使用医院病例统计数据库识别未破裂的内动脉瘤的选择性治疗方法
Samuel Hall1, Benjamin Gaastra1,2, Frederick Ewbank1,2
1Department of Neurosurgery, University Hospitals Southampton NHS Foundation Trust, Southampton, Hampshire, UK.
British journal of neurosurgery
|July 2, 2025
概括
医院情节统计数据库有效地识别了未破裂的内动脉瘤治疗方法,高灵敏度对于动脉瘤破裂风险研究的随访至关重要. 这种编码准确性确保可靠的数据来确定断裂风险.
科学领域:
- 神经外科 神经外科
- 医疗信息学 医疗信息学
- 流行病学 流行病学
背景情况:
- 动脉瘤破裂风险 (ROAR) 研究旨在评估已知未破裂的内动脉瘤 (UIA) 患者的破裂风险.
- 准确识别UIA治疗对于患者的随访和自然历史研究中的审查至关重要.
- 国家医疗保健数据库被建议用于患者随访,需要验证它们对UIA治疗的编码灵敏度.
研究的目的:
- 评估各种诊断和程序代码的敏感性,以确定可选的未破裂的内动脉瘤治疗方法.
- 确定医院病例统计 - 入院患者护理 (HES-APC) 数据库用于捕获UIA治疗事件的有效性.
- 在前ROAR研究中确定患者随访的最佳数据来源.
主要方法:
- 从单个神经外科病房 (2006-2020年) 进行患者记录的回顾性审查.
- 患者记录与"医院病例统计 - 入院患者护理 (HES-APC) "数据库的链接.
- 案例注释审查所有HES发作与OPCS4代码用于动脉瘤治疗,包括外部记录检索.
主要成果:
- 共有318种选择性UIA治疗方法被确定,其中310种 (95.6%的灵敏度) 被HES-APC数据库捕获.
- 在ROAR研究中,HES-APC和电子病历的综合灵敏度估计为99.88%.
- 在HES-APC记录的93.8%的选择性动脉瘤治疗中,OPCS4代码L33或O01-4被使用.
结论:
- 该HES-APC数据库显示高灵敏度,是识别可选UIA治疗的宝贵资源.
- 已建立的编码灵敏度支持在ROAR研究中使用HES-APC进行强大的长期患者随访.
- 准确识别治疗事件对于可靠的自然史研究不可破裂的内动脉瘤至关重要.
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