Intelligent big data analysis method and system for drug group purchase

Abstract

The invention discloses an intelligent big data analysis method for drug group purchase, and the method comprises the steps: carrying out the standardization processing of obtained drug purchase data, and matching and associating the classification information of all drugs; constructing a functional model, and forming a multifunctional comprehensive big data model through cross correlation of common dimensions; enabling a visual intelligent analysis platform to issue contents and indexes of the functional model through the cloud according to the application scene and the user permission. The invention further provides an intelligent big data analysis system for drug group purchase. According to the invention, the intelligent big data analysis system for drug group purchase is established, so that the supervision department can be assisted in mastering the purchase condition of a medical institution, a GPO catalog, national collection and national chat, prevention and control of stored drugs and decrease and saving of the purchase amount of drugs with various classification attributes in real time, and the supervision department can be helped to better manage and control the purchase behavior, and the medical insurance fund can be better utilized.

Description

technical field [0001] The invention relates to the technical field of big data analysis, in particular to an intelligent big data analysis method and system for drug group procurement. Background technique [0002] The procurement mode operated by the GPO group procurement organization has been in operation across the country for several years, and in recent years, various regions have also started it one after another. At present, the Shenzhen mode is the most influential in the promotion of the domestic GPO mode. GPO is to strengthen the bargaining power of upstream suppliers (drugs, medical devices, and other medical services) by concentrating the procurement needs of various downstream medical institutions, so as to obtain greater discounts for medical institutions and reduce procurement costs. Therefore, the quantity-based procurement of medicines is the key to the GPO model. There are hundreds of thousands of medicines on the market in my country. Shenzhen GPO integra...

AI Technical Summary

Problems solved by technology

[0004] However, before the regional GPO was launched, the data sources of various medical institutions were diverse and the content was complex. The original method was to first standardize the messy data of medical institutions in EXCEL, and then unify the common name of the catalog, catalog dosage forms, standard specifications, standard manufacturers, and The standardized procurement data of the GPO procurement platform is matched according to the unique catalog matching principle. The amount of data in each region and time period can reach hundreds of thousands. After manual standardized catalog matching, it may take two to three weeks, and Different time periods, different regions, different medical institutions, different drug catalog batches, and different platform data. This kind of work can only be repeated again and again. The previous decline results can only be registered in the form of accounting. When year-end summary is required, overlap It is very troublesome to deal with the decrease in time period, and the error rate is high

For two or three regions, the decline calculation may still be handled manually. With the implementation of the GPO’s cross-regional group procurement, 21 regions have joined, and the original working method cannot meet the needs of the local medical insurance bureaus for the decline calculation.

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