Source of this article: Digital Economy and Society
Author: Zhang Xiao Hong Huang Wenli Lan Cheng (China Finance Research Institute of Zhejiang University of Finance and Economics)
Counting from the first announcement of the outbreak on December 30, 2019, the number of pneumonia cases of the new coronavirus infection was within 30 days, and the number of confirmed cases exceeded the number of SARS cases in 2003. According to reports from 31 provinces (autonomous regions and municipalities) and the Xinjiang Production and Construction Corps, there are currently 53284 confirmed cases (among which 11,477 are severe cases), a total of 20659 discharged cases have been cured, a total of 2345 deaths have been reported, and 76288 confirmed cases have been reported There are 5365 suspected cases.
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The inadequate early warning of infectious diseases, the late detection of the epidemic, and the lack of corresponding preventive measures have exacerbated the severity of the epidemic. The Central Government clearly stated on the Central Comprehensive and Deepening Reform Committee that it is necessary to reform and improve the disease prevention and control system, resolutely implement the prevention-oriented approach to health and health work, persist in unremitting efforts, move the prevention barrier forward, and prevent minor diseases from becoming a pandemic. We should encourage the use of digital technologies such as big data, artificial intelligence, and cloud computing to better play a supporting role in epidemic surveillance analysis, virus tracing, prevention and control, and resource deployment. We believe that in the context of the digital economy, the use of blockchain technology can well improve the limitations of the current infectious disease early warning system, thereby opening up data silos between medical institutions and achieving medical information data sharing; optimizing infectious disease early warning data sources and improving The overall effect of the epidemic early warning system; promote the flat management of the reporting system and improve the efficiency of epidemic information transmission.
I. Status and limitations of early warning systems for infectious diseases
The current automatic early warning mechanism for infectious diseases is mainly composed of two parts: the database of the National Infectious Disease Surveillance Center and the automatic early warning system. The National Infectious Disease Surveillance Center database is an Internet-based national disease surveillance information report management system launched in 2004. It covers all types of medical and health institutions at all levels throughout the country, and is used to collect and report case information of infectious diseases, and to electronicize and store case report data. The automatic early warning system uses mathematical algorithms to continuously perform automatic analysis and calculation of the nationally reported infectious disease surveillance data, and uses modern communication methods to send an abnormal increase or aggregation of detected diseases to the county (district) in a timely manner via mobile phone text messages. Disease surveillance staff of the CDC. The system was officially put into operation nationwide in April 2008.
At present, China's early warning system basically realizes the collection and monitoring of data on 39 infectious diseases nationwide. With the development of science and technology and the maturity of technical conditions, the country has also successively established the national infectious disease report information management system and its core subsystem, national infection. Disease network direct reporting system, basically realized real-time, online, direct reporting of legal infectious disease cases based on medical institutions. Although the current early warning system is constantly being improved, from the perspective of digital technology, a re-examination and careful study of the current early warning system can reveal the following problems:
1. Information islands and cross-regional management issues. Through the process of reporting the infectious disease report, we can find that the hospital information management system (HIS) and direct reporting system of each hospital can reduce the difficulty of filling the infectious disease report card to a certain extent, improve the uploading efficiency, and speed up the transmission of data. But at the same time, hospitals and epidemic control centers are separated from each other, and information and illness cannot be shared between each other, forming an island of information. The formation of information islands has brought cross-regional management issues between different hospitals, institutions, different regions, provinces and cities. Data comparison of the same symptoms, disease information, and research on special epidemics cannot achieve horizontal sharing.
2. Problems such as missing data and single structure. After the infectious diseases are discovered by the clinician, the infectious disease report card is filled in semi-automatically or manually, and sent to the national infectious disease network direct reporting system through the provincial and national health data exchange platforms. For suspected, similar but unconfirmed other cases and the collection of risk symptoms of infectious diseases, such as: fever, chest radiograph, cough, biochemical indicators, etc., the national infectious disease early warning system cannot analyze the first time, which makes the analysis There is a large unity of data. At the same time, national infectious diseases follow a gradual reporting mechanism, lacking transparency, and the authenticity of data cannot be guaranteed. In addition, the data uploaded by various hospitals through the HIS system has a large human factor. The filling of the infectious disease report card is under pressure from the outside world and everywhere, which has a great impact on the confirmation and upload of the data.
3. The time interval between review and report is long. At present, infectious disease report cards need to be manually reviewed by the disease control centers at the hospital, county (district) level, city level, etc. after reporting by the clinician to the national infectious disease network direct reporting system. Verification and approval by multiple agencies and personnel is a relatively safe and secure method. Although it is conducive to ensuring the integrity and accuracy of the data, multiple manual reviews have increased the reporting interval to a certain extent and delayed the issue of early warning. The best timing.
4. There are still some problems with the early warning system due to the problems of its own early warning method, threshold setting, and judgment diagnosis method. First of all, there is no distinction between early warning methods and thresholds. Considering the differences in the incubation period, infectious period, spreading power, passage time and public health significance of different diseases, the early warning methods and thresholds of different diseases need to be different. The current methods of early warning mechanisms are not diverse enough and the pertinence of threshold setting needs to be further strengthened. In addition, the number of early warning signals between different diseases and the number of outbreaks finally found are quite different. For some diseases with more reported data but less outbreaks, the effectiveness of the early warning system needs to be improved.
Second, the early warning model diagnoses the disease in a single way. The current automatic warning mechanism is mainly based on statutory reporting of infectious disease surveillance data, but this is only one of the early detection methods for disease outbreaks. In actual work, in addition to infectious disease report cards, there are other means such as medical staff reports, teachers or school doctors reporting disease prevention and control personnel outbreak monitoring, family or media reports, etc. The current model of the infectious disease early warning system in China is only Based on the results rule judgment model of the infectious disease report card, the discovery method is too simple.
In summary, due to the above-mentioned shortcomings in the current automatic early warning systems for infectious diseases, when the epidemic broke out, it could not play a timely and effective role. Therefore, it is suggested to introduce blockchain technology as a supplementary means to improve the current automatic early warning mechanism of infectious diseases, improve the major epidemic prevention and treatment system, and improve the major epidemic emergency response mechanism.
Second, the blockchain technology optimizes the epidemic warning system
Compared with traditional epidemic early warning systems with problems such as information islands, single structure, and long review time, blockchain technology can be used to upgrade the epidemic early warning system. The blockchain is essentially a decentralized distributed ledger database, which has the characteristics of decentralization, immutability and forgery, traceability, and collective maintenance. Based on these characteristics, the blockchain can help institutions such as hospitals and disease control centers to quickly and securely authenticate permissions, realize free data access and sharing, and form a new model of joint sharing and joint defense led by relevant government departments and multi-center collaboration. Therefore, the blockchain is the key technology to reform and improve the disease prevention and control system, move the prevention barrier forward, and prevent minor diseases from causing a pandemic.
(I) Open up data silos between medical institutions and realize medical information data sharing
Establish alliance chains between medical institutions, promote data sharing such as medical information and epidemic situation information, and achieve in-depth horizontal exchanges. Aiming at the lack of data comparison between patients with similar symptoms in current medical institutions, and underestimating the destructive impact of infectious diseases, blockchain technology is used to establish a complete, standardized and maintainable shareable, maintainable, and cross-chain method through alliance chain and cross-chain. Medical information database. According to the extremely private and inconvenient disclosure characteristics of some medical information, access to this part of data has strict permission restrictions. Use the alliance chain with certain access mechanisms and access conditions in the blockchain to build an alliance chain between medical institutions in the same area, jointly manage, maintain, and share information to achieve multi-directional data communication. The cross-chain technology in the blockchain is used to open different alliance chains to achieve cross-chain data interaction and complementary advantages, thereby promoting the cross-border flow of medical information data and increasing the degree of data sharing.
Relevant national departments take the lead to divide the authority and responsibility of each subject and node in data sharing to ensure the effective operation of the database. Due to the sensitive and confidential characteristics of infectious disease data, it must inevitably require the supervision of certain government departments. In the epidemic early warning system, decentralization does not mean that all subjects have equal rights and responsibilities. Through the point-to-point technology of the blockchain, two-way integration and multi-way communication of multiple subjects are realized. Relevant government departments can coordinate planning and directly coordinate each subject in the chain. And nodes' rights and responsibilities to maintain orderly sharing of data in the system and perform efficiently.
(II) Optimizing the early warning data source for infectious diseases and improving the overall effect of the early warning system for epidemic situation
By using the traceability of the information and data of the blockchain technology, the source of infectious disease outbreaks can be quickly identified, and the efficiency and level of epidemic prevention can be improved. The blockchain timestamp used to identify a moment is non-tamperable, can accurately record the data's block time, adds time dimension to the information data, has uniqueness, and ensures that the information data stored therein has traceability Verifiability. Once an epidemic breaks out, the source can be determined very quickly along the time chain, strangling the epidemic in the cradle and reducing the risk of epidemic spread.
Increasing information and data related to infectious disease symptoms, and improving the speed and accuracy of epidemic warning. In the blockchain information database, data uploaded by hospitals, disease control centers, and the Ministry of Health can be divided into structured and unstructured data. The structured data includes values and text related to infectious diseases. Unstructured data includes related data such as infectious disease pictures and audio. Due to the large amount and complexity of these data, only the hash value of these data is chained, and the hash value is taken as the structured data stored in the node. . In addition to uploading traditional infectious disease traits, additional direct material data such as chest radiographs and related symptom photos of infectious disease patients are added, which is no longer limited to confirmed cases and improves the speed and accuracy of infectious disease judgment.
Combined with flexible and fast data processing and analysis of big data, the use value and space of blockchain medical information data are greatly enhanced. On the one hand, blockchain technology is a secure, desensitized, legal, and correct credit endorsement of big data. On the other hand, big data data sorting, analysis, visualization, and application technologies can efficiently and perfectly use blockchain data. Big data technology based on blockchain data can reduce manual tasks, automate the detection and analysis of infectious disease data sources, increase the breadth and depth of epidemic warnings, and meet the diversification of infectious disease warnings in different regions and with different symptoms. demand.
(3) Promote the flat management of the reporting system and improve the efficiency of epidemic information transmission
Disease prevention and control centers at all levels register nodes in the blockchain system, flatten the traditional " infectious disease reporting system " vertical reporting model, and accelerate the transmission of epidemic information. Building a medical alliance blockchain, all hospitals and disease prevention and control centers at all levels register nodes in the system, and each node can directly receive epidemic information broadcast across the entire network. When a single hospital finds a suspected epidemic case, it uploads the information to the chain for broadcast on the entire network. Due to the open and transparent nature of the blockchain, data tamperability and traceability, each node can obtain accurate reports at the first time. Information, reducing the time and potential for misinformation. After obtaining the information, each hospital can consciously pay attention to patients with similar symptoms, disease prevention and control centers at all levels can prepare for epidemic prevention in a timely manner, and the national epidemic prevention center can immediately conduct research and take corresponding measures to overcome the lag of traditional early warning models.
(4) Establishing automatic early warning smart contracts to reduce human factors in epidemic release
Verify and confirm the reported data, encourage other doctors who find the situation to report the situation, and reduce the phenomenon of concealment. Using smart contracts to establish a review and confirmation system in the blockchain. After doctors report suspected outbreaks, nearby hospitals and CDC nodes have the responsibility to confirm based on specific conditions, verify whether the reported information is accurate, and distribute the pressure on the reporters. The reported information can be released only after the verification and confirmation of other nodes, and the neighboring nodes are responsible for reporting the concealed nodes within their capabilities, and play a role of mutual supervision to reduce the possibility of concealment.
Combined with big data technology, an automatic early warning system for epidemic situations at all levels was established to strengthen the ability to respond to new viruses. The traditional automatic early warning system mainly performs automatic early warning based on confirmed and reported cases of infectious diseases. However, as new infectious diseases are not added to the system options, the system cannot upload new cases, which causes the automatic early warning system to fail. A smart contract refers to a procedure that can automatically perform a preset operation without being disturbed by other factors when a previously set condition is triggered. Smart contracts combined with big data technology, instead of artificially diagnosed infectious diseases, automatically link suspected infectious disease cases with symptom similarities exceeding a certain threshold in the alliance chain into a chain. When the chain reaches a certain length threshold, the smart contract automatically realizes early warning, broadcasts the entire network, initiates early warning and epidemic prevention measures, and increases the timeliness and objectivity of early warning. From local early warning to national early warning, different smart contract parameters are set according to different early warning levels, including predefined states, transition rules, triggering conditions, response operations, etc., and a grading and layered major epidemic early warning mechanism is established.