In the consultation room of a tertiary hospital in the Yangtze River Delta, 67 year old Aunt Li asked the doctor to issue a thyroid ultrasound examination form. The system automatically popped up a prompt: "You have completed thyroid function testing in the community hospital in the past 3 months, and this examination is a duplicate application." The doctor immediately withdrew the examination and suggested that priority be given to the results of the community examination. Behind this scene, the connection between medical insurance settlement data and hospital diagnosis and treatment data is playing a role. The relationship between medical insurance departments and medical institutions is often seen as an opposition between "regulation and being regulated". In some cases, medical insurance departments may overly rely on post audit to prevent fraud, while medical institutions may engage in improper medical behaviors such as splitting hospitalization and excessive examination to control costs and increase revenue. Nowadays, the medical insurance and healthcare system are shifting from passive linkage to active collaboration. The core password behind this shift lies in the flow and integration of massive amounts of data. Medical insurance data and medical institution data, one is the "medical security ledger" and the other is the "health diagnosis and treatment log". When the two break down barriers and deeply integrate, a two-way governance digital engine is formed, which not only strengthens the defense line for the safety of medical insurance funds, but also injects momentum into improving the quality and efficiency of medical services. Medical insurance data is a barometer of the medical needs of insured persons, which not only records basic information such as payment base, benefit enjoyment, and medical treatment trajectory of more than 1.3 billion insured persons, but also accumulates dynamic expenditure data such as diagnosis and treatment projects, drugs and consumables. Medical data is the microscope of diagnosis and treatment behavior, covering the entire process information such as electronic medical records, examination and testing reports, surgical records, medication trajectories, etc. It not only contains technical details of "how to treat diseases", but also implies behavioral patterns of "how patients see". For the medical insurance department, data is an important means of precise supervision. By integrating medical insurance settlement data, hospital information system data, and drug consumables traceability data, the medical insurance department can establish a full chain supervision system. For example, relying on the national medical insurance information platform, Zhejiang Province cross checked the historical medical records, drug inventory data, and real-time settlement information of insured persons. In the first half of 2024, 12000 suspicious clues such as "bed hanging hospitalization" and "false examination" were identified, recovering a fund loss of 230 million yuan. For medical institutions, timely access to medical insurance payment data, patient flow data, and drug usage data can optimize resource allocation more scientifically. However, in the past, data retrieval was one-way, meaning that the medical insurance department could grasp relevant information about medical institutions. However, the operation of the medical insurance fund and the comparison of data between medical institutions held by the medical insurance department were difficult for medical institutions to obtain, which was not conducive to improving service efficiency. In July 2024, the National Healthcare Security Administration issued a notice on the issuance of the 2.0 version of the grouping scheme based on disease groups and disease categories, and further promoted related work. It was proposed that various regions should establish medical insurance data working groups to further publicize the operation of medical insurance funds to the society, and regularly "reveal their wealth" to designated medical institutions, thus opening the curtain for the "two-way rush" of data. In March of this year, the medical insurance data working groups in various regions basically completed the first information release work. They not only analyzed the income and expenditure of medical insurance funds, fund settlement, medical institution service quality and efficiency data, but also organized data communication meetings to communicate the data analysis results face-to-face with designated medical institutions. At the same time, they collected opinions and suggestions from medical institutions on data analysis, medical insurance fund settlement, payment method reform, and other aspects. In Dalian, Liaoning Province, data sharing has helped hospitals bid farewell to the "experience based decision-making" model in terms of average hospitalization costs, the proportion of examinations, tests, and drugs, monthly cost changes, and the average cost structure of the same disease. The warning function of the intelligent monitoring system provides strong support for refined management; In Fuzhou, Fujian Province, through a data visualization application system, designated medical institutions can not only quickly obtain their own summary and analysis data, but also access various indicators of public medical insurance and horizontal analysis and statistical data of the institution. This enables hospitals to easily benchmark and identify differences, analyze reasons, and formulate accurate operational strategies. These practices demonstrate that deep collaboration starting from data connectivity is driving the governance model of medical insurance and healthcare institutions from "passive response" to "active empowerment". The ultimate goal of improving the supervision of medical insurance and the level of medical services is to benefit the insured. Believing in the two-way flow of relevant data and regular face-to-face communication between medical insurance and healthcare can promote medical insurance policies to be closer to clinical reality, medical behavior to be more in line with medical insurance laws, and enable the public to enjoy more efficient and warm medical services. (New Society)