The title picture comes from: worm creative, this article comes from WeChat public account: Everyone is a product manager (ID: woshipm) < / span> , the original title of “hard-core: improved national monitoring and early warning network of infectious diseases with the block chain technology”, author: Wu Shi children

In the Spring Festival of 2020, new coronary pneumonia affects everyone’s heart. What can we do as connected people in this battle? In this article, the author tells us from a professional perspective that there are many things we can do.

Keyword: Blockchain Infectious Disease Surveillance and Early Warning Infectious Disease Direct Reporting

Related nouns: National Infectious Diseases Automatic Warning Information System, Infectious Disease Report Information Management System, Hospital Information Management System (HIS) , National Infectious Diseases Disease network direct reporting system (NNDRS) , public health data exchange platform, public health management information system, ICD-10 diagnostic code, population health information platform , Infectious atypical pneumonia (SARS) , electronic health records (EHR) , electronic medical records (EMR) , National Center for Disease Control and Prevention (CDC)

2020 is bound to be an extraordinary year.

The author is thinking about this complicated mood, and decides to writeAt the time of this article, the latest national statistics on pneumonia of new coronavirus infections are:

As of 19:26 on January 29, 2020, China’s (including Hong Kong, Macao and Taiwan) confirmed 6081 cases, 132 died, 116 were cured For example, it has infected most of the provinces except Tibet Autonomous Region-the spread of the epidemic, catching up with SARS that year.

You know, SARS was 17 years ago. Nowadays, regardless of domestic medical infrastructure, sanitary conditions, or supporting epidemic management software, it has made rapid progress. The automated warning and epidemic prevention of infectious diseases have also reached the international advanced level. I do n’t want to I believe that when the spring of 2020 begins, the epidemic will break out so quickly and so unexpectedly.

With curiosity about the domestic epidemic prevention system, the author consulted a large number of literature on the disease surveillance network to try to find the reasons for the failure to prevent and control the epidemic in a timely manner.

Because the author is not a medical staff, this article does not explain how to prevent and treat coronavirus; not a government worker, not a Weibo blog, so I do n’t talk about the merits of the incident; the author is just an IT technician, I try to pass technical To review and analyze the current status of the automated reporting and early warning system of infectious diseases in China from a systematic perspective, we hope to adopt new technologies and new structures to improve the transparency and timeliness of infectious disease surveillance and early warning.

More importantly: the author is a citizen of the country and has the right and obligation to contribute his strength to participate in the governance of the country and society.

If there is any deviation in the professional system part of the text, please correct it in time, thank you!

I. Status Analysis

Current status of reporting and surveillance of infectious diseases in China:

In April 2008, China ’s 31 provinces across the country (municipalities, autonomous regions) have run the national automatic warning system for infectious diseases and established Automatic warning and response mechanism; it has realized the automatic analysis of surveillance data for 39 infectious diseases, real-time identification of spatiotemporal aggregation, sending of early warning signals, and real-time tracking of response results. It is currently in the advanced position in the world.

At the same time, in addition to the national automatic warning system for infectious diseases, China has also built a national infectious disease report information management system toAnd its core subsystem, the National Infectious Diseases Network Direct Reporting System (NNDRS) , real-time and online implementation of legal infectious disease cases based on medical institutions , Direct reporting;

In order to improve the completeness and accuracy of surveillance data, electronic health records (EHR) , electronic medical records (EMR) and other standardized and unified data collection, have also piloted and run the four-level population health information platform and its data exchange platform (district, city, province, country) ;

In order to reduce the difficulty for doctors to fill in infectious disease report cards, the hospital’s HIS system and direct reporting system have been opened. The medical records will pop up or manually open the filling page, and semi-automatic submission of infectious disease report cards.

1. Specific system architecture

Because the construction situation is not the same in all provinces across the country, I use the above figure as a reference to highlight the specific process of reporting the current national infectious disease report:

▲ The current reporting and early warning structure of infectious disease reports in China

In some well-established provinces, semi-automatic and manual infectious disease report uploading methods can be supported. Doctors can use the hospital HIS system to automatically pop up infectious disease reports when filling in electronic medical records. The card supplements the data format and integrity through a four-level public health data exchange platform. (Electronic Health Card and Electronic Medical Record) The data was finally collected into the National Infectious Diseases Network Direct Reporting System (NNDRS) The National Early Warning System for Infectious Diseases adopts these infectious disease report cards and adopts fixed threshold method and time model method. (moving percentile method, cumulative and control chart method , Aggregate Epidemic Situation Law) Calculate, monitor and analyze 39 infectious disease epidemics on a daily basis and give early warning to grassroots hospitals and CDCs.

2. Report specific business processes

Let’s take a look at the approval process for reporting an infectious disease report card:

Infectious diseases are semi-automatically or manually filled in infectious disease report cards by clinicians after they are discovered, and then submitted to the hospital for review. After being reviewed by the in-hospital health insurance doctors, they are submitted to district and county and city-level disease control centers for review and supplementation, and finally pass the provincial level. And national health data exchange platform to the national infectious disease network direct reporting system.

▲ Infectious disease epidemic reporting process based on direct introduction of electronic medical records

Note: The picture comes from Kong Yuanyuan, Gao Guiling, Zhang Qinghui, Guo Xiaoqin Practice of infectious disease epidemic report and management information system based on hospital electronic medical records / p>

Whether it is the system structure or the review and submission process of the infectious disease report card, it is uploaded and promoted layer by layer, and hierarchical management is realized.

The structure of the uploaded infectious disease report card is as follows:

▲ Infectious disease report card in HIS system of a basic hospital

Second, why is there no warning this time?

The infectious disease surveillance system in China has evolved from the old manual reporting method to the IT-based and information-based reporting method, and has basically achieved the aggregation and monitoring of 39 infectious disease data across the country.

Compared to SARS in 2003, it is indeed a very big improvement, but the real problem is:

Why is the National Automated Early Warning System for Infectious Diseases dumb before this major outbreak?

By carefully reading the relevant papers and literature of the “Disease Surveillance Network”, the author concludes that the current national infectious disease reporting and early-warning mechanism in China has serious hidden dangers for new major outbreaks. The specific problems are as follows: >

1. Infectious disease report card is actually a judgment result of known ICD-10 diagnostic codes, and it takes a long time to confirm new diseases.

As you can see from the figure above, the current national infectious disease report card is triggered based on the ICD-10 diagnostic code, which reports 39 known infectious diseases, and new types of infectious diseases require repeated verification and confirmation and reporting. The judgment period is long.

Although the report card containsSuspect reporting options, but each doctor, each hospital and local CDC bears the pressure of corresponding individual and institutional reporting accuracy, and reporting suspected cases without certainty is itself a courage.

Note: Only on January 24, 2020, the National Center for Disease Control and Prevention launched a new function for detecting pneumonia infected with a new type of coronavirus pneumonia.

2. Infectious disease report cards require level 3 manual approval from discovery to reporting. Whether the report is successful or not, there are too many human interference factors.

At present, after the clinician fills in the report, the infectious disease report card will be reported to the National Infectious Diseases Network Direct Reporting System, which requires 3 manual approvals, namely: in-hospital health insurance review, district and county CDC review, Level CDC audit.

Why so many manual reviews?

It is mainly based on the completeness and accuracy of data reported by national infectious diseases.

Using multiple agencies and personnel to verify and approve is a very safe and secure way; but it is a major shortcoming for monitoring the outbreak of major infectious diseases.

Once an early epidemic of infectious diseases occurs, the stability of the local government, economic and public pressure may affect the smooth reporting process.

The infectious disease report card originally served the early warning and surveillance of infectious diseases, but its structural nature hindered the response to the emergent major infectious disease surveillance.

3. The early warning model of the National Infectious Diseases Early Warning System is a rule model in nature, and it can only detect and alert for known diseases.

In 2008, China operated the national automatic warning system for infectious diseases and established an automatic warning and response mechanism. The early warning data comes from the data reported by the national infectious disease report card.

The early warning model is mainly divided into two kinds of fixed threshold method and time model method. The fixed threshold method is an event model that sets the threshold of the number of occurrences for 15 major infectious diseases. The method is divided into: mobile percentile method, cumulative and control chart method, and cluster epidemic method. It is the detection of 18 infectious diseases. Its essence is to increase the historical statistical analysis of time and space dimensions. The proportion of emergence exceeds a certain percentage. This phenomenon generates early warning.

Current warning models for infectious disease early warning systems in ChinaIt is not a conditional model based on big data analysis, but only a judgment model based on the result rules of the infectious disease report card.

The rule judgment model must be a judgment and early warning of known infectious diseases, so it has basically no effect on new types of major infectious diseases.

4. National infectious disease reporting is a gradual review and summary report, which lacks transparency and is deficient in responding to sudden large-scale infectious disease epidemics.

The national infectious disease report is passed by the hospital after the clinician finds and reports the infectious disease report card—> district CDC audit—> city CDC audit—> three-level data exchange platform—> step-by-step summary of the national direct reporting system There are many levels of aggregation, manual data supplement and review process are cumbersome-this is okay for daily data management, and it is stretched to cope with the sudden epidemic.

In addition, there is a lack of data comparison between patients with the same symptoms between hospitals. Infectious disease report cards are only uploaded vertically, and there is no horizontal information sharing. For the prompts and early warning of other hospitals, only the national automatic infectious disease early warning system can be used. .

Three, Improved Suggestions

Optimize the current gradual vertical one-way national infectious disease reporting network, and use the blockchain fragmentation mechanism to establish district, city, province, and national four-level blockchain automated data synchronization networks, relying on each of the four-level networks Level of disease control center, to establish autonomous data collection and real-time early warning capabilities of infectious diseases, do not completely rely on national infectious disease early warning systems.

Using the existing public health data exchange platform as the exchange node for each level of data, a real-time automated data exchange mechanism is formed.

The infectious disease report data between the districts is synchronized in the municipal epidemic prevention chain; the infectious disease report data between the cities is synchronized in the provincial epidemic prevention chain; and so on, the national epidemic prevention data is synchronized to the national level.

Like the four wheels, the four-level epidemic prevention chain automatically completes the internal epidemic prevention and warning work in each district, city, and province, and continuously updates and supplements the data of other provinces through the national level epidemic prevention chain to form a regional epidemic prevention capability with a certain regional autonomy. The internet.

▲ Four-level epidemic prevention chain

Details are as follows:

1. Establish a two-line asynchronous parallel process for the initial registration and reporting of infectious disease report cards, manual verification, and post-event supplementation.

Modify the current serial process of filling, supplementing, verifying, approving, and reporting infectious disease report cards: the first-line asynchronous parallel process of infectious disease report cards registration and reporting, supplementation, verification, and approval.

▲ Asynchronous parallel process for infectious disease report card

In the current national infectious disease reporting system, the data integrity and accuracy requirements for infectious disease reports are too high, so they can only be verified step by step, supplementary information and review, which delays the best time to report infectious diseases.

We all know that the misreporting of infectious diseases will have a great impact on the economic and social stability of the local government. This is also the main reason why we would rather choose a more secure serial audit reporting model; but serial audit The reporting responsibilities and pressure of the reporting model are all in the doctor, the hospital, and the local CDC, so it is highly likely that it will be affected by government and human intervention, concealing and delaying reporting.

As we all know, the early warning model based on big data does not make strict requirements on the completeness and accuracy of singleton data. The scale, scope and timeliness of data are the core of big data early warning of infectious diseases.

So it ’s recommended to relaxThe authority for the first report of infection, doctors and primary medical institutions can directly report the initial infectious disease report card; afterwards, the insurance doctor and district, city CDC personnel verify and supplement the report card; and national infectious disease big data warning can use the first infection The disease report card calculates the outbreak and spread of infectious diseases in advance, so as to carry out early warning and preparation.

2. Separate medical records and examination report data, and increase the collection of data on risk symptoms of infectious diseases.

The infectious disease report card is conclusive in nature, and it takes a lot of time to determine whether it is suspected or confirmed.

After establishing a conditional early warning model of big data, in addition to collecting infectious disease report card data, infectious disease risk symptom data can also be separated from medical records and inspection reports for automatic identification and reporting.

It is recommended that the National Infectious Diseases Direct Reporting System increase the collection of infectious disease risk symptom data. Infectious disease risk symptom data, such as fever, chest radiograph description, cough, and biochemical indicators, can be separated and analyzed through unstructured data analysis. Identification, labeling of key infectious disease risk symptoms, and automatic upload through four-level health and health data exchange nodes.

Since the report card for infectious diseases is not directly uploaded, it has no direct impact on social stability and the economy. For big data early warning, the scope and scale of data can be increased, and the accuracy of early warning can be improved.

In addition, the reporting of infectious disease risk symptom data shifts the pressure from doctors, hospitals and local CDCs to the fourth-level health and health data exchange node, and replaces manual reporting with automation, reducing the burden of responsibility at the grassroots level.

3. A big data condition analysis model is used to supplement the original regular event model to establish a national and grass-roots two-level warning network.

As mentioned above: At present, the national automatic warning model for infectious diseases is a rule model. The rule model has only an early warning function and no predictive function.

It is recommended that the National Infectious Diseases Automated Early Warning System establish a set of “Big Data Condition Analysis Models” as offline forecasting and early warning support libraries, and collect “Infectious Disease Risk Symptom Data” and “Internet Data” other than “Infectious Disease Report Cards” “.

For example: air ticket booking, drug supply, search data, etc., to build a national top-level off-line early warning network for infectious diseases.

At the same time, relying on the real-time synchronization capability of the four-level anti-epidemic chain data, intelligent integration through the blockchainEstablish a real-time judgment and early warning capability based on the data of the rule model; sink the current automatic warning function of national infectious diseases into the district, city and provincial epidemic prevention chains to form a grassroots real-time early warning network.

The national top-level off-line early-warning network of infectious diseases and the real-time early-warning network at the grass-roots level work together at the same time, which can take into account the real-time nature of early warning and the ability to predict big data.

4. Establish a distributed, point-to-point, and infectious disease report data sharing network based on hospitals and local CDCs.

District and county-level hospitals, district CDCs, and municipal CDCs are the basic windows for reporting infectious diseases. Hospitals and CDCs have the obligation and responsibility to report cases of infectious diseases, and they are the basis for the country’s overall surveillance, early warning, and control of the epidemic.

However, in terms of judging the overall situation of the current epidemic situation, the hospital can only report from the top to the bottom through the CDC statistics of infectious disease reports.

We know that outbreaks of major epidemics often have sudden characteristics, and in the early stages of an epidemic, reporting data in the first time, across multiple hospitals, and across multiple regions, will greatly enhance the confidence of doctors and hospitals in reporting the epidemic. It provides first-line medical workers with awareness of the epidemic situation and provides basic guarantees for preparing material protection in advance.

It is recommended to build district, city, province, and national blockchain epidemic prevention chains to achieve automatic synchronization of epidemic data across hospitals and regions, and to achieve cross-regional and Hierarchical data exchange.

Single chain achieves data synchronization in the region through the data synchronization capability of the blockchain automation node; the four-level epidemic prevention chain can achieve certain grassroots autonomous early warning capabilities through smart contracts, and can control the epidemic situation and scope in the region early in the outbreak. .

▲ Grassroots autonomous warnings