Miao Health and Inspur Group Forge Strategic Partnership to Bridge Hospital-Home Data Gap and Build a Closed-loop Healthcare Big Data Ecosystem

Since 2015, health and medical big data has evolved from its initial clear definition to being incorporated into the national big data strategic layout by the State Council, emerging as a new growth pole for the future development of the health and medical industry.

Issues such as low standardization, fragmented management, and technological silos that previously plagued big data in health and healthcare have been brought to the forefront. Policy formulation aimed at standardizing hospital-based health and healthcare big data and enabling interoperability has become the primary direction of current development.

The “Guiding Opinions of the General Office of the State Council on Promoting and Standardizing the Application and Development of Health and Medical Big Data,” officially promulgated in June 2016, set the tone for the development of health and medical big data.

In 2017, the successive establishment of three major state-owned big data groups initially formed a landscape dominated by the National Health and Family Planning Commission, with these three groups tasked with building national health and medical big data centers, regional centers, application development centers, and industrial parks.

Signing Ceremony (Image source: Provided by the company)

In May 2018, Beijing Miaoyijia Information Technology Co., Ltd. (hereinafter referred to as “Miao Health”) and Inspur Software Group Co., Ltd. (hereinafter referred to as “Inspur Group”) formally signed a strategic cooperation agreement. The two parties will engage in in-depth collaboration in areas such as internet application service operations, health intervention management based on healthcare data, and AI-driven health and elderly care projects. This signing marks the first key strategic cooperation project following the State Council’s executive meeting on April 12, which determined measures to promote the development of “Internet + Healthcare.”

As a member of the national team for health and medical big data, what kind of “spark” will be generated by Inspur Group’s collaboration with Miao Health, a mobile health management platform? In which areas will the two parties join forces? In response to this partnership, VCBeat conducted an exclusive interview with Kong Fei, CEO of Miao Health.

The healthcare sector generates massive volumes of highly complex data. Each patient’s personalized treatment plan yields diverse types of information, including medical imaging, pathological slides, and biochemical analyses. The lack of interoperable interfaces for data sharing across software and hardware systems among various healthcare institutions has hindered the efficient collection of big health data, creating a disconnect between data acquisition and application. Information silos have become the most significant obstacle to the application of medical big data in current healthcare institutions.

In fact, beyond the structured data generated during patient consultations, a larger volume of big data exists not within hospitals but rather in the home environment after diagnosis and treatment have concluded. Out-of-hospital physiological data reflects various aspects of daily living, lifestyle habits, physiological changes, potential lesions, disease progression, medication frequency, and rehabilitation status, all of which hold significant clinical value in medicine.

However, compared with the large-scale in-hospital medical data stored in Hospital Information Systems (HIS), acquiring large-scale out-of-hospital health and health behavior data has consistently been more challenging.

With the widespread adoption of smartphones, wearable devices, and other products, non-medical-grade health monitoring solutions have seen significant growth, enabling convenient self-monitoring of health data for diverse populations, including healthy individuals, those in a sub-health state, and patients.

It is common to see that iPhone-based HealthKit can record metrics such as step count, running distance, and body weight. The latest version of the Apple Watch can even accurately monitor data such as heart rate. The widespread adoption of wearable devices has made daily human behaviors quantifiable; however, once these fragmented behavioral data are collected, their value is primarily leveraged for preventive purposes, such as formulating health management plans.

In fact, breaking down the information barriers between hospitals and homes is not limited to the "pre-hospital" phase; significant efforts must also be devoted to the "post-hospital" period. The medical value of health big data is largely derived from the monitoring of physiological indicators during the interval between post-treatment discharge and the subsequent follow-up visit.

Kong Fei stated that the difficulty in collecting out-of-hospital health big data lies in: “Previously, there was a severe lack of health monitoring and management for patients in China after they left the hospital, making it impossible for doctors and hospitals to track patient behavior and health data.”

Indeed, hospital data constitutes the core of clinical care; however, once a patient is discharged, the collection and feedback of their medical information typically fall outside the hospital’s scope. Currently, post-discharge physical recovery data primarily rely on feedback from follow-up visits or information gathered through patient follow-ups.

The requirements for health big data are scale and continuity. The gap between initial diagnosis/treatment and follow-up visits results in discontinuity in in-hospital and out-of-hospital health and medical big data. Experience from developed countries has demonstrated that the data chain for many rehabilitation processes can seamlessly extend from hospitals to patients’ homes. Therefore, the concept of the “bedside” extends beyond the hospital “bed” to include the home “bed.”

Therefore, in the application of big data, leveraging the Internet of Things (IoT), wearable devices, and other technologies to continuously monitor and collect patient data during and after clinical visits has become a crucial means of bridging the data gap between diagnostic and treatment phases, thereby establishing a closed-loop big data ecosystem. This focus also constitutes the core component of the collaboration between Miao Health and Inspur Group.

According to data from Jiefang Daily’s Shanghai Observer, there are 290 million cardiovascular disease patients in China, yet over 95% of medical data remains underutilized. This untapped big data has led to higher diagnosis and treatment costs as well as increased financial burdens on families. Establishing standardized “barrier-free channels” for big data integration both within and outside hospitals can reduce medical costs and economic burdens by at least 20%.

It is often said that out-of-hospital data resembles “scattered soldiers,” existing in a fragmented and dispersed state; however, for Miao Health, collecting such data appears to be “not so difficult.”

Since its inception in 2014, Miao Health has prioritized the interoperability of diverse health data and services. In early 2016, it launched “Miao+,” an open platform for health data and services. The platform currently integrates data from over 300 smart devices across major mainstream brands, as well as various health-related data sources, including physical examinations, genetic testing, and insurance records, thereby providing users with comprehensive health data monitoring and management solutions.

“Miao+” platform has currently integrated data from over 300 smart devices across major mainstream brands (Image source: Provided by the company)

Meanwhile, Inspur Group, the other party to this collaboration and a key member of China’s national big data team, maintains four major resource databases: basic resource information, population-wide demographic data, electronic health records (EHRs) for residents, and electronic medical record (EMR) summaries, accumulating nearly 5 billion data entries. Its strength lies in possessing a mature repository of in-hospital healthcare big data. Inspur is also the only IT specialist enterprise in China that offers comprehensive competitive advantages spanning cloud data centers, cloud computing, and big data services.

Leveraging the respective strengths of both parties in in-hospital and out-of-hospital data, the collaboration between Miao Health and Inspur can effectively integrate in-hospital medical data with out-of-hospital health behavior data. Once the platforms are interconnected, physicians can rapidly access patients’ health and health behavior data from discharge to follow-up visits, thereby enabling more precise formulation of the next phase of treatment plans.

Kong Fei stated, “The collaboration between the two parties has achieved the integration of in-hospital medical data and out-of-hospital health behavior data, which is conducive to exploring the construction of a closed-loop model for big data in healthcare.”

Miao Health and Inspur Group will jointly build a health management model supported by a mobile health platform, creating precise health profiles for users. Centered on a health knowledge graph and leveraging artificial intelligence technologies, they will provide intelligent, precision services addressing users’ health needs—including health reminders, physical examinations, insurance, medical care, and genetic screening—thereby forming a closed-loop health solution and delivering value-added application services.

Furthermore, both parties will fully leverage their respective strengths and distinctive capabilities in industry, platforms, technology, data, and solutions to deepen cooperation in areas such as internet application service operations, health intervention management based on healthcare data, and AI-driven health and elderly care projects. This collaboration aims to enhance complementary advantages in business development, information resources, application services, technological advancement, and data resources.

Following its collaboration with Inspur Group, Miao Health will further expand the volume of health big data storage and incorporate multi-dimensional health data. Leveraging this foundation, the company aims to accelerate the development of artificial intelligence to create more scientific and effective health management solutions and methodologies.

Currently, the Miao Health app alone has amassed over 35 million registered users and 4 million monthly active users. By integrating various smart hardware devices, intelligent health screening robots, and all-in-one smart physical examination kiosks, Miao Health is capable of collecting hundreds of health metrics and behavioral data points covering more than ten physiological systems, including the circulatory, digestive, respiratory, endocrine, skeletal, immune, reproductive, and integumentary systems.

However, processing massive health big data to achieve more accurate model predictions is not something that can be accomplished alone. Therefore, Miao Health has chosen to form strategic partnerships with leading institutions across various fields, creating a synergistic effect where 1+1>2.

With the rapid development of technologies such as the Internet of Things, big data, and artificial intelligence, large-scale application of mobile internet models in the field of healthy living has become possible. Kong Fei stated, “In the future, Miao Health will continue to integrate and analyze health behavior data and medical data to make health management more scientific and precise.”