Queue identification method and device applied to special disease clinical test

Abstract

The invention discloses a queue identification method and device applied to a special disease clinical test. The method comprises the following steps: based on a pre-established knowledge system of aspecial disease clinical test in-and-out standard, generating query information of the special disease clinical test in-and-out standard; acquiring electronic medical record data, and performing information analysis on the electronic medical record data to obtain special disease phenotype analysis information; and based on the special disease phenotypic analysis information and the query information of the special disease clinical test in-and-out standard, determining a special disease clinical test queue matched with the query information. According to the invention, the knowledge system of the special disease clinical test in-and-out standard is a system for expressing the special disease clinical test in-and-out standard by knowledge of computer recognizable information; the in-and-outstandard is automatically converted into the structured query language, the electronic medical record data can be directly processed, a subject meeting the special disease clinical test is obtained, the information conversion processing efficiency is improved, and the accuracy of the queue identification work of the clinical test is improved.

Description

technical field [0001] The invention relates to the technical field of information processing, in particular to a queue identification method and device applied to clinical trials of special diseases. Background technique [0002] In order to verify the effectiveness or superiority of new drugs or treatment regimens, different sizes of test populations need to be included in different clinical trial cycles. Special disease clinical trial cohort identification is to identify qualified subjects for clinical trials carried out in a certain disease field in medicine, so as to meet the recruitment needs of subjects in various stages of clinical trials. Based on the inclusion and exclusion criteria of clinical trials (also referred to as inclusion criteria for short), researchers match the acquired characteristics of potential subjects to identify whether they meet the criteria. [0003] The current common methods of acquiring subjects include publishing recruitment information, ...

AI Technical Summary

Problems solved by technology

It can be seen that there is still a lack of systematic research methods for the cohort identification of clinical trials for specific diseases

Especially when cohort identification is based on electronic medical record data, manual analysis is generally used to explain and convert the rules of clinical trial inclusion and exclusion criteria, and there is a lack of intelligent processing and application of unstructured electronic medical record data

As a result, the manual analysis method not only requires time-consuming and high-intensity labor by personnel with rich professional background, but also makes it difficult to guarantee the accuracy of the results. This method lacks universal applicability, which in turn makes the cohort of effective clinical trials for specific diseases less accurate and low processing efficiency

Images