| 摘要: | 目的：由於癲癇症是一種反覆發作的慢性疾病，其治療是漫長的過程，臨床上常見患者，因疾病的進展或控制不好而反覆癲癇症發作，經常住院接受治療，不僅是加重患者本身的負擔，同時家人的生活品質亦深受衝擊，醫療及社會成本的負擔增加，本研究則是希望了解患者出院後再住院之相關影響因素，找出潛在的非計劃性再住院的風險，期能將研究結果運用在臨床照護與管理，來預防非計劃性再住院的發生，提升醫療品質。方法：本研究採病歷回溯研究法，研究對象為台灣南部某醫學中心，診斷為癲癇症，時間於2012年01月至2013年12月之初次住院之患者，收取有效樣本資料共332位。統計方法包括：百分比、平均數及標準差等描述性統計，及Chi-Square、邏輯式回歸分析等進行推論性統計。結果：研究結果顯示再住院病人平均年齡約56.9歲，國中以下學歷、和家人同住最多、癲癇症病患非計劃性再入院率為34.9％（674/6725），進一步以邏輯斯迴歸分析，發現非計劃性再入院之預測因子為：入院原因－器質性腦疾病、代謝性及藥物引起的癲癇症、誘發因素、本次入院時意識評估、入院時心率評估、入院時是否有支持性管路留置、入院時成人營養評估、入院時體重是否合乎理想、入院時日常活動能力評估、入院時是否有介入出院準備服務計劃、出院時意識狀況、在出院時活動力評估皆為影響出院後一年內非計劃再住院者之預測因子。結論：減少未來的非計劃性再住院率將取決於獲得一個更好的了解再入院的原因和誘發因素。本研究所獲得之結果不僅可以進一步提供臨床護師對癲癇症病患之照護處置更?迅速而嚴謹，也更清楚的詮釋了癲癇症非計劃性再入院之相關危險因子。未來將能規劃完整的利用電腦資訊工具建構自動化的癲癇症照護模式之評估監測系統，以降低非計劃性再入院的情形 將是建立癲癇症症患者照護模式中之重要介入方針。
Objective:Epilepsy represented uncontrolled brain activities that can be idiopathic or caused by intracerebral lesions. It is an important neurological diseases while the pathogenic mechanisms are complex, with long duration of disease interval, high recurrent rate. Epilepsy is listed as one of the world's top ten medical problems.Patients with epilepsy often experienced unpredictable condition that required admission. These included recurrent seizure with regular drug compliance, drug withdrawal seizure, side effects after drug overdoses, medical conditions or accidents. These events, if recurred multiple times within one year, could lead to great patient stress, family burden and socioeconomic expenses. In this retrospective study, our primary aim is to find out the risk factors that determine multiple unplanned admission in patients with epilepsy within one year. The result of this study can be used to model further nursing care to reduce disease related relapse and to decrease unexpected admission in patients at risks.Research design and methods:1.trospective chart review period: from January 2012-December 2013 2.Cases selected from patients admitted at Chang Gung Memorial hospital, Kaohsiung Explanation 3. Selection criteria: Patients admitted at Neurologic wards 4. Number of samples: Expects about 332 patients will be entered in this study. Age> 20 year-old; Both male and female Explanation:This study used a retrospective study that will collect the following information (see medical records format): 1.patient basic information, such as: gender, age, marital status, education level, length of stay, ways for hospitalization, readmission reasons 2. inpatient medical history, disease course 3. seizure type, seizure frequency, duration years, the use of anti-epileptic drug items, state of consciousness, vital signs items, nutritional status, self-care, support indwelling catheters 4 discharged. after care and carers and other relevant changes, research and analysis,Statistical Analysis All values were expressed as mean ? standard deviation. The chi-square test was used to compare the significance between categorical variables. The t-test or One-way ANOVA with Bonferroni correction was used, as appropriate, to compare continuous variables between groups. Person correlation was used to explore the correlation of clinical scores All statistical analyses were performed using the Statistical Package for Social Science (SPSS, version 14.0 for Windows; Chicago, IL, USA). Statistical significance was set at p<.05.Results: The results showed that the average age of inpatients again about 56.9 years, the country following qualifications, and family live up to, epilepsy patients unplanned readmission rate was 34.9% (674/6725), further logistic regression analysis showed that non-planned readmission predictors: the reasons for hospitalization - organic brain diseases, metabolic and drug-induced epilepsy, predisposing factors, assessing awareness of this admission, admission heart rate to assess whether there is support for indwelling catheters admission , admission adult nutritional assessment, whether the admission weight satisfactory and activities of daily living assessment on admission, whether involved in discharge planning program admission, discharge state of consciousness, within one year after discharge activity during the impact assessment are discharged predictors of unplanned readmission of persons.Conclusions: Reduce future unplanned readmission rates will depend on to get a better understanding of the reasons for readmission and predisposing factors. The results obtained in this study can not only provide further clinical nurse caring for patients with epilepsy and rigorous disposal more quickly, but also a clearer interpretation of the risk factors associated with epilepsy unplanned readmission. Future plans will be able to complete construction of automated computerized information tools epilepsy care model assessment monitoring system to reduce unplanned readmission case will be established epilepsy care model for patients with disorders of the important policy intervention.Key Words: Epilepsy, Unplanned readmission, Medical care quality |
