A few days ago, a patient reported that the Second People’s Hospital of Wuhu City, Anhui Province (hereinafter referred to as "Wuhu Second Hospital") overcharged medical expenses, which aroused strong concern in the industry about "excessive diagnosis and treatment".

On December 2nd, Anhui Medical Insurance Bureau informed the Second Hospital of Wuhu about the illegal use of medical insurance funds, and on the 4th, official website of Hunan Medical Insurance Bureau issued the "Administrative Punishment of Xiangya Hospital of Central South University", which fined the hospital about 980,000 yuan for illegal use of medical insurance funds.

CBN found that in recent years, the Regulations on the Supervision and Administration of the Use of Medical Insurance Funds (hereinafter referred to as the Administrative Regulations) and the Interim Measures for the Supervision and Administration of the Use of Medical Insurance Funds (hereinafter referred to as the Interim Measures) and other laws and regulations have been promulgated one after another, providing policy and legal basis for the supervision of medical insurance funds; As a complement to the Interim Measures, the Measures for Reporting Incentives for Illegal Use of Medical Insurance Funds (hereinafter referred to as the "Incentive Measures") was also released in November 2022. This document is to mobilize social forces to participate in fund supervision and safeguard the safety of medical insurance funds.

The National Medical Insurance Bureau has repeatedly stressed that the medical insurance fund will never become "Tang monk meat". According to official data, since 2019, the National Medical Insurance Bureau has sent a total of 184 flight inspection teams to inspect 384 designated medical institutions, and found that 4.35 billion yuan of related funds were used illegally. Since the implementation of the "Incentive Measures" in January this year, medical insurance departments at all levels across the country have verified and recovered the amount of medical insurance violations of 158 million yuan according to the clues reported by the masses.

An expert on medical insurance policy told CBN that with the increasing efforts to crack down on fraudulent medical insurance in China, blatant fraudulent medical insurance behaviors such as "fake patients", "fake services", "fake medical products" and "fake medical insurance expenses" have been effectively curbed, but some fraudulent medical insurance behaviors have also shifted from the front to the back, and gradually changed to behaviors such as excessive medical treatment and excessive fees. How to determine the boundary of excessive medical treatment and how to adopt scientific and accurate comprehensive management methods are the key points in the next stage.

The boundary of "excessive diagnosis and treatment"

According to the notification of Anhui Medical Insurance Bureau, Wuhu Medical Insurance Bureau has fully recovered the medical insurance fund illegally used by Wuhu Second Hospital according to the medical insurance service agreement signed by the hospital, and deducted the liquidated damages at 30%, interviewed the relevant person in charge of the hospital, and handed it over to the public security and health care departments for further verification. At the same time, the bureau has started the administrative punishment procedure in accordance with the Management Regulations.

"Medical insurance service agreements are handled in different ways, but most medical institutions deduct liquidated damages at a rate of 30%." A person in charge of the medical reform department of a health and wellness commission in the southern region told the reporter that in addition to the treatment method according to the medical insurance service agreement, in the administrative punishment procedure, the above-mentioned "Management Regulations" stipulates that illegal acts that cause losses to the medical insurance fund shall be ordered to return, and a fine of more than 1 time and less than 2 times shall be imposed.

Zhao Dahai, a professor at the School of International and Public Affairs of Shanghai Jiaotong University, told the First Financial Reporter that whether it is for medical institutions or medical staff, the end of over-diagnosis and treatment must bring economic returns to themselves and institutions (institutions also involve scale expansion), but in the final analysis, the supervision of medical insurance funds needs a set of strict, scientific and legally effective standards to judge and identify.

"For public hospitals, we can constantly correct their use of medical insurance funds by strengthening supervision, but private hospitals and pharmacies have certain commercial attributes, so we still need to rely on effective supervision methods when avoiding the risk of fraudulent insurance." Zhao Dahai said that in the next stage, health care and medical insurance departments can jointly promote the standardization and implementation of clinical diagnosis and treatment paths.

To this end, the person in charge of the medical insurance service department of a top-three hospital in Beijing said that at any time, medical institutions should never make profits by prescribing drugs and consumables without collecting the information of the insured. This is malicious fraud and insurance fraud, and it is also the bottom line problem. However, at this stage, it is not uncommon for medical institutions to occupy too much medical insurance funds by improving the accessibility of drugs and consumables.

"But whether this belongs to’ excessive diagnosis and treatment’ needs to be viewed objectively." The person in charge said that on the one hand, some innovative drugs are expensive but have great benefits to diseases, and doctors prescribe them for patients out of kindness. However, due to the annual update of the medical insurance catalogue, whether the innovative drugs are still within the scope of the medical insurance catalogue, whether the medical insurance limited payment ratio has been adjusted, and whether the patient’s area is applicable need further careful confirmation. On the other hand, the scope of medical insurance fund’s limited payment needs to refer to a number of matters, including the indications in the drug instructions and the reimbursement ratio of the insured’s location. "It is almost impossible for doctors to record all the contents and ensure that there are no mistakes. Therefore, it is imperative to introduce an information-assisted platform and do a good job in training."

Is there a solution to the problem that medical institutions illegally use medical insurance funds caused by "excessive diagnosis and treatment"?

Cai Haiqing, former director of the Treatment Protection Department of Jiangxi Provincial Medical Insurance Bureau, said that, first of all, it is necessary to solve the problem of how to identify "excessive diagnosis and treatment"; Secondly, with the comprehensive implementation of the reform of DRGs (Payment by Disease Diagnosis Group) and DIG (Payment by Disease Score), the problem of medical insurance payment currently facing the clinic is to solve the problem of "over-diagnosis and treatment" and to prevent possible insufficient diagnosis and treatment. "Insufficient diagnosis and treatment includes low-standard discharge, reducing necessary medical services and inspection items, and reducing the use of drugs and consumables. This situation is to reduce the cost of medical services and improve the yield."

As a matter of fact, the First Financial Reporter learned in the industry that it is difficult to identify, identify and dispose of over-medical treatment. In June this year, "Research on the Identification of Over-medical Treatment Behavior and the Regulation Rules of Medical Insurance" released the first "over-medical treatment index system". The theoretical basis of this system includes sampling data, written materials and written materials of fund supervision discussions of 121 designated medical insurance institutions in Shanghai. It involves 5 first-level indicators, 30 second-level indicators and 67 third-level indicators.

"Although the system is developed in the form of research, it is still some time before it is fully implemented, but at least it has broken the definition of the boundary of overtreatment." Cai Haiqing said.

Regulatory challenges

Since the beginning of this year, official website, the National Medical Insurance Bureau, has published 40 typical cases of fraudulent insurance in four phases. The illegal use of medical insurance funds includes: changing medical treatment items, falsely recording infusion drugs, treatment and inspection fees, forging materials, uploading false medication data, etc. Most of these cases were discovered by local medical insurance departments through active forms such as medical data verification in different places, big data screening and analysis, and on-site supervision and inspection.

On the basis of the previous vigorous rectification work, what are the challenges in the supervision of medical insurance funds and how to establish a long-term supervision mechanism?

To this end, Yu Changyong, an associate professor at the School of Public Administration of Zhongnan University of Economics and Law, told reporters that under the new situation, the new challenges of China’s medical insurance fund supervision can be interpreted from four aspects. First of all, after years of flight inspection and special work to combat fraud and insurance fraud, some "blatant" fraud and insurance fraud in the past have been effectively curbed, and the means of fraud and insurance fraud will be more subtle and the way of fraud will be more complicated.

Secondly, the overall level of medical insurance in various regions has been gradually improved, and the area where patients seek medical treatment has become larger, which will also significantly expand the scope of supervision of medical insurance funds and increase the difficulty of supervision. Thirdly, the reform of outpatient co-ordination makes the medical insurance department not only supervise the hospitalization behavior, but also supervise the outpatient behavior and the drug purchase behavior of pharmacies, and the objects and contents of supervision will show explosive growth.

In addition, the state attaches great importance to the development of Chinese medicine, and Chinese medicine services will be further included in the scope of medical insurance fund payment. However, Chinese medicine services are often treated by people and diseases, and its legal compliance or more difficult to judge, making it more difficult to supervise medical insurance funds.

To this end, Yu Changyong suggested that for some hidden and complicated illegal use of medical insurance funds, the medical insurance administrative department needs to be accurate and qualitative, and administer according to law; On the other hand, it is necessary to increase administrative punishment and even criminal punishment. In addition, it is necessary to strengthen the construction of intelligent monitoring and big data screening mechanisms, and establish a credit supervision system as soon as possible.

For the establishment of a long-term mechanism, a medical insurance fund supervisor said that in fact, in the past, the punishment for illegal use of medical insurance funds was mostly in medical institutions, and the punishment for individuals was not enough; At the same time, due to the low cost of violating laws and regulations, in most cases, it is ultimately handled in accordance with the medical insurance service agreement, and administrative punishment, transfer to justice or discipline inspection are rare.

"On the one hand, it is recommended that the medical insurance department unify the standards for law enforcement and incorporate illegal acts of medical institutions into credit management; On the other hand, medical institutions should establish the accountability system, reward and punishment system for the main leaders of the party and government and department heads, and improve the business training in the field of medical insurance payment. In addition, it is necessary to improve the comprehensive supervision mechanism that pays equal attention to incentives and constraints. Medical institutions that self-examine and self-correct and voluntarily return funds can reduce or not be punished. However, for those medical institutions and individuals who repeatedly check recidivism and do not change, they must be dealt with severely. " The source said.

Manchester City announced their home jerseys for the upcoming 2023-24 season.
Manchester City said on the club’s website on the 19th (Korea time), "Manchester City players are wearing home uniforms produced by Puma for the 2023-24 season. Manuel Akanji, Kevin De Bruyne, Jack Goreli, Erin Holland and Edersen are wearing them, "he said formally.
This set of jerseys is designed to commemorate the transfer to Etihad Stadium. Since 1923, Manchester City has used Main Road as its home for 80 years. But with the passage of time, problems such as aging appeared. In 2003, they moved to Etihad Stadium as their new home.
Manchester City said: "This move marks the beginning of a new era for the club, which is defined by new records, new legends and great moments." I was inspired by the giant turret. Even the details are hidden. On the back of the neckline of the jersey is written the postal code of Etihad Stadium, M11 3FF, with pictures of Etihad Stadium painted on it. It also has a white V-neck, inspired by the 2003-04 home jersey.
An atmosphere completely different from this season’s uniforms. The home jersey of Manchester City in 2022-23 season is set in sky blue, and the Manchester City team emblem is embedded in the center of the chest. The logo of the uniform manufacturer Puma is located below it, and you can see the letter of the sponsor Etihad below it.
However, in this home jersey, the club badge is located on the left chest and the Puma logo is located on the right chest. In addition, you can also see the horizontal stripes in the middle on the sky blue background.
Meanwhile, Manchester City are challenging the club’s first treble this season. If you win the upcoming Chelsea game alone in the Premier League (EPL), you will be able to confirm your third consecutive league title. In addition, in UEFA Champions League (UCL), we beat Real Madrid to enter the final and compete with Inter Milan for the New Year. In the FA Cup in England, they faced their arch-rival Manchester United.

Recently, Yan Ning, a famous structural biologist, announced that he would resign from Princeton University and set up the Academy of Medical Sciences in Shenzhen. In response to the latest research that she will focus on when she returns to China, she said that the discovery of structural biology is of great significance to the pharmaceutical industry, including the research on the interaction between drugs and hormones, which has more implications for drug development and disease treatment.

Yan Ning said, for example, that through the method of structural biology, scientists saw for the first time that two commonly used drugs used protein as a "scaffold", which directly "side by side" affected the normal function of protein.

Technological change promotes the development of structural biology.

Protein, as the scaffold and main substance of human tissues and organs, plays an important role in human life activities. In the cell, a large number of protein elements form the molecular machines, which performs important molecular processes in the cell through the interaction of protein, including the cell’s response to the external environment and the internal environment, and also forms a signal transduction network system with the interaction of protein as a link.

Structure By studying the three-dimensional structure, dynamic process and biological function of biological macromolecules, biology can provide more details of protein interaction and real-time dynamic process, thus helping scientists to understand molecular mechanism and explore the pathogenesis of diseases related to macromolecular dysfunction.

The development of biology not only contributes to the discovery of drugs, but also affects the research fields of life sciences including biochemistry, cell biology, genetic development, neurobiology, microbiology and pathopharmacology.

The development of science and technology has been promoting the progress of structural biology. In 2017, the Nobel Prize in Chemistry was awarded to cryoelectron microscopy, which can greatly improve the efficiency of analyzing the atomic resolution three-dimensional structure of large protein complexes; Moreover, researchers can freeze biomolecules in motion and visualize their motion process.

This breakthrough has brought a perfect storm to the field of structural biology. In recent years, important breakthroughs have been made in the field of life sciences. The work of China scientists such as Cheng Yifan, Shi Yigong, Yang Maojun and Liu Zhengfeng has also benefited from this technology. They have analyzed the important complex structure of atomic resolution. In addition, the enzyme that produces the protein that leads to Alzheimer’s syndrome was analyzed by cryomicroscope.

In August, 2015, Shi Yigong’s research team published an article in Nature, reporting the three-dimensional electron microscope structure of human γ -secretase with a resolution of 3.4 angstrom, and studying the function of the pathogenic mutant of γ -secretase based on the structure analysis, which provided an important foundation for understanding the working mechanism of γ -secretase and the pathogenesis of Alzheimer’s disease.

In February, 2020, after the outbreak of COVID-19, the research team of West Lake University successfully analyzed the full-length structure of novel coronavirus receptor ACE2 for the first time by using cryo-electron microscopy, which helped the research and development of drugs in COVID-19.

What does AI predict protein folding change?

With the help of artificial intelligence technology, DeepMind, a subsidiary of Google, recently announced 220 million kinds of protein structures predicted by AlphaFold software, which shocked the field of structural biology, because it indicates that artificial intelligence enterprises have begun to "truly hand over the power of Al to scientists all over the world".

Scientists compare the significance of this disruptive breakthrough with the human genome project. In the 1990s, when the Human Genome Project began to take shape, scientists realized that it was not enough to master the base arrangement of genes, but also to know the protein, the product of genes.

Shi Yigong, academician of China Academy of Sciences, structural biologist and president of West Lake University, commented on AlphaFold’s work: "Its accurate prediction of protein structure is the greatest contribution of artificial intelligence to the scientific field, and it is also one of the most important scientific breakthroughs made by mankind in the 21st century."

Shi Yigong once told China Business News: "AlphaFold represents the world’s leading artificial intelligence protein organization prediction system." At the same time, he said, China’s high-tech enterprises are catching up, expecting to bring surprises to the world in the near future.

He also said that the improvement of the accuracy of protein structure prediction will greatly benefit the pharmaceutical industry. "Artificial intelligence prediction of protein structure provides an important foundation for drug design and optimization. The structure of drug target proteins combined with all small molecule drugs can almost be wiped out by AlphaFold. " Shi Yigong said.

In the opinion of some scientists, although AlphaFold’s work is shocking, the accuracy of drug research and development prediction is not enough. Professor Liu Zhijie, executive director of iHuman Institute, Shanghai University of Science and Technology, told the First Financial Reporter: "It has been a long time to predict the protein structure. Now the accuracy of the prediction is definitely getting higher and higher, but it still hasn’t reached the precision of crystal structure."

Liu Zhijie First Financial News told the reporter that the crystal structure is the most accurate, and now artificial intelligence can predict the protein folding with the accuracy of electron microscope and nuclear magnetic resonance. In addition, because there are thousands of structures in protein, the difficulty of analysis is different. "If some protein sequences are similar to the known structure of artificial intelligence, it is easier to predict." Liu Zhijie said.

However, he still believes that with the continuous improvement of the prediction accuracy of protein folding, it will play a more important role in the field of life sciences in the future. "If the current prediction can reach the accuracy of electron microscope, some drugs can already be designed. Drug design is the biggest application field of artificial intelligence protein folding prediction." Said to Liu Zhijie First Financial Reporter.

Others think that with the development of artificial intelligence, there may not be so many structural biologists in the future. "Many researchers who do structural biology are actually more like technical service personnel. The more people there are, the more structures that can be analyzed. Therefore, in essence, a large part of their work depends on manpower. Now with AI, it is true that a large number of people who do structural biology have changed careers." A virus researcher told the First Financial News reporter.

However, for top structural biologists such as Shi Yigong, technology is only a powerful support for the "top brain", which can help them realize more ideas. "Every conscientious biologist should know how to make good use of the structural prediction of artificial intelligence." Shi Yigong said.

Professor Michael Levitt, winner of the Nobel Prize in Chemistry in 2013, told China Business News: "I think many structural biologists are not only doing structural research, but also doing a lot of work on protein function and drug research and development, just like Professor Yan Ning. Artificial intelligence only liberates a part of traditional manpower, but the progress of science still needs to rely on the smartest human brain. I’m afraid that artificial intelligence alone will not work. "

In recent years, a number of AI pharmaceutical companies have also been born in China. In this regard, Ewing Nan, academician of Chinese Academy of Sciences and president of Beijing Institute of Scientific Intelligence, pointed out to the First Financial Reporter: "The emergence of AI for Science research paradigm is an important historical opportunity for scientific and technological innovation, which not only expands the capability boundary of data-driven and physical model-driven models, but also is expected to promote the organic combination of the two, provide theoretical basis for further solving practical problems, and greatly narrow the distance between scientific research and practical application."