Research And Implementation Of Intelligent Clinical Decision Support Platform For Hypertension

Currently,the incidence of hypertension in China is continuously increasing,and the overall level of prevention and treatment is relatively low,especially in primary medical institutions where clinical service capabilities are weak.With the rapid development of medical information technology,clinical decision support systems(CDSS)have been widely applied.Studies have shown that the application of CDSS in hypertension community management can improve treatment effectiveness.Therefore,research on CDSS for hypertension can help improve the service capabilities of primary medical institutions.Although research and applications of CDSS have covered multiple disease domains,there are still deficiencies and challenges in the field of hypertension.Specifically,practical issues in the hypertension diagnosis and management process have not been fully considered:first,the problem of pre-diagnosis medical records automatic collection,where most systems have not fully considered the efficiency and quality of hypertension medical record information collection;second,the problem of medication assisted decision during diagnosis,where case-based reasoning technology is still inadequate in hypertension medication decision research,and an increase in cases can lead to decreased retrieval efficiency;third,the problem of post-diagnosis intelligent monitoring management,where traditional systems have not focused on the relationship between disease condition and monitoring frequency,and lack personalized monitoring management mechanisms.To address these issues,this paper will conduct in-depth research and implementation of an intelligent CDSS platform for hypertension.It aims to provide technical support for the informationization and intelligence of the hypertension patient diagnosis and management process.The research content includes three innovation points and a system platform as follows:(1)Design a hypertension pre-diagnosis method based on human-computer dialogue,which automatically collects patient medical record information through multi-round dialogue and form filling to ensure medical record quality,and to support the doctor’s formal diagnosis.Additionally,a knowledge question-and-answer function will be provided to help patients better understand and manage their condition.(2)Research a hypertension clinical medication decision model based on case-based reasoning and attribute graph.By querying the medication case graph to find similar patients’ medication plans and recommending them to doctors for assisted decision,the retrieval of similar cases is transformed into a graph query to improve retrieval efficiency and accuracy.(3)Propose a personalized monitoring mechanism for hypertension that combines cardiovascular risk levels.Based on the patient’s risk level,personalized monitoring tasks will be formulated,and monitoring frequency will be intelligently adjusted when the condition changes,providing real-time feedback to doctors to prevent disease deterioration.(4)Implement an intelligent CDSS platform for hypertension,which can provide full-process services for patient diagnosis and management and assist doctors in making accurate decisions.This platform has been pilot-tested at the Beijing Anzhen Hospital of the Capital Medical University and the community hospital of the Beijing General Institute of the Nonferrous Metal Research,serving over 400 people and providing stable platform services and a good interactive interface.