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臨床決策支援系統之介紹:以急性腎損傷照護為例

Introduction to the Clinical Decision Support System: Taking the nursing of acute kidney injury as an example

摘要


本文旨在介紹臨床決策支援系統(Clinical Decision Support System,簡稱CDSS)護理上的應用,CDSS是使用人工智能(AI)資訊系統,通過快速性和準確性來提高醫療品質,從病人的病歷中識別關鍵訊息,找到相對應的可能問題,以提出適當的診斷和治療指引,在國外被應用於護理診斷的精確度、血糖管理、輸血管理、預防壓瘡、靜脈血栓栓塞等。優點是能有效降低醫療錯誤,提高醫護人員的自主性及自我效能,增加護理角色的認同,提升員工士氣和團隊合作。本院藉由導入急性腎損傷(Acute Kidney Injury,簡稱AKI) 的資訊化護理活動,提供護理人員及時且正確的評估,引導其建立相對應的健康問題,並提供以實證為基礎的護理措施,以期發展疾病進展預測模式,改善急性腎損傷病人的嚴重度及不可逆的惡化結果。建議在導入CDSS資訊化設計之前,應先進行跨部門的整合與溝通協調,方能規劃出更完善、更人性化的CDSS,彰顯智能化系統在臨床護理應用的效益,提升醫療照護的成效與價值。

並列摘要


This study aims to introduce the clinical decision support system (CDSS) in nursing. CDSS uses an artificial intelligence information system to improve medical quality through rapidity and accuracy, identifies critical information from patients' medical records, determines corresponding possible problems, and puts forward appropriate diagnosis and treatment guidance. The system has been applied abroad to various fields, such as the accuracy of nursing diagnoses, blood glucose management, blood transfusion management, and the prevention of pressure ulcers, venous thromboembolism, and acute kidney injury (AKI). The advantages of this support system are that it can effectively reduce medical errors, improve the autonomy and self-efficacy of medical staff, increase the recognition of role identity, and enhance staff morale and teamwork. By introducing the nursing activities of AKI, as based on the collected information, our hospital provides timely and accurate assessment to nursing staff and guides them in identifying the correct health problems. Our hospital provides evidence-based nursing measures, with the expectation of developing a prediction model for disease progression and reducing the severity and irreversible deterioration of patients with AKI. It is suggested that before the introduction of the CDSS information design, cross-department integration, communication, and coordination should be carried out to plan a more comprehensive and user-friendly CDSS. By improving the efficiency of intelligent systems in clinical nursing applications, the effectiveness and value of medical care can be increased.

參考文獻


Aitken, E., Carruthers, C., Gall, L., Kerr, l., Geddes, C., Kingsmore, D. (2013). Acute kidney injury: Outcomes and quality of care, An International Journal of Medicine, 106, 323-332. doi:10.1093/qimed /hcs237.
Al-Jaghbeer, M., Dealmeida, D., Bilderback, A., Ambrosino, R., Kellum, J. A. (2018). Clinical decision support for in-hospital AKI. Journal of the American Society of Nephrology, 29; 654–660, doi: https://doi.org/10.1681/ASN. 2017070765
Ancker, J. S., Edwards, A., Nosal, S., Hauser, D., Mauer, E., Kaushal, R. (2017). Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system. BMC Medical Informatics and Decision Making, 17-36, DOI:10.1186/s12911-017-0430-8
Bagshaw, S. M. (2015). Acute Kidney Injury Care Bundles. Nephron, 131, 247–251, doi: 10.1159/000437152
Bataineh, A., Dealmeida, D., Bilderback, A., Ambrosino, R., Al-Jaghbeer, M. J., Fuhrman, D. Y., Kellum, J. A. (2020). Sustained effects of a clinical decision support system for acute kidney injury, Nephrol Dial Transplant, 35; 1819–1821, doi:10.1093/ndt/gfaa099

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