An analytical method for calculating the incidence of rare diseases based on medical insurance big data

Abstract

The invention discloses a method for measuring and calculating the incidence of rare diseases based on medical insurance big data, which involves medical insurance data processing and analysis technology. The calculated diseases cannot be completely cured, and once diagnosed, they will suffer for life. By summarizing multiple key parameters of monthly medical insurance data, the numerator and denominator information required for the calculation of the incidence rate is obtained, and then the incidence rate is calculated; the required numerator is the number of new cases of the target disease in a certain range of people within a specific time; the required The denominator is the number of exposed population within a certain period of time, that is, people who may develop the target disease, and it is necessary to exclude people who are already sick and are unlikely to become new cases within a certain period of time. The method of the invention can obtain the incidence data of rare diseases, promote the development of epidemiological research on rare diseases, provide data and technical support for the rational formulation of clinical guidelines; further promote the transformation and application of medical insurance big data, and fill the epidemiology of rare diseases in my country blank data.

Description

technical field [0001] The invention relates to medical insurance data processing and analysis technology, in particular to an analysis method for calculating the incidence of rare diseases (Incidence) based on medical insurance big data. Background technique [0002] Rare diseases refer to a class of rare diseases with very low prevalence and incidence. At present, my country lacks information on the basic epidemic characteristics of such diseases, including incidence and prevalence. Medical insurance data (Claims data) is generally the data formed through the integration of payment information in the medical insurance administrative management system, including the basic characteristics of the insured, diagnosis, treatment and other information. Low, high operability, and longitudinal data from the real world, which is conducive to rapid and efficient epidemiological research, especially the use of national medical insurance data to provide new insights into the lack of rar...

AI Technical Summary

Problems solved by technology

In the current foreign analysis methods for the incidence of rare diseases, Raghu G and other scholars use the US Medicare medical insurance data to calculate the incidence of idiopathic pulmonary fibrosis during 2001-2011, but the calculation of these incidence rates is based on the medical insurance data. For my country's massive medical insurance data, regardless of the period, format and volume of data storage, or the span, absence, and individual out-of-insurance of data indicators, they are all different from foreign medical insurance data, so the above method cannot be directly used. In the epidemiological research of my country's medical insurance database; and looking at the research on the use of medical insurance data in China, it is found that most of them are currently focused on discovering fraud by mining medical insurance data, improving disease treatment effects, and assisting policy revisions. Data epidemiology, especially the research on the incidence and prevalence of rare diseases, makes it difficult to make full use of medical insurance big data to analyze the relevant epidemiological characteristics of rare diseases

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