目的：调查神经眼科用药现状，并对其超说明书用药进行评价，探索科学有效的管理策略，为神经眼科的临床合理用药提供参考。方法：随机抽取2023年7—12月郑州市第二人民医院神经眼科处方，依据国家药品监督管理局核准的药品说明书、美国食品药品监督管理局(Food and Drug Administration, FDA)说明书及UpToDate、Micromedex等循证医学数据库证据判断超说明书用药类型，并对其进行分类(包括超适应证、超剂量、超疗程、超给药途径等)。同时基于Thomson分级理论建立三级评价标准，分别为A级(高证据等级，仅需口头告知)，B级(中证据等级，需在病历或病程中详细记录)，C级(低证据等级，须患者签署书面知情同意书)。通过处方前置审核系统干预，对未纳入评价标准的超说明书用药进行实时拦截与分级警示，比较2023年下半年(干预前)与2024年下半年(干预后)超说明书用药处方的不合理率变化。 结果：干预前共抽取超说明书处方370张，超说明书类型主要为超适应证、超给药途径和超剂量及次。干预后，共抽取超说明书用药560张，超说明书用药不合理率从9.2%(34/370)降至2.9%(16/560)。结论：神经眼科超说明书用药普遍，主要源于视神经炎、缺血性视神经病变等复杂疾病的治疗需求与药品审批滞后之间的矛盾。基于循证医学证据构建分级管理体系，结合信息化实时干预，可有效规范超说明书用药行为，降低医疗风险。

Objective: To investigate the current status of medication use in neuro-ophthalmology, evaluate off-label drug use, and explore scientific and effective management strategies, providing references for rational drug use in neuro-ophthalmology clinical practice. Methods: We Randomly selected neuro-ophthalmology prescriptions from July to December 2023 in our hospital. By refering to the drug instructions approved by the National Medical Products Administration, FDA instructions, and evidence from evidence-based medical databases such as UpToDate and Micromedex, we identified and classified the types of off-label drug use, including off-label indications, off-label doses, off-label courses, off-label administration routes, among others. Simultaneously, based on the Thomson classification theory, we established a threelevel evaluation standard: Level A (high evidence level, requiring only oral notification); Level B (medium evidence level, necessitating detailed records in the medical record or medical course); Level C (low evidence level, demanding patients sign a written informed consent form). Through the intervention of pre-prescription review system, we carried out real-time interception and classification warnings for off-label drug use not covered in the evaluation standards. We then compared the changes in the unreasonable rate of off-label drug use prescriptions from the second half of 2023 (before intervention) to the second half of 2024 (after intervention). Results: Before the intervention, a total of 1852 prescriptions were selected, with the proportion of off-label drug use at 19.98% (370 prescriptions), primarily involving off-label indications (90.27%). After the intervention, the unreasonable rate of off-label drug use decreased from 9.2% (34/370) to 2.9% (16/560). Conclusions: Off-label drug use is prevalent in neuro-ophthalmology, mainly due to the conflict between the treatment requirements for complex diseases such as optic neuritis and ischemic optic neuropathy and the delay in drug approval. By constructing a hierarchical management system based on evidence-based medical evidence and combing it with real-time information-based intervention, we can effectively regulate off-label drug use behavior and reduce medical risks.