照護歷程分析技術－－以缺血性中風為例

Clinical Pathway Similarity Analytic Techniques-Ischemic Stroke Clinical Application

腦中風是全世界第三大死因，在美國，每年大都有550,000人遭受此疾病侵襲，更有超過三分之一（約5,000,000多人次）病患產生了永久性的失能（殘廢、癱瘓等），使得腦中風之疾病照護所造成的財務負擔，遠超過冠狀動脈心臟病及癌症（前兩大死因）之照護資源消耗。在台灣，依據健保局2011年統計，急性腦血管疾病花費的住院醫療費用佔前10大死亡疾病的4.9％，排名第五。本研究目的在建構一套缺血性中風分群比對系統，開發個人化（就醫➝出院）照護歷程分析推估技術，使用缺血型中風住院個案住院與門急診資訊602筆共1150維度（量表資訊32維及醫令1118維）之資料進行演算法驗證。統計NIHSS各級距間實際案例之正確預估準確率，其中以輕微中風及中度中風族群之分群結果驗測準確度達80％，期望此系統能有效提升及增進醫院端醫療品質及照護介入之醫療資源管理配置。

Cerebrovascular accident (CVA) or stroke is the third leading cause of death globally. In the United States, approximately 550,000 people suffered by brain attack strikes each year and more than 30% of patients had permanent disabilities. The financial burden caused by stroke has been far more than coronary heart disease and cancer (the top two causes of death). In Taiwan, according to the report from National Health Insurance Administration (NHIA) in 2011, the hospital medical expenses for acute cerebrovascular diseases was the fifth (4.9%) of the top 10 causes of death. This study is aimed to developed a prototype classification system from ischemic stroke patients utilized the clinical pathway similarity analytic techniques. In our study used the 602 patient data records and 1,150 variables (32 by medical scales and 1,118 by clinical orders), the evaluation result has achieved the 80% accuracy rate by using the hospitalized cases and emergency department information. In future studies the application should be applied in clinical practice, and we hold that can expect the increased usage of acute wards and decrease the cost of medical expenses.