本研究旨在估算慢性疾病的生產力損失，並以中風患者為例。在依據性別、年齡層，以及初始從業身份進行分組之下，估算各組的終身生產力損失。透過2000年至2013年的全民健保資料庫，先篩選出罹患中風當下25歲至65歲的患者。接著再以中風患者為基礎，用1:10的比例抽樣配對，建構出對照組。將資料進行處理並分組後，匯入iSQoL2，以外推估計「經就業機率調整的存活函數」。同時，使用2000年至2013年的人力運用調查資料庫，在依據性別以及從業身份分組後，估算出各組25歲至65歲的薪資。並且考慮到「從業身份的轉換」以及「投保於職業工會者」的存在，運用全民健保資料庫算出「從業身份轉換機率」與「職業工會占比」，以得到各組的「期望薪資」。最後結合「經就業機率調整的存活函數」以及「期望薪資」，估算出在特定性別、年齡層，以及初始從業身份下，罹患中風所導致的終身生產力損失。估算結果顯示：男性的生產力因中風所造成的損失大於女性。再而，若罹患中風時的年齡層較低，也對生產力有較大的影響。另外，初始從業身份為無業者，罹患中風所承擔的生產力損失比例最高；初始從業身份為公部門者，因中風所喪失的生產力總價值最大。本研究建議：無論是男性或女性、哪一個年齡層，或者何種從業身份，都能警覺中風對於生產力的巨大影響，並喚醒個人及政策決定者，對於中風的預防意識。

　　This study aims to estimate the productivity loss of chronic diseases. Using stroke patients as an example, this research classifies the observed groups by gender, age, and initial employment status. First, screen out patients with strokes from the ages at 25 to 65 from the National Health Insurance Research Databases over the priod of 2000 to 2013. Then sample pairing with a ratio of 1:10 to construct a control group based on the stroke patients. After the data is classified, importing the observed groups into iSQoL2 to extrapolate and estimate the "survival function adjusted by employment probability". Furthermore, this research uses the Manpower Utilization Survey Database over the period from 2000 to 2013 to estimate the salary of the group at age of 25 to 65, grouped by sex and employment status. After adjustment of transition probability of employment status, and the proportion of craft unions, this research calculates the expected salary. Finally, combining the "survival function adjusted by employment probability" and the the expected salary, we estimate lifetime productivity loss due to stroke at a specific gender, age, and initial employment status. Estimation results indicate that productivity loss of stroke male patients is greater than that of female patients. men’s due to stroke will bigger than women’s. Patients at younger age lose more productivities than patients at the older age for the whole life. Besides, if patient’s initial employment status is unemployed, the ratio of productivity loss will be the highest among the patients. If the initial employment status is public sector, the total value of productivity loss is the biggest. Prevention on stroke requests for the public and the policy maker’s attentions.

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