Auxiliary decision-making system and method based on clinical path

Abstract

The invention relates to an auxiliary decision-making system and method based on a clinical path. The method comprises the following steps: adaptively correcting a clinical path preset model of a userin a clinical path model library according to a personal diagnosis result of the user so as to form a clinical path actual model for the current diagnosis of the user; then forming a recommended treatment scheme for the personal diagnosis and treatment of the user according to the formed clinical path actual model, and updating the personal data in the personal data module according to the treatment effect while performing rehabilitation treatment on the user according to the recommended treatment scheme; and meanwhile, optimizing the clinical path preset model in the clinical path model library is optimized, so that timely, effective, accurate and rapid corresponding rehabilitation treatment is carried out according to the personal data and the diagnosis result of each patient, and timely and effective feedback optimization is carried out in the rehabilitation treatment process and after the completion, and therefore the rehabilitation treatment efficiency and accuracy are further improved.

Description

technical field [0001] The invention belongs to the technical field of clinical medical decision-making, and in particular relates to an auxiliary decision-making system and method based on a clinical path. Background technique [0002] With the continuous development of today's social economy, people's neglect of their own resistance, the outbreak of various new infectious diseases, and the gradual aging of the population, the number of users who come to the hospital for medical treatment is gradually increasing, and each doctor needs to receive continuous patients. It is impossible to know the personal data and past medical history of each patient, so it takes time for doctors to understand the personal data and past medical history of each patient, which increases the working time for accurate diagnosis of patients. Reduced work efficiency; at the same time, when making the latest diagnosis results, it is necessary to re-draft the diagnosis documents, lack of necessary hi...

AI Technical Summary

Problems solved by technology

[0002] With the continuous development of today's social economy, people's neglect of their own resistance, the outbreak of various new infectious diseases, and the gradual aging of the population, the number of users who come to the hospital for medical treatment is gradually increasing, and each doctor needs to receive continuous patients. It is impossible to know the personal data and past medical history of each patient, so it takes time for doctors to understand the personal data and past medical history of each patient, which increases the working time for accurate diagnosis of patients. Reduced work efficiency; at the same time, when making the latest diagnosis results, it is necessary to re-draft the diagnosis documents, lack of necessary historical reference, and cannot make a timely, effective, accurate and rapid corresponding diagnosis for each patient

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