Medical record data processing method, apparatus and system

Abstract

The present invention relates to the technical field of clinical medicine, and particularly to a medical record processing method, apparatus and system. The method comprises: acquiring medical record data of a current patient; performing an operation on the medical record data by using a pre-established symptom stage model, wherein the symptom stage model is established in advance according to medical record data of multiple patients whose disease stage has been determined; determining a disease stage of the current patient according to a result of the operation; and displaying the disease stage of the current patient. According to the method, by means of the symptom stage model, the operation is performed on the medical record data of the current patient to determine the disease stage of the patient, so that the doctor only needs to directly acquire the medical data of the patient in clinical medical treatment and determine the disease stage of the patient, i.e. a development stage of the hand-foot-and-mouth disease by combining actual situations after seeing the displayed disease stage of the current patient, which reduces hand-foot-and-mouth disease condition delay in clinic.

Description

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AI Technical Summary

Benefits of technology

This patented technology allows for accurate analysis of diseases such as hepatitis or tuberculosis (TB) from electronic health records (EHR). It uses an algorithm called Difference Logging Regression Analysis ("DLR") to create models which are used during these processes. These models can be trained against new cases of certain types of illnesses over time through training data collected beforehand. By analyzing EHR data obtained at different stages of their evolution, it becomes possible to predict how well people will develop TB later when they start taking care medicine together. Overall, this approach helps physicians make informed decisions about preventive measures early enough while reducing delays caused by diagnosis.

Problems solved by technology

Clinicians face challenges when trying to determine if an illness such as acute chilblains syndrome affecting heartbeat could progress beyond what they already know about them until later. Current methods require extensive documentation from physician offices and involve physical observation by asking patients' names and signs over their entire lifetime. These techniques only help identify specific conditions based upon these observations alone, making timely identification crucial for effective treatments.

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