全球醫療人力荒持續升溫，特別在COVID-19疫情後，醫師與護理師的大量流失對醫療品質與財務營運造成顯著挑戰。為因應高流動率與人力老化問題，各國政府陸續推出多元化的留任機制與激勵策略，然成效與可持續性差異甚鉅。本研究以台灣護理人力為核心觀察對象，選擇美國、澳洲、英國與日本四個已開發國家為比較對象，針對其護理人員在制度誘因、政策架構、財務回報與人力管理模式等層面進行橫向評比與結構化分析。透過文獻資料蒐集、官方數據比對與政策內容解析，建構出具備彈性工時、專業成長、心理支持與區域誘因的「混合式留才模型」架構，並結合企業管理與Z世代人才價值觀，提出可應用於台灣及類似醫療體系的具體建議。本研究亦從財務觀點探討不同誘因對留任成本效益之影響，強調留才制度不應只限於薪資調整，更應透過制度創新與文化管理，實現永續人力資本經營。

The global shortage of medical personnel has intensified, particularly in the aftermath of the COVID-19 pandemic, making nurses turnover the primary operational bottleneck for acute-care systems, with direct impacts on patient flow, safety, and financial sustainability. Centering on Taiwan and benchmarking the United States, Australia, the United Kingdom, and Japan, this study conducts a structured, cross-national comparison of nurse retention policies across four levers: compensation architecture (differential shift premiums, staged retention bonuses, tuition support tied to service); workforce design (staffing ratios, AI-enabled demand forecasting, cross-unit float pools, flexible／part-time tracks); organizational infrastructure (mentoring, psychological safety, Magnet／Pathway-type identity models); and regional／service-line incentives. Using peer-reviewed literature, official datasets, and policy documents, we synthesize a hybrid retention model that aligns managerial innovation with financial sustainability: shift from one-off bonuses to sustained differentials; link rewards to capability and teaching; and pair predictable scheduling with system-level peak-load deflection (e.g., AI staffing, weekend／holiday UCCs). We frame retention as a capital allocation loop which redeploying savings from overtime, agency labor, and avoidable boarding into targeted premiums, mentoring capacity, and re-entry programs thereby stabilizing supply without expanding the reimbursement envelope. The model offers actionable guidance for Taiwan and similar systems, while addressing Generation Z expectations for autonomy, development, and well-being.

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