Automatic generation and execution method of clinical data quality assessment rules based on openEHR model

Abstract

The invention discloses an automatic generation and execution method of clinical data quality assessment rules based on an openEHR model. The method comprises the following steps: (1) establishing a mapping relationship between data quality constraint knowledge of each node in the openEHR model and the data quality assessment rules; (2) obtaining a used openEHR model, and analyzing the openEHR model into a JSON object in a fixed format; (3) processing each node in all openEHR models according to the mapping relation and the JSON object, and generating a data quality evaluation rule of a fixed structure; (4) processing the data quality evaluation rule to generate a rule execution configuration file; (5) deploying related information of the database to be evaluated in the Spark rule execution engine; and (6) according to the rule execution configuration file and the related information of the database to be accessed, enabling a Spark rule execution engine to execute the data quality evaluation rule by calling a function to obtain a data quality evaluation result.

Description

technical field [0001] The invention belongs to the technical field of electronic medical record data quality assessment, and in particular relates to an automatic generation and execution method of clinical data quality assessment rules based on an openEHR model. Background technique [0002] Health and medical big data is an important basic strategic resource of the country. Electronic medical records are one of the core databases, and the data stored in them are of great value to medical care, scientific research, and public health. However, the value of data is based on its "high quality" or "ready for research and use". my country's electronic medical records generally have quality problems such as missing, wrong, invalid, incomplete, and inconsistent, and these problems will directly affect the quality of the data. Apply effects. Data quality assessment can help data users find data quality problems so that they can take appropriate measures to improve data quality. It...

AI Technical Summary

Problems solved by technology

For this type of method, defining the rules applied to data is the starting point for implementing data quality assessment, which will directly affect the results of data quality assessment, and is also a time-consuming link that requires manual participation in the implementation of quality assessment

Most of the current assessment methods involve creating data quality queries and writing data quality assessment rules through Structured Query Language (SQL), but electronic medical records contain hundreds or even thousands of data items, and a data quality assessment task usually needs to run several Hundreds of rules, heavy workload, time-consuming and labor-intensive

[0004] Existing research uses the idea of ​​parameterization to define rules through structures such as variables, functions, and parameters, which simplifies the rule definition process. However, in practical applications, the parameters of each rule still need to be defined, which does not effectively solve the problem of heavy workload, time-consuming and labor-intensive process of defining rules. The problem

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