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从全科医疗的电子病历中估算发病率。一种分组系统的评估。

Estimating morbidity rates from electronic medical records in general practice. Evaluation of a grouping system.

作者信息

Biermans M C J, Verheij R A, de Bakker D H, Zielhuis G A, de Vries Robbé P F

机构信息

Department of Medical Informatics, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands.

出版信息

Methods Inf Med. 2008;47(2):98-106.

Abstract

OBJECTIVES

In this study, we evaluated the internal validity of EPICON, an application for grouping ICPC-coded diagnoses from electronic medical records into episodes of care. These episodes are used to estimate morbidity rates in general practice.

METHODS

Morbidity rates based on EPICON were compared to a gold standard; i.e. the rates from the second Dutch National Survey of General Practice. We calculated the deviation from the gold standard for 677 prevalence and 681 incidence rates, based on the full dataset. Additionally, we examined the effect of case-based reasoning within EPICON using a comparison to a simple, not case-based method (EPI-0). Finally, we used a split sample procedure to evaluate the performance of EPICON.

RESULTS

Morbidity rates that are based on EPICON deviate only slightly from the gold standard and show no systematic bias. The effect of case-based reasoning within EPICON is evident. The addition of case-based reasoning to the grouping system reduced both systematic and random error. Although the morbidity rates that are based on the split sample procedure show no systematic bias, they do deviate more from the gold standard than morbidity rates for the full dataset.

CONCLUSIONS

Results from this study indicate that the internal validity of EPICON is adequate. Assuming that the standard is gold, EPICON provides valid outcomes for this study population. EPICON seems useful for registries in general practice for the purpose of estimating morbidity rates.

摘要

目的

在本研究中,我们评估了EPICON的内部效度,EPICON是一种用于将电子病历中ICPC编码的诊断分组为照护事件的应用程序。这些事件用于估计全科医疗中的发病率。

方法

将基于EPICON的发病率与金标准进行比较;即第二次荷兰全国全科医疗调查的发病率。我们根据完整数据集计算了677个患病率和681个发病率与金标准的偏差。此外,我们通过与一种简单的、非基于病例的方法(EPI-0)进行比较,研究了EPICON中基于病例的推理的效果。最后,我们使用分割样本程序来评估EPICON的性能。

结果

基于EPICON的发病率与金标准的偏差很小,且无系统偏差。EPICON中基于病例的推理的效果很明显。在分组系统中加入基于病例的推理减少了系统误差和随机误差。虽然基于分割样本程序的发病率没有显示出系统偏差,但它们与完整数据集的发病率相比,与金标准的偏差更大。

结论

本研究结果表明EPICON的内部效度是足够的。假设该标准是金标准,则EPICON为本研究人群提供了有效的结果。EPICON似乎对全科医疗中的登记处估计发病率很有用。

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