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Method for establishing medical consultation fee lattice model based on big data analysis

A technology of dot matrix model and big data, applied in the direction of electrical digital data processing, special data processing applications, instruments, etc., can solve the problems of wasting medical resources, irresponsible people's health, etc., and achieve the effect of reasonable charges

Inactive Publication Date: 2017-01-11
CHENGDU UNIV OF TRADITIONAL CHINESE MEDICINE
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

Doctors' random inspections and prescribing medicines not only hurt people's wallets, but also waste our country's limited medical resources, and are also irresponsible for people's health.

Method used

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  • Method for establishing medical consultation fee lattice model based on big data analysis
  • Method for establishing medical consultation fee lattice model based on big data analysis
  • Method for establishing medical consultation fee lattice model based on big data analysis

Examples

Experimental program
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Effect test

Embodiment 1

[0035] The method for establishing a lattice model of medical consultation expenses based on big data analysis comprises the following steps:

[0036] Step 1. Obtain the data in the original cost table; the patient ID, each charge item, and the record value of the charge item amount;

[0037] Step 2, data preprocessing: convert the recorded value of the amount of each charging item in the original cost table into a quantified value, then calculate the sum of the quantified values ​​of the same charging item for the same patient, and store the processed data in Quantized value table. For example, there is an irregularity in the record value in the original cost table, such as "35 yuan", so this step converts "35 yuan" into a quantitative value "35".

[0038] Step 3, clustering and analyzing the preprocessed data by using the distance-based multi-indicator abnormal data mining technology to dig out the noise points in the data records.

[0039] Further, step 4 is also included...

Embodiment 2

[0054] In this embodiment, the medical consultation fee for epigastric pain is taken as an example to describe the present invention in detail.

[0055] Obtain the data in the original expense table of epigastric pain patients of a certain age in a certain period of time; convert the recorded value of the amount of each charge item in the original expense table into a quantified value, and then quantify the same charge item for the same patient Values ​​are summed and calculated, and the processed data is stored in the quantitative value table, the header of the quantitative value table includes the patient ID and the name of each charging item; for example figure 1 Quantified value table of epigastric pain consultation fee shown;

[0056] Convert the quantized value in the quantized value table to utility value, get as figure 2 As shown in the utility value table, the header of the utility value table includes the patient ID and the name of each charging item; then scan the...

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Abstract

The invention relates to a method for establishing a medical consultation fee lattice model based on big data analysis. The method comprises the following steps: step 1, acquiring data in a fee original table; step 2, pre-processing the data: converting recorded values of all charging items in the fee original table into quantification values; carrying out summation calculation on the quantification values of a same charging item of one patient, and storing processed data into a quantification value table; step 3, carrying out cluster analysis on the pre-processed data by adopting a multi-index abnormal data digging technology based on a distance, and digging out noise points in data records. According to the method provided by the invention, rare data is digged out through establishing the model aiming at medical consultation fees to carry out data analysis, and abnormal behaviors of off-group points are researched; various types of disease symptoms, treatment items accepted by people, prescription drugs and charging are analyzed; item points with abnormal charging are found out and reference is provided for clinical drug of doctors and reasonable charging, so that the doctors are supervised and urged to insist on reasonable drug administration, reasonable checking, reasonable treatment and reasonable charging.

Description

technical field [0001] The invention relates to the technical field of diagnosis fee abnormality detection, in particular to a method for establishing a medical diagnosis fee lattice model based on big data analysis. Background technique [0002] Nowadays, people have a lot of criticisms about the medical system, especially problems such as random inspections and random prescriptions. Doctors' random inspections and random prescriptions not only hurt people's wallets, but also waste our country's limited medical resources, and are also irresponsible for people's health. Effective, timely and comprehensive monitoring of medical expenses is a hot issue that patients, hospitals, and management departments are concerned about. It directly affects the quality of medical care and the development of medical health. Timely, effective and comprehensive monitoring and management will help improve the supervision mechanism and contribute to the establishment of an effective The hospit...

Claims

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Application Information

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IPC IPC(8): G06F19/00
Inventor 温川飙程小恩贾帅
Owner CHENGDU UNIV OF TRADITIONAL CHINESE MEDICINE
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