...
首页> 外文期刊>BMC Medical Informatics and Decision Making >Automated comparison of last hospital main diagnosis and underlying cause of death ICD10 codes, France, 2008–2009
【24h】

Automated comparison of last hospital main diagnosis and underlying cause of death ICD10 codes, France, 2008–2009

机译:自动比较上次医院的主要诊断和基本死亡原因ICD10代码,法国,2008-2009年

获取原文
   

获取外文期刊封面封底 >>

       

摘要

Background In the age of big data in healthcare, automated comparison of medical diagnoses in large scale databases is a key issue. Our objectives were: 1) to formally define and identify cases of independence between last hospitalization main diagnosis (MD) and death registry underlying cause of death (UCD) for deceased subjects hospitalized in their last year of life; 2) to study their distribution according to socio-demographic and medico-administrative variables; 3) to discuss the interest of this method in the specific context of hospital quality of care assessment. Methods 1) Elaboration of an algorithm comparing MD and UCD, relying on Iris, a coding system based on international standards. 2) Application to 421,460 beneficiaries of the general health insurance regime (which covers 70% of French population) hospitalized and deceased in 2008–2009. Results 1) Independence, was defined as MD and UCD belonging to different trains of events leading to death 2) Among the deaths analyzed automatically (91.7%), 8.5% of in-hospital deaths and 19.5% of out-of-hospital deaths were classified as independent. Independence was more frequent in elder patients, as well as when the discharge-death time interval grew (14.3% when death occurred within 30?days after discharge and 27.7% within 6 to 12?months) and for UCDs other than neoplasms. Conclusion Our algorithm can identify cases where death can be considered independent from the pathology treated in hospital. Excluding these deaths from the ones allocated to the hospitalization process could contribute to improve post-hospital mortality indicators. More generally, this method has the potential of being developed and used for other diagnoses comparisons across time periods or databases.
机译:背景技术在医疗保健中的大数据时代,大型数据库中医疗诊断的自动比较是一个关键问题。我们的目标是:1)正式定义和确定死者在生命的最后一年中,其上次住院主要诊断(MD)和死亡原因背后的死亡登记(UCD)之间的独立性; 2)根据社会人口统计学和药物管理变量研究其分布; 3)在医院护理质量评估的特定背景下讨论此方法的重要性。方法1)依靠Iris(基于国际标准的编码系统),拟定一种比较MD和UCD的算法。 2)在2008–2009年期间住院和死亡的421,460名普通健康保险制度的受益人(覆盖70%的法国人口)。结果1)独立性被定义为MD和​​UCD属于导致死亡的不同事件序列2)在自动分析的死亡中(91.7%),医院内死亡为8.5%,院外死亡为19.5%分类为独立。老年患者以及出院-死亡时间间隔增加时独立性更为频繁(出院后30天内死亡的发生率为14.3%,6至12个月内死亡的发生率为27.7%)以及肿瘤以外的UCD。结论我们的算法可以识别出可以认为死亡与医院所治疗病理无关的病例。从分配给住院过程的死亡中排除这些死亡可能有助于改善院后死亡率指标。更一般而言,该方法有可能被开发并用于跨时间段或数据库的其他诊断比较。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号