Standardized diagnosis and treatment center authentication assessment system based on AI diagnosis and treatment follow-up visit system

Abstract

The invention discloses a standardized diagnosis and treatment center authentication and examination system based on an AI diagnosis and treatment follow-up visit system, and the system comprises the steps: firstly inputting a medical record of a patient, selecting a scheme through a standardized AI decision, tracking and collecting an actual treatment scheme of the patient through a follow-up intelligent treatment follow-up visit system, and then comparing the actual treatment scheme with an AI decision scheme. According to the scheme, weights are compared and sorted in a unified manner, hospitals meeting an access threshold are sorted according to grades, and grade evaluation is completed according to illness state grading, so that automatic matching of patients and hospitals can be completed, the accuracy of patient hospital grading matching is improved, medical resources are effectively saved, the illness state triage working efficiency of the patients is improved, through the actual patient medication name and medication cycle obtained from the haixin AI standardized follow-up decision system and the medication prescription data packet obtained from the examination hospital operation platform, the corresponding hospital is automatically matched, and the matching efficiency is improved, so that a basis is provided for subsequent tumor industry standardized hospital department authentication.

Description

technical field [0001] The invention relates to the technical field of certification and assessment of standardized diagnosis and treatment centers, in particular to a standardized diagnosis and treatment center certification and assessment system based on an AI diagnosis and treatment follow-up system. Background technique [0002] Oncology, like internal medicine, surgery, obstetrics and gynecology, and pediatrics, is a secondary discipline of clinical medicine, divided into medical oncology, radiotherapy oncology, and surgical oncology. The Radiation Oncology Department is mainly engaged in radiation therapy for tumors. The Oncology Surgery Department provides comprehensive treatment based on surgery. The degree of standardized diagnosis and treatment in the tumor industry is relatively low. Patients do not have a unified understanding of the standardized diagnosis and treatment center. In the traditional cancer diagnosis and treatment process, doctors compare Analyze a s...

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Problems solved by technology

[0002] Oncology, like internal medicine, surgery, obstetrics and gynecology, and pediatrics, is a secondary discipline of clinical medicine, divided into medical oncology, radiotherapy oncology, and surgical oncology. The Radiation Oncology Department is mainly engaged in radiation therapy for tumors. The Oncology Surgery Department provides comprehensive treatment based on surgery. The degree of standardized diagnosis and treatment in the tumor industry is relatively low. Patients do not have a unified understanding of the standardized diagnosis and treatment center. In the traditional cancer diagnosis and treatment process, doctors compare Analyze a series of images of cases and rely on experience to predict the pathological degree of the patient's disease. This method requires professional doctors to perform cumbersome manual operations on a large amount of data. At the same time, the accuracy and reliability of the diagnostic results of this method are heavily dependent on the doctor's experience. Knowledge and professional quality, and the accuracy of diagnostic results are limited, and tumor patients need different treatment plans according to their disease stages, some need surgery, some need chemotherapy, and some need radiotherapy, and different disciplines Specialties are different, and at the same time, the experts in the diagnosis and treatment centers have different focuses, so it is impossible to judge which diagnosis and treatment center is most suitable for the patient according to the severity of the patient's condition. To maximize the allocation of medical resources, it is necessary to standardize the diagnosis and treatment level of the diagnosis and treatment center, and at the same time conduct a diagnosis and treatment level assessment to complete the ranking of target hospitals. For this reason, we propose a standardized diagnosis and treatment center certification assessment system based on the AI ​​diagnosis and treatment follow-up system

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