Medical insurance data analysis method based on big data

A data analysis and big data technology, applied in data processing applications, healthcare informatics, patient care, etc., can solve problems such as inability to classify big data and establish effective medical insurance prediction models, so as to improve data accuracy and guarantee Accuracy and timeliness, the effect of good data integration

Pending Publication Date: 2019-08-16
王为光
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to solve the existing problem of not being able to classify big data according to requirements and establish an effective medical insurance prediction model, and propose a medical insurance data analysis method based on big data

Method used

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  • Medical insurance data analysis method based on big data
  • Medical insurance data analysis method based on big data
  • Medical insurance data analysis method based on big data

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0052] A method for analyzing medical insurance data based on big data, comprising the following steps;

[0053] S1. Organize medical insurance data in a certain area, including validity check, error data elimination and modification;

[0054] S2. Preliminary statistics, forming a preliminary understanding of the fluctuation law. Classify the electricity consumption data of different industries and regions, analyze the trend of the data curve according to the characteristics of different data, and combine the preliminary autocorrelation analysis to study the internal and external factors that lead to the irregular changes of major diseases and staged infectious diseases. When sorting out different data studies, integrate them according to monthly, quarterly and annual time spans;

[0055] S3. Construction of medical insurance data forecasting model, searching for forecasting models with high forecasting accuracy and goodness of fit by categories and scales, monthly, quarterly...

Embodiment 2

[0089] Embodiment 2: Based on Embodiment 1 but different;

[0090] Monthly forecast error of medical insurance in a certain area

[0091]

[0092] Quarterly forecast error of medical insurance in a certain area

[0093]

[0094] Annual forecast error of medical insurance in a certain area

[0095]

[0096] Through the representative models in the model library, the medical insurance data in a certain area are fitted and predicted. The results show that choosing the ARIMA model for monthly and quarterly data can get better prediction results. For annual data, choosing the gray system model can get better prediction results. prediction results.

Embodiment 3

[0097] Embodiment 3: based on embodiment 1 and 2 but different;

[0098] Through the analysis of the medical insurance situation of various population groups in this area, a population classification method based on monthly medical insurance sequence clustering is proposed. The analysis results of various influencing factors show that the classification results obtained by this classification method are stable and reliable. Based on the classification results obtained, this study analyzes the proportion of medical insurance among various groups of people and the impact of medical insurance fluctuations, and selects 10 specific groups in three categories as the key medical insurance groups. These 10 groups have the largest proportion of medical insurance among all groups, and at the same time have the greatest impact on the fluctuation of the overall medical insurance. Based on the classification of medical insurance groups, a prediction model of medical insurance demand by po...

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Abstract

The invention discloses a medical insurance data analysis method based on big data, and belongs to the field of medical insurance data analysis. A model is established and analyzed; it is found that all indexes of macroeconomy have a large influence on the prediction precision of the models; the crowd classification medical insurance of this research only occupies a small part of the medical insurance data from the aspects of data dimension and data scale, and the analysis and research of future medical insurance big data must be wider in data range, larger in data volume and deeply combined with macroeconomic indexes. The medical insurance big data technology and application of the invention are mainly in the following three aspects. The development of metering automation equipment technology and the improvement of information system level are realized. The development of metering automation equipment can collect information in a multi-dimensional mode, meanwhile, the accuracy and timeliness of information collection can be guaranteed, and better data integration, storage and statistics can be brought by the development of an information system.

Description

technical field [0001] The invention relates to the field of medical insurance data analysis, in particular to a method for analyzing medical insurance data based on big data. Background technique [0002] Medical insurance refers to social medical insurance. Social medical insurance is a social insurance system established by the state and society in accordance with certain laws and regulations to provide basic medical needs protection for workers within the scope of protection in case of illness. The basic medical insurance fund consists of pooling funds and individual accounts. The basic medical insurance premiums paid by individual employees are all included in personal accounts; the basic medical insurance premiums paid by employers are divided into two parts, one part is transferred to the personal account, and the other part is used to establish a pooling fund. [0003] The medical insurance industry classification and medical insurance demand prediction modeling an...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q40/08G16H10/00G06Q10/04
CPCG06Q10/04G06Q40/08G16H10/00
Inventor 王为光
Owner 王为光
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