一种使用电子健康记录编码的新方法,用于生成一个独特的,多用途的数据库,用于对空气消化系统恶性瘤的监测
Lindsey Mortensen1, Alexander Dwyer1, Benjamin Palatnik1
1Department of Otolaryngology, University of Minnesota, MMC396, 420 Delaware St SE, Minneapolis, MN 55455, USA.
Oral oncology
|February 12, 2026
概括
自动化的电子健康记录查询有效地识别了患有口腔潜在恶性疾病 (OPMDs) 的患者. 这些数据有助于提高临床试验的包容性和了解癌症风险.
科学领域:
- 在瘤学瘤学.
- 公共卫生 公共卫生
- 医疗信息学 医疗信息学
背景情况:
- 头部和部癌症,特别是口腔和口腔大,每年影响超过45,000人.
- 对口腔潜在恶性疾病 (OPMDs) 的监测提供了一种减轻这些癌症负担的策略.
- 一项试点研究引入了癌症积极监测计划 (CASP) 的数据库生成方法,适用于各种癌症前期疾病.
研究的目的:
- 评估一种数据库生成方法,用于从癌症积极监测计划 (CASP) 获取数据.
- 评估使用电子病历 (EMR) 数据用于识别OPMD患者的可行性.
- 分析CASP队列中的地理和种族代表性.
主要方法:
- 采访EMR数据使用35个ICD-9和ICD-10代码,代表超过300个独特的粘膜病变描述符.
- 进行了概念验证分析,以评估CASP内的地理和种族人口统计数据.
- 将EMR数据的自动提取与OPMD识别的手动图表检查进行比较.
主要成果:
- 自动EMR提取识别了1576名OPMD患者,显示了比手动审查更高的准确性和更低的成本.
- 与州人口数据相比,城市地区的CASP患者比例较高,农村地区的比例较低.
- CASP队列包括较高比例的黑人患者和较低比例的亚洲/太平洋岛屿患者,而不是总体的癌症人口统计数据.
结论:
- 自动化EMR查询有效地识别在定义的采集区内患有癌前或风险状况的患者.
- 这种数据驱动的方法可以为资源分配提供信息,以提高代表性不足的群体的包容性.
- 这种方法促进了对癌症预防临床试验潜在参与者的简化识别.
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