Data expansion:
DIP refers to the total budget paid by region and by disease. It uses fuzzy mathematics to solve the payment problem of medical insurance, including payment by disease and comprehensive budget management. This payment method binds the interests of all medical institutions in the overall planning area, so that medical institutions can be combined into a "destiny" and supervise and restrict each other.
In June 5438+ 10 and June 5438+065438+ 10, 2020, the Office of the National Medical Security Bureau successively promulgated the Pilot Work Plan of Regional Point Method Total Budget and Divided Payment by Disease, and the National Medical Security Divided Payment by Disease (DIP) and DIP Disease Directory Database (1).
A new round of pilot reform of payment methods was launched, and the national 7/kloc-0 pilot cities were determined for the first time. This means that DIP has become the main payment method in parallel with the reform of DRG payment method.
Under the general budget mechanism, the score is calculated according to the total annual medical insurance payment, the proportion of medical insurance payment and the total number of cases in each medical institution. The medical insurance department forms the payment standard according to the disease score and the integral score, realizes the standardized payment of each case of medical institutions, and no longer pays the medical service project fees.
The basic grouping path and principle of DIP is based on the grouping of real cases, the principle of similar disease diagnosis and clinical process, and the objective combination formed by big data clustering according to the classification and coding of disease diagnosis and surgery, which is not much different from clinical practice;
At the same time, DIP truly reflects the changes of clinical diseases with full sample data, which can form a dynamic response with the development of clinical technology and support the development of medical and health industry and hospitals.
DIP grouping results are finer and the joining rate is higher. DIP big data method forms a natural grouping by comparing all sample data, takes the critical value of the number of cases as the middle number, directly regards diseases above the critical value as the core diseases, * * * statistically exceeds 14000 groups, and DIP below the critical value re-clusters to form comprehensive diseases to meet the needs of clinical cases.
DIP is compatible with clinical medical record data, and the enrollment rate of all sample data is close to 99%, which reduces the number of unincorporated cases, reduces the uncertainty risk caused by unincorporated cases, and realizes the balance between convenient operation and fine application.
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