以醫師觀點，探討台灣醫學中心於COVID-19防疫策略

Physicians’Perspective of Prevention Strategy of Taiwan Medical Center on COVID-19

目的：世界衛生組織於2020 年3 月11 日宣布嚴重特殊傳染性肺炎(COVID-19) 進入全球大流行。依據台灣衛生福利部疾病管制署公告，2020 年1 月21 日我國確診首例境外移入COVID-19 個案，全國各醫院隨即啟動防疫措施。本研究主要比較跨院際醫療支援之主治醫師對醫院防疫策略的信心感受。方法：採回溯性研究設計，使用次級資料分析，母研究自2020 年3 月至2020 年4月對跨院支援的醫師進行問卷發放。結果：納入研究結果分析共58 人，男性佔77.6%，大多支援區域醫院(37.9%)，84.5% 為兼任支援。綜合來說，對於醫院整體的防疫措施，支援醫院感受均值為4.91 分（普通），本研究個案醫院為5.50 分（有信心），於支援醫院與本研究個案醫院之間的信心程度有達統計上顯著差異(t = – 4.147, p = 0.000 < 0.01)。另，受測醫師對於醫學中心之「陪病及探病管制」及「醫院提供的防疫資訊」，較非醫學中心有信心( p < 0.05)。結論：本研究結果顯示在這個資訊化與醫療導入AI (Artiflcial Intelligence) 的時代，醫療政策合併資訊平台同步發展，不僅能配合瞬息萬變的防疫政策，更能增加員工對於機構的管理信心。

Objective: On March 11, 2020, the World Health Organization declared the outbreakof severe special infectious pneumonia (COVID-19) as a global pandemic. According to theannouncement of Taiwan’s Centers for Disease Control, the first case of COVID-19 in Taiwanwas imported from abroad on January 21, 2020, and hospitals across the country immediatelyinitiated epidemic prevention measures. In this study, the confidence of physicians involved in theinterhospital medical support implemented as part of hospitals’ epidemic prevention strategies wereassessed.Methods: A retrospective study design was adopted, and secondary data analysis wasconducted. In the parent study, questionnaires were administered to physicians who participated ininterhospital medical support from March to April of 2020.Results: A total of 58 physicians were included in the analysis, of which 77.6% were men.Most of them offered medical support in regional hospitals (37.9%), with 84.5% offering parttimesupport. For the overall epidemic prevention measures of the hospital, the average confidencescore for the been supported hospitals and the case hospital was 4.91 (normal) and 5.50 (confident),respectively. A statistically significant difference in the degree of confidence was observedbetween the supporting hospital and case hospital (t = −4.147, p = 0.000, p < 0.01). In addition,the physicians have more confidents in medical center rather than unmedical center in the “medicalmanagement of the accompany and visiting center” and “the epidemic prevention informationprovided by the hospital” (p < 0.05).Conclusion: The results of this study indicated that the introduction of artificial intelligencein medical care alongside the development of medical policy integration information platformscan assist hospital management in coping with the ever-changing epidemic prevention policiesand increase employees’ confidence in managerial policy strategies.