Automated comparison of last hospital main diagnosis and underlying cause of death ICD10 codes, France, 2008-2009
Automated comparison of last hospital main diagnosis and underlying cause of death ICD10 codes, France, 2008-2009
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DOI：
10.1186/1472-6947-14-44
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发表时间：
2014-06-05
影响因子：
3.5
通讯作者：
Rey, Gregoire
中科院分区：
文献类型：
--
作者：
Lamarche-Vadel, Agathe;Pavillon, Gerard;Rey, Gregoire
背景：在医疗保健大数据时代，大规模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）正式定义和识别在生命的最后一年住院的死亡受试者的最后一次住院主要诊断（MD）和死亡登记的潜在死亡原因（UCD）之间的独立性; 2）根据社会人口统计学和医疗管理变量研究它们的分布; 3）讨论这种方法在医院护理质量评估的特定背景下的利益。1）以基于国际标准的编码系统Iris为依托，提出了一种比较MD和UCD的算法。2)向421 460名普通健康保险受益人适用2008- 2009年期间，法国人口的70%在此期间住院和死亡。1）独立性，定义为MD和UCD属于不同的导致死亡的事件序列2）在自动分析的死亡中（91.7%），8.5%的院内死亡和19.5%的院外死亡被归类为独立死亡。独立性是更常见的老年患者，以及当出院死亡时间间隔增长（14.3%时，死亡发生在出院后30天内，27.7%在6至12个月内）和UCDs以外的肿瘤。结论：我们的算法可以确定的情况下，死亡可以被认为是独立的病理在医院治疗。将这些死亡从分配给住院过程的死亡中排除可能有助于改善住院后死亡率指标。更一般地说，这种方法有可能被开发和用于跨时间段或数据库的其他诊断比较。
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.