting the Development of Medical and Health Cloud Services under the “Internet Plus” Model。

To understand the progress of Winning Health in electronic medical records and healthcare big data, VCBeat conducted an exclusive interview withChen Xu, Head of the Artificial Intelligence Laboratory at Winning Health、Yang Dejun, Senior Industry Expert at Winning Health.

Chen Xu of Winning Health:In June 2016, the State Council issued the Guiding Opinions on Promoting and Regulating the Application and Development of Health and Medical Big Data, marking the formal inclusion of the health and medical big data sector into China’s national development strategy. This move holds profound guiding significance for the health and medical big data industry.

Certainly. In July this year, the State Council issued the “Development Plan for New-Generation Artificial Intelligence,” which has once again heightened interest in artificial intelligence and big data. The plan explicitly states that laws, regulations, ethical norms, and policy frameworks for artificial intelligence, as well as big data infrastructure systems, will be gradually established.

As a result, big data and artificial intelligence are no longer regarded as conceptual technologies; instead, they have been formally incorporated into national planning and implemented as strategic technologies. This further affirms the role of artificial intelligence in driving technological innovation across various sectors of society.

Chen Xu of Winning Health:In my opinion, the development of this industry will undergo at least three stages. The first is the initial stage, which focuses on data preparation (including data acquisition, security and privacy protection, and handling data authenticity, integrity, consistency, etc., as well as preliminary data analysis) and market cultivation (including talent development and knowledge dissemination).

Next is the acceleration phase, which focuses on establishing data specifications and standards, developing and leveraging a unified data storage and computing platform, and delivering tangible benefits to healthcare stakeholders—including the general public—through diverse medical application scenarios, thereby creating a business model that gains broad market acceptance.

Third is the universalization stage, characterized by “de-emphasizing big data.” Big data has become one of the fundamental resources, as well as a critical analytical method and tool. In nearly all major healthcare scenarios, big data is omnipresent, much like water and air in our daily lives, thereby truly enabling intelligent and precision medicine.

Chen Xu, Winning Health:Winning Health’s products are primarily categorized by business function, centering on core systems such as the Hospital Information System (HIS) for patient diagnosis and treatment services, the Clinical Information System (CIS) for clinicians, the Nursing Information System (NIS) for nurses, and specialized systems for medical technology departments, including the Laboratory Information System (LIS), Radiology Information System (RIS), and Picture Archiving and Communication System (PACS). Additionally, to optimize existing hospital system architectures and enhance data management, Winning Health has launched products such as an Application Integration Platform and a Data Service Platform. These solutions integrate and consolidate services and data, thereby meeting the future operational and managerial needs of hospitals.

Taking our clinical research analysis product as an example, to achieve data sharing among different clinical information systems and thereby support the scientific research activities of our hospital, we have built a big data center platform dedicated to clinical research on the basis of the Clinical Data Repository (CDR).Centralize and integrate data previously scattered across various clinical business systems, encompassing the complete in-hospital lifecycle data of patients. By leveraging a series of technologies including big data processing, natural language processing (NLP), machine learning, and data mining, we have constructed a large-scale knowledge graph driven by clinical big data.

Automatically identify patient populations responsive to specific treatment regimens for common clinical issues (e.g., community-acquired pneumonia, antibiotic misuse). This approach integrates optimal therapeutic pathways mined from complex medical knowledge bases with best clinical practices identified through data analytics.

Our goal is to provide healthcare institutions with highly reusable and customizable standard data analysis workflows and tools, including disease risk analysis, similar patient analysis, and treatment effectiveness analysis, thereby offering support and insights for clinical research data analysis.

In addition, we have our own research and R&D products in the fields of AI for medical imaging (e.g., intelligent pulmonary nodule detection and intelligent bone age assessment), as well as intelligent analysis and information standards for multi-source, multi-modal healthcare big data.

We have successively established collaborations with Fudan University, Hefei University of Technology, the University of Chinese Academy of Sciences, and the First Affiliated Hospital of Anhui Medical University, as well as with numerous other top-tier academic institutions and hospitals. Through these partnerships, we have set up joint laboratories, thereby strengthening our R&D capabilities.

Yang Dejun, Winning Health:Winning Health currently serves three main categories of clients: the first category comprises healthcare service institutions, including large secondary and tertiary general hospitals, community health service centers, township health centers, and village clinics; the second category consists of healthcare administrative agencies, primarily health and family planning commissions at various levels and Centers for Disease Control and Prevention (CDC); the third category includes independently operated clinical laboratory centers and other institutions specializing in diagnostic testing and examinations.

Yang Dejun of Winning Health: Current demands for healthcare big data are closely tied to the specific institutions and development models involved. For instance, within medical consortiums, greater emphasis is placed on information interoperability, tiered diagnosis and treatment, and telemedicine.

Large, standalone tertiary Grade-A hospitals tend to focus more on clinical research, with an emphasis on disease diagnosis and treatment. In contrast, most secondary-level hospitals have greater needs in areas such as management, clinical information sharing, and decision support.

Chen Xu, Winning Health:“Valueless” data may simply reflect limited capabilities for mining and utilization at a given stage; some data that appear useless today could well become valuable assets in the future. Therefore, within the constraints of cost, technical architecture, and customer requirements, organizations should strive to retain all data.

Currently, nearly all data generated by electronic medical record (EMR) systems is valuable.

For instance, the utilization of clinical big data has facilitated the construction of medical knowledge graphs, with significant applications in clinical decision support and scientific research analysis. Nevertheless, the most pressing challenge we currently face remains data acquisition and integration. Without an effective platform for the centralized storage of large-scale, multi-source, heterogeneous medical data, value extraction will continue to be conducted in a fragmented, manual manner.

Yang Dejun, Winning Health:There is a broad business consensus on the significant value of electronic medical record (EMR) data; however, strategies for its utilization warrant further discussion, particularly regarding how to leverage such data more reasonably while ensuring robust protection of patient privacy.

Currently, the majority of medical data remains within healthcare institutions. To enable direct patient access for health-related purposes, it is essential to first establish enforceable regulatory and technical frameworks that ensure data security. Such secure data utilization holds significant value for health management and post-disease rehabilitation.

Yang Dejun, Winning Health:To achieve breakthroughs in medical big data, three key aspects must be addressed: First, data generators need to establish data governance organizations to ensure accurate and reliable data quality. Second, technical solutions are required for mining unstructured and semi-structured data, including image recognition. Third, it is necessary to build clinical semantic repositories and various standards for controlled clinical terminologies.

Chen Xu of Winning Health:The market is still in its nascent stage, with a large number of industry practitioners and startups eager to participate. While many are generating revenue within certain scopes, the market as a whole remains immature and exhibits some bubble-like phenomena.

The primary reason is that we are currently in the transition period from Stage 1 to Stage 2. As an emerging business model, medical big data must inevitably undergo tests across multiple dimensions, including technology, cost, and industry perception.

Chen Xu of Winning Health:Addressing the pain points and challenges posed by emerging technologies such as artificial intelligence and big data, Winning Health has adopted three major development strategies: First, it has successively established an Innovation Research Institute and an Artificial Intelligence Laboratory to conduct research on medical informatics, data standards, and cutting-edge technologies. The company focuses on translating into practical applications those technologies that are relatively mature and aligned with existing hospital clinical scenarios, enabling rapid replication and expansion to serve clinical practice through rigorous clinical testing and validation.

Second, Winning Health will collaborate with industry experts to conduct in-depth, project-based research in vertical healthcare domains, such as common diseases, oncology, and genomics.

Third, Winning Health will transform technologies such as big data and artificial intelligence into foundational public technologies to empower its proprietary products, thereby enabling hospitals and patients to be served through these products.

Having cultivated the healthcare IT industry for two decades, Winning Health has accumulated extensive business expertise, along with a comprehensive understanding of various business processes and product functionalities. Healthcare big data should return to its business roots, facilitating process optimization and clinical decision support for existing operations. By implementing scenario-based data applications and driving the closure of business data loops, it provides effective support and efficiency guarantees for clinical intelligence and scientific management.