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In hospitals, safety climate refers to the safety policies and regulations established by medical institutions and the measures taken to ensure medical personnel feel safe while working at these institutions. Safety climate can directly affect the overall work performance of medical personnel and indirectly affect patient care quality, which in turn impacts the rate of occupational hazards. Common occupational hazards in the medical workplace include contracting infectious diseases, overwork, irregular circadian rhythm due to working shifts, changes in sleep patterns and dietary habits, musculoskeletal discomfort, workplace violence, workplace stress, and needlestick injuries. This paper was developed to explore the history of promoting needlestick prevention in Taiwan, and discusses how to use the results of empirical research as scientific evidence and critical proofs to advocate for needlestick prevention and to establish related policies. In addition, the process of how improvements to the hospital safety climate and the prevention of occupational hazard incidents mutually influence and complement each other was examined. Future studies are encouraged to explore this topic to further elucidate the sources of workplace stress and to devise methods to ameliorate their influence on workplace stress in medical institutions. The results of these studies may be referenced by relevant government agencies and medical institutions when developing policies promoting safe environments in hospitals that improve the safe-work perceptions of nursing personnel and create comfortable and friendly medical environments.醫院安全風氣：由科學到政策—臺灣針扎防治歷程.醫療機構所建立相關的安全政策與制度，讓醫療人員感受到組織安全的相關作為，即是醫院安全風氣，其可以直接影響醫療人員整體工作表現，及間接地影響病人的照護品質，並進一步影響職業危害的發生狀況。醫療職場常見的職業危害，包含傳染性疾病、過勞高風險、輪班造成的晝夜節律、睡眠型態與飲食習慣改變、肌肉骨骼不適、職場暴力、職場壓力及針扎等；本文即是分享臺灣在針扎防治的推動歷程，如何運用實證研究結果的科學證據，倡議及提供政策制定的重要佐證及說帖，進而提升醫院安全風氣與職業危害事件降低之互相影響與改善的過程；未來應鼓勵透過更多的科學研究投入，針對職場壓力源的了解與改善，提供政府主管部門及醫療機構制定政策之參考，以創造安全風氣高的護理執業環境及提升護理人員對執業環境安全的整體知覺，共創合宜、友善的醫療執業環境。.

Additional file 1.. Fig. S1. Annotation rules for hemodynamic intervention. Table S1. Clinical variables used in HSI and plausibility filter for each variable. Table S2. Missing rate of clinical variables. Table S3. Baseline characteristics comparison between unstable and stable patients. Table S4. Performances of HSI model, shock index and systolic blood pressure in TPEVGH cohort. Table S5. Confusion matrix of HSI model under different threshold. Table S6. Subgroup performance of HSI model in TPEVGH. Table S7. Median comparison between the US cohort and TPEVGH cohort.