Unsupervised electronic medical record-based medical behavior compliance assessment method

Abstract

The invention discloses an unsupervised electronic medical record-based medical behavior compliance assessment method. The method comprises the following steps of S1, collecting, cleaning and preprocessing medical record data; S2, classifying the case data of the patient; S3, clustering the medical advice data of the patient; S4, fusing the medical advice data after the patient clustering and the operation data with the time sequence, and mining the diagnosis and treatment process model according to the patient category in combination with the effect after the diagnosis and treatment of the patient; S5, aligning the actual diagnosis and treatment sequence with the excavated diagnosis and treatment process model based on the cost function so as to position the position of the anomaly and calculate the deviation degree of the anomaly. The priori knowledge dependency is reduced, data can be deeply utilized, the clinical interpretability of the evaluation result is high, and the complexity of preset logic such as the illness state and the physical condition of the patient is high.

Description

technical field [0001] The invention relates to the field of medical data processing and analysis, in particular to an unsupervised electronic medical record-based medical behavior compliance evaluation method. Background technique [0002] In recent years, with the improvement of people's living standards, the development of the medical and health industry has also encountered many difficulties. On the one hand, medical expenses are increasing at a fairly rapid rate, and in the process of clinical diagnosis and treatment, due to the interference of interests of medical institutions, some patients have irrational clinical medical behaviors, which not only causes a waste of medical resources, but also Increase the economic burden of patients, and may even endanger the health of patients. On the other hand, in the process of clinical diagnosis and treatment, there are problems such as insufficient grasp of the intervention process and standards required by the guidelines, and...

AI Technical Summary

Problems solved by technology

[0005] Most of the existing technologies only use the information of the patient's charging items, and do not fully consider the patient's admission examination results, allergies, and doctor's orders, and the information utilization is not deep enough;

[0006] The existing technology does not consider the clinical value of each index, and the clinical interpretability of the evaluation results is insufficient;

[0007] Existing models overly consider the unity of the model and underestimate the differences in the condition and physical condition of different patients, resulting in low accuracy and poor adaptability. At the same time, the preset logic rules of the early warning system are mostly aimed at single diseases and simple clinical scenarios

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