影響急診轉診效率相關因素之探討--以嘉義市基督教醫院為例

Abstract

研究背景與目的：急診轉診是完善病人治療、達成區域聯防及緩解急診壅塞的重要手法之一，跟病人安全息息相關。台灣醫療體系在急診轉診方面面臨許多挑戰，特別是急重症患者轉診時的效率問題。本研究以嘉義市基督教醫院為例，評估急診轉診流程的效率，探討影響急診轉診效率的因素，並尋找改善策略。 研究方法：採用前瞻性量性研究，收集嘉義市基督教醫院2024年3月1日起合乎研究目的的100份轉診記錄單，進行個案探討及統計分析。單變項分析為急診轉診患者，在三大時間區段(轉診前在急診已滯留時間，尋找接收醫院時間，行政流程及等候救護車)共花了多少時間。雙變項分析裡，自變項包括病人因素、醫院因素及區域因素。依變項則為尋找接收醫院的時間(本研究選用的轉診效率指標)。 研究結果：嘉基跟醫學中心一樣，面臨病人轉診意願低下及急診壅塞。不同點為轉診族群多樣化，轉出以需求加護病房最多(47%)且不少為外縣市(28%)。病人坐救護車來院時在轉出時會有更短的找醫院時間(平均15.75分)，病人轉出至外縣市時會有更長的找醫院時間(平均41.179分)。在急診滯留總時間裡，尋找接收醫院的時間為各時間區段裡占比最低(平均24分鐘/9.49%)，現階段國內無其他醫院的文獻可供比較。 結論：本研究提供了結構式的分析視角，發現在急診轉診流程中各階段會面臨的挑戰不同。研究發現，尋找接收醫院時間在整個轉診流程中占比最低，雖然轉到外縣市較耗時，但年長患者與嚴重患者在找醫院時間與其他患者相比並無顯著差異。數據收集及分析的過程中發現轉診阻力的存在，推測受到病人、醫師及環境等諸多因素的影響。整體數據肯定政府對急重症轉診網絡和綠色通道的規劃，但在疫情等特殊情況下是否仍能維持轉診韌性則需進一步的研究釐清。此外，在阻力存在情況下(如病人轉診意願低)，本研究未能有效評估轉診效率的全貌。建議當病人須要跨縣市轉診時，要注意找醫院時間及轉送距離可能對病人安全帶來影響。相關單位要規劃當地醫療量能，可根據本研究結構式手法輔以數據自動化，建立轉診指引及院際合作，監測及改善轉診效率。

Research Background and Purpose: Emergency referrals are a crucial method for ensuring comprehensive patient care, achieving regional medical collaboration, and alleviating emergency department congestion, all of which are closely related to patient safety. The Taiwanese healthcare system faces numerous challenges in emergency referrals, particularly regarding the efficiency of referrals for critically ill patients. This study uses Chiayi Christian Hospital as a case study to assess the efficiency of the emergency referral process, explore factors affecting referral efficiency, and seek improvement strategies.

Research Method: This study adopts a prospective quantitative approach, collecting 100 referral records from Chiayi Christian Hospital starting from March 1, 2024, that meet the research purposes. Case studies and statistical analyses are conducted. Univariate analysis examines the total time spent in three major time segments (time spent in the emergency department before referral, time spent finding a receiving hospital, administrative processes, and waiting for an ambulance) for emergency referral patients. In the bivariate analysis, independent variables include patient factors, hospital factors, and regional factors, while the dependent variable is the time spent finding a receiving hospital (the efficiency indicator selected for this study).

Research Results: Similar to medical centers, Chiayi Christian Hospital faces low patient willingness for referrals and emergency department congestion. Differences include a diverse referral population, with the highest demand for intensive care units (47%), and a significant portion being out-of-county referrals (28%). Patients arriving by ambulance had shorter times in finding a receiving hospital (average 15.75 minutes), while out-of-county referrals took longer (average 41.179 minutes). In the total emergency department stay time, the time spent finding a receiving hospital was the lowest among all time segments (average 24 minutes/9.49%). Currently, no other hospital literature is available for comparison domestically.

Conclusion: This study provides a structured analysis perspective, identifying different challenges faced at each stage of the emergency referral process. It found that the time spent finding a receiving hospital was the lowest in the entire referral process. Although it takes longer to refer patients to out-of-county hospitals, no significant difference was found in the time spent finding a hospital between elderly or critically ill patients and other patients. The data collection and analysis process revealed the existence of referral resistance, hypothesized to be influenced by patient, physician, and environmental factors. The overall data affirms the government's planning of emergency referral networks and green channels for critical cases. However, the resilience of referrals under special circumstances such as pandemics requires further study. Moreover, where barriers exist (such as low patient willingness to transfer), this study could not fully assess the overall efficiency of referrals. For safety considerations, recommendations include paying attention to contact time and transfer distance when patients need inter-county referrals. It is crucial to plan local medical capacity and utilize structured methods from this study, combined with data automation, to establish referral guidelines and inter-hospital cooperation in order to monitor and improve referral efficiency.