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    智能慢病管理系統CDSS系統

    2023-04-17
    http://m.daycoding.com/
    原創
    130
    摘要: 慢病CDSS是針對慢病的防、診、治、管、健一體的全流程慢病智能決策支持平臺,有效整合臨床醫學知識、專家經驗及深度學習模型,能夠輔助醫生
    慢病CDSS是針對慢病的防、診、治、管、健一體的全流程慢病智能決策支持平臺,有效整合臨床醫學知識、專家經驗及深度學習模型,能夠輔助醫生對慢病患者進行全流程管控,提升診療水平及效率,提升居民健康水平,合理降低醫保費用
    Chronic disease CDSS is a comprehensive intelligent decision support platform for the prevention, diagnosis, treatment, management, and health of chronic diseases. It effectively integrates clinical medical knowledge, expert experience, and deep learning models to assist doctors in controlling chronic disease patients throughout the entire process, improving diagnosis and treatment levels and efficiency, improving residents' health levels, and reasonably reducing medical insurance costs
    功能介紹
    Function Introduction
    轉診建議
    Referral suggestions
    自動抓取病史及檢查檢驗信息,智能識別基層處置范圍之外的慢病并發癥等危重情況,并推薦出轉診信息,提示基層醫生進行迅速合理的向上轉診操作
    Automatically capture medical history and examination and testing information, intelligently identify critical situations such as chronic disease complications outside the scope of grassroots treatment, and recommend referral information, prompting grassroots doctors to quickly and reasonably carry out upward referral operations
    輔助診斷
    Auxiliary diagnosis
    基于大專家臨床經驗和大量臨床診療數據結合的深度學習模型,針對患者病史,智能推出診斷提示,圈定疑似疾病,輔助醫生進行精細化診斷
    Based on the clinical experience of major experts and a large amount of clinical diagnosis and treatment data, a deep learning model is developed to intelligently launch diagnostic prompts for patients' medical history, delineate suspected diseases, and assist doctors in fine diagnosis
    合理性建議
    Reasonable suggestions
    根據患者病情給出個性化檢查檢驗建議,提升檢查檢驗項目的合理性
    Provide personalized examination and testing suggestions based on the patient's condition to enhance the rationality of examination and testing items
    慢病管理平臺系統
    病情嚴重程度評估
    Assessment of the severity of the condition
    自動獲取評估信息,在醫生有需要時提供標準化疾病評估路徑,幫助醫生更好地進行病情分層
    Automatically obtain assessment information and provide standardized disease assessment pathways when needed by doctors, helping them better stratify their conditions
    治療方案推薦
    Recommended treatment plan
    基于臨床指南診療路徑,自動融合患者病情體征,及用藥史、過敏史、既往史等信息,個體化給出專病治療方案建議,輔助醫生進行個體化治療
    Based on clinical guidelines for diagnosis and treatment pathways, automatically integrate patient's condition and physical signs, as well as medication history, allergy history, past history, and other information, provide personalized recommendations for specialized disease treatment plans, and assist doctors in personalized treatment
    個體化健康處方
    Individualized health prescription
    根據患者的慢病分級評估結果,智能推薦患者的個體化管理方案,包括隨訪、用藥、運動、飲食、健康教育內容
    Based on the patient's chronic disease grading evaluation results, intelligently recommend personalized management plans for patients, including follow-up, medication, exercise, diet, and health education content
    智能隨訪管理
    Intelligent follow-up management
    用戶個體化方案確定后,會自動生成隨訪任務,可以在患者列表,患者管理首頁以及隨訪任務列表,進入隨訪上報管理。支持隨訪異常提示和隨訪記錄查看。
    After the user personalization plan is determined, follow-up tasks will be automatically generated, which can be accessed in the patient list, patient management homepage, and follow-up task list to enter follow-up report management. Support for abnormal follow-up prompts and viewing follow-up records.
    統計報表
    Statistical report
    體系化慢病管理統計報表,可支持當前慢病系統中患者總人數、各病種人數以及占比、各病種不同病情等級患者比例、各病種管控率和達標率
    Systematic chronic disease management statistical report, which can support the total number of patients in the current chronic disease system, the number and proportion of each disease type, the proportion of patients with different disease levels, the control rate and compliance rate of each disease type
    產品優勢
    Product advantages
    慢病管理新模式
    New mode of chronic disease management
    以數據智能服務+家庭可穿戴設備為依托,線上線下聯動,實現智能化全流程管控,構建“三師共管”的慢病管理新模式
    Relying on data intelligence services and home wearable devices, with online and offline linkage, achieving intelligent full process control, and building a new model of chronic disease management with "three teachers' joint management"
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