2020/12/17 [最新預刊]

Surge capacity解析與規劃—八仙事件的醫院實證

目標:本研究目的是針對突發湧入作業能量(surge capacity)的意義與規劃,以八仙粉塵暴燃事件(八仙事件)實證進行釐清與解析,以提升該名詞的在災害應變計畫中的應用。 方法:收集四家初期收治八仙傷患醫院的基本能量資料、急診室大量傷患湧入期間的傷病患檢傷、出入急診時間、轉院/轉房等紀錄,以及相關文獻。採用流程追蹤分析方法,建立傷病患流動與急診負荷變化的時間圖列,並計算各醫院過載時間、負荷指數、以及負荷上升與減緩指數,進一步比較醫院間大量傷患湧入對於突發湧入作業能量的需求變化樣態與速率。 結果:八仙事件造成四家醫院呈現四種傷病患超載的緊急醫療服務需求模型,其中MM和TH醫院的過載時間與負荷指數較高,顯示該二醫院資源供需的差距最大,以及醫院應變的相對困難度較高。基於醫院規模與急診平日診量之差異,MM與TH醫院衡量突發湧入作業能量的病床基準並不一致。另外,MM的負荷變化速率亦高於TH,對於資源短缺的因應,視緊急醫療處置內容與短缺項目,兩家醫院採取類似或差異化的調適性(韌性)作為,來應對醫療處置能量間的差距。 結論:Surge capacity 並不能統一單一衡量指標,如空床數,來運算出“最大”的計量,而是依照大量傷患的規模與醫院的特性,設置適當的衡量基準。Surge capacity的規劃宜以突發湧入作業能量概念結合韌性能力,並加強系統要素在資源規劃的角色,同時,參考過載時間、負荷增減速率等多元性的因素,做為未來大量傷患緊急應變計畫的整備策略。

  • 預定刊載卷期:台灣衛誌 2020;39(6)
  • 原著 Original Article
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  • 莊秀文
    Sheu-Wen Chuang
  • 台灣大量傷患事件、八仙事件、緊急應變、突發湧入作業能量(surge capacity)
  • 目標:本研究目的是針對突發湧入作業能量(surge capacity)的意義與規劃,以八仙粉塵暴燃事件(八仙事件)實證進行釐清與解析,以提升該名詞的在災害應變計畫中的應用。 方法:收集四家初期收治八仙傷患醫院的基本能量資料、急診室大量傷患湧入期間的傷病患檢傷、出入急診時間、轉院/轉房等紀錄,以及相關文獻。採用流程追蹤分析方法,建立傷病患流動與急診負荷變化的時間圖列,並計算各醫院過載時間、負荷指數、以及負荷上升與減緩指數,進一步比較醫院間大量傷患湧入對於突發湧入作業能量的需求變化樣態與速率。 結果:八仙事件造成四家醫院呈現四種傷病患超載的緊急醫療服務需求模型,其中MM和TH醫院的過載時間與負荷指數較高,顯示該二醫院資源供需的差距最大,以及醫院應變的相對困難度較高。基於醫院規模與急診平日診量之差異,MM與TH醫院衡量突發湧入作業能量的病床基準並不一致。另外,MM的負荷變化速率亦高於TH,對於資源短缺的因應,視緊急醫療處置內容與短缺項目,兩家醫院採取類似或差異化的調適性(韌性)作為,來應對醫療處置能量間的差距。 結論:Surge capacity 並不能統一單一衡量指標,如空床數,來運算出“最大”的計量,而是依照大量傷患的規模與醫院的特性,設置適當的衡量基準。Surge capacity的規劃宜以突發湧入作業能量概念結合韌性能力,並加強系統要素在資源規劃的角色,同時,參考過載時間、負荷增減速率等多元性的因素,做為未來大量傷患緊急應變計畫的整備策略。
    Objectives: To investigate and compare hospitals’ surge capacity during the Formosa Fun Coast Dust Explosion (FFCDE) to promote refined applications of surge capacity in disaster response planning. Methods: We collected the following data from four initial receiving hospitals after the FFCDE: basic hospital capacity; emergency department (ED) patient log data, including triage, arrival time, departure or discharge time, and ED stay duration; and related literature. Process tracking analysis was employed to establish a time chart of patient flow against the ED workload. Each hospital’s overload time, load index, load accumulated index, and load relief index were calculated and used to compare the effects of burn patient influx and demand patterns on the overload rates of the four hospitals with respect to surge capacity. Results: After FFCDE, the four hospitals presented four types of dynamic overload patterns, all of which illustrated their emergency medical service demand statuses. The overload time and load index of the MM and TH hospitals were relatively high, indicating that these hospitals had the largest resource supply–demand gap. Moreover, the two hospitals had some difficulty in eliciting response. The differences between hospital size and average number of daily ED patient visits indicated differences in metrics of bed size measurement used by the MM and TH hospitals for measuring surge capacity. Furthermore, the load change rate was higher in hospital MM than in hospital TH. Depending on the content of emergency medical treatment and shortage items, the MM and TH hospitals elicited similar or different responses to cope with medical resource shortages. Conclusions: Surge capacity was not consistently calculated as a “maximum” measurement of only one metric (e.g., number of empty beds), but it was set using appropriate measurements based on the mass casualty size and characteristics of each hospital. Surge capacity is defined as the capacity to satisfy sudden demand due to patient influx during or after a disaster. Hospitals should integrate the concept of surge capacity with resilience, strengthen the role of their system elements during surge capacity planning, and adopt multiple dimensions, including resource volume, overload time, load accumulated index, and relief index, when conducting surge capacity planning for disaster response.
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