目的：分析眼科护理对人工智能技术应用的内在需求，为眼科医院临床的人工智能技术开发及应用提供导向与依据。方法：采用整群抽样和单纯随机抽样相结合的方法，于2019年7月至2019年8月，对抽取的中山大学中山眼科中心，中山大学附属第一医院、珠海市人民医院、无锡人民医院、新疆维吾尔族自治区人民医院等目标医院其中的眼科护理人员进行问卷调查，内容包括一般资料及人工智能需求等。结果：调查对象绝大部分来自三级甲等医院(89.2%)，以华南地区为主(87.2%)，人工智能在眼科临床护理应用的需求多种多样，其中以健康教育、接诊与分诊、患者回访领域需求最强烈，分别占比95.7%、93.5%、93.2%。结论：人工智能在眼科临床护理应用有较强及多样化的需求，应结合实际需求为导向，重点推进人工智能在眼科患者健康教育等相关应用的研发。
Objective: To analyze the internal demands of the application of artificial intelligence technology to ophthalmic care, and provide guidance and basis for the development and application of artificial intelligence technology in ophthalmic hospitals. Methods: Using the method of combining cluster sampling with simple random sampling, a questionnaire survey was conducted on the ophthalmic nursing staff in the selected target hospitals from July to August 2019, which included general information and artificial intelligence needs. Results: Most of the respondents came from the third-class hospitals (89.2%), and hospitals in South China account for 87.2% of them. There are diverse demands of artificial intelligence in ophthalmology clinical nursing applications, including health education, clinical reception and triage, patients return visits, which have the strongest demand for the artificial intelligence, accounting for 95.7%, 93.5%, and 93.2%, respectively. Conclusion: The application of artificial intelligence in ophthalmic clinical nursing has strong and diversified demands, and the research and development of artificial intelligence in the health education of ophthalmic patients and other related applications should be promoted according to the actual demands.
目的：探讨多元化宣教在提高眼科日间手术患者眼部用药正确率及满意度的应用效果。方法：采用便利抽样的方法，选取中山大学中山眼科中心2020年10至12月收治的200例眼科日间手术患者眼部用药的执行者为对象，将10至11月收治的100例日间手术患者眼部用药的执行者纳入对照组，将12月收治的100例日间手术患者眼部用药的执行者纳入试验组。对照组采取传统宣教方式，试验组应用多元化宣教模式进行健康教育。采用自制的健康教育需求调查表调查眼部用药执行者的健康教育需求，采用眼部用药执行评价表、健康宣教满意度调查表评价干预效果。结果：采用多元化宣教方式干预后，试验组患者眼部用药正确率(94%)高于对照组(35%)，差异具有统计学意义(P<0.05)。试验组对多元化宣教满意度得分明显高于对照组，差异具有统计学意义(P<0.05)。结论：多元化宣教模式可提高眼科日间手术患者眼部用药正确率，提高患者及家属的满意度，值得临床推广应用。
Objective: To explore the effect of diversified education on improving the accuracy and satisfaction of eye medication in patients undergoing ophthalmic ambulatory surgery. Methods: A total of 200 practitioners of administering eye medication after undergoing ambulatory surgery in Zhongshan Ophthalmic Center, Sun Yat-sen University from October to December 2020 were investigated by convenience sampling, 100 practitioners admitted from October to November were included in the control group, and 100 practitioners were included in the experimental group. The control group adopted the traditional method of education, while the experimental group applied diversified education mode to carry out health education. The health education needs of the patients were investigated by the self-made health education needs questionnaire, and the effect of intervention wasevaluated by the eye medication implementation evaluation form and health education satisfaction questionnaire. Results: After the intervention, the correct rate of eye medication in experimental group (94%) was higher than the control group (35%) with a statistical difference (P<0.05). The satisfaction score about diversified education in experimental group was significantly higher than the control group with a statistical difference (P<0.05).Conclusion: Diversified education model can improve the accuracy of administering eye medication in patientsundergoing ophthalmic ambulatory surgery, and the satisfaction in patients and their families is significantly improved. It is worthy of clinical application.
目的：分析眼科护理对人工智能技术应用的内在需求，为眼科医院临床的人工智能技术开发及应用提供导向与依据。方法：采用整群抽样和单纯随机抽样相结合的方法，于2019年7月至2019年8月，对抽取的中山大学中山眼科中心，中山大学附属第一医院、珠海市人民医院、无锡人民医院、新疆维吾尔族自治区人民医院等目标医院其中的眼科护理人员进行问卷调查，内容包括一般资料及人工智能需求等。结果：调查对象绝大部分来自三级甲等医院(89.2%)，以华南地区为主(87.2%)，人工智能在眼科临床护理应用的需求多种多样，其中以健康教育、接诊与分诊、患者回访领域需求最强烈，分别占比95.7%、93.5%、93.2%。结论：人工智能在眼科临床护理应用有较强及多样化的需求，应结合实际需求为导向，重点推进人工智能在眼科患者健康教育等相关应用的研发。
Objective: To analyze the internal demands of the application of artificial intelligence technology to ophthalmic care, and provide guidance and basis for the development and application of artificial intelligence technology in ophthalmic hospitals. Methods: Using the method of combining cluster sampling with simple random sampling, a questionnaire survey was conducted on the ophthalmic nursing staff in the selected target hospitals from July to August 2019, which included general information and artificial intelligence needs. Results: Most of the respondents came from the third-class hospitals (89.2%), and hospitals in South China account for 87.2% of them. There are diverse demands of artificial intelligence in ophthalmology clinical nursing applications, including health education, clinical reception and triage, patients return visits, which have the strongest demand for the artificial intelligence, accounting for 95.7%, 93.5%, and 93.2%, respectively. Conclusion: The application of artificial intelligence in ophthalmic clinical nursing has strong and diversified demands, and the research and development of artificial intelligence in the health education of ophthalmic patients and other related applications should be promoted according to the actual demands.
