Underestimated prevalence of heart failure in hospital inpatients: a comparison of ICD codes and discharge letter information.
Underestimated prevalence of heart failure in hospital inpatients: a comparison of ICD codes and discharge letter information.
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DOI：
10.1007/s00392-018-1245-z
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发表时间：
2018-09
期刊：
影响因子：
--
通讯作者：
Störk S
中科院分区：
文献类型：
--
作者：
Kaspar M;Fette G;Güder G;Seidlmayer L;Ertl M;Dietrich G;Greger H;Puppe F;Störk S
心力衰竭是住院的主要原因，也是德国的主要死亡原因之一。然而，缺乏对流行率和发病率的准确估计。来自不同信息来源的报告数字受到经济原因或文件质量等因素的影响。我们实现了一个临床数据仓库，它集成了各种信息源（结构化参数，纯文本，通过自然语言处理提取的数据），并使可靠的近似心力衰竭患者的真实的数量。比较了2000-2015年期间基于ICD的诊断在检测心力衰竭方面的性能，（a）基于集成医院信息系统各种来源的算法的高级定义，和（B）基于医生的参考标准。应用这些方法检测住院患者的心力衰竭显示，依赖ICD代码导致心力衰竭的真实患病率明显低估，范围从验证数据集中的44%到总体分析中的55%（单年）和31%（所有年份）。随着时间的推移，数据发生了变化，这表明编码实践和效率发生了长期变化。从最初的专家指定的查询（F1得分为81%）到计算机优化的查询（F1得分为86%），或者根据搜索目标优化精度或灵敏度，使用搜索和排列算法显着提高了性能。使用ICD编码作为唯一的数据来源来估计心力衰竭的患病率产生了不可靠的结果。诊断准确性显着提高使用专用搜索算法。我们的方法可以推广到其他医院的信息系统。
Heart failure is the predominant cause of hospitalization and amongst the leading causes of death in Germany. However, accurate estimates of prevalence and incidence are lacking. Reported figures originating from different information sources are compromised by factors like economic reasons or documentation quality. We implemented a clinical data warehouse that integrates various information sources (structured parameters, plain text, data extracted by natural language processing) and enables reliable approximations to the real number of heart failure patients. Performance of ICD-based diagnosis in detecting heart failure was compared across the years 2000–2015 with (a) advanced definitions based on algorithms that integrate various sources of the hospital information system, and (b) a physician-based reference standard. Applying these methods for detecting heart failure in inpatients revealed that relying on ICD codes resulted in a marked underestimation of the true prevalence of heart failure, ranging from 44% in the validation dataset to 55% (single year) and 31% (all years) in the overall analysis. Percentages changed over the years, indicating secular changes in coding practice and efficiency. Performance was markedly improved using search and permutation algorithms from the initial expert-specified query (F1 score of 81%) to the computer-optimized query (F1 score of 86%) or, alternatively, optimizing precision or sensitivity depending on the search objective. Estimating prevalence of heart failure using ICD codes as the sole data source yielded unreliable results. Diagnostic accuracy was markedly improved using dedicated search algorithms. Our approach may be transferred to other hospital information systems.
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