Health medical data preprocessing method and system

Abstract

The invention discloses a health medical data preprocessing method and system. The method comprises the following steps: storing original physical examination data in a data frame form, storing physical examination information in a character string format, and generating a physical examination row table; deleting repeated physical examination data in the row table; setting a unique identity code for each physical examination person; if the physical examination number is missing, generating a unique physical examination number according to the unique identity code and the physical examination date; if the physical examination time is lost, supplementing the earliest physical examination time under the same physical examination to the position where the physical examination time is lost; taking the physical examination data within a certain time threshold under the same physical examination number as one time of physical examination; combining column names representing the names of the physical examination items in the physical examination data together through a first hyphen; combining the result, the reference range and the dimension of each physical examination item by using a second hyphen; and converting the physical examination data in the row table form into a list. According to the method, non-standard original data is normalized, and medical big data standard treatment work is facilitated.

Description

technical field [0001] The invention belongs to the technical field of data governance, and in particular relates to a method and system for preprocessing health and medical data. Background technique [0002] With the continuous advancement of medical informatization, the medical and health industry, with the support of big data technology, has great potential for efficient integration and adjustment of medical resources. However, in the real world, data often has problems such as incompleteness, complex structure, and redundant information. These low-quality data will make data governance more difficult, so a complete set of methods and processes for standardizing raw medical data is required. This will greatly improve the quality of data, the efficiency of data governance and the progress of medical data informatization. [0003] At present, the health big data industry is developing rapidly, but there is no process specification for the preprocessing of medical data. ...

AI Technical Summary

Problems solved by technology

Non-standard raw data will undoubtedly reduce the efficiency of data governance, including manual and machine algorithms

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