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Limitations of child injury data from the CPSC's National Electronic Injury Surveillance System: the case of baby walker related data.

机译:来自美国消费品安全委员会国家电子伤害监视系统的儿童伤害数据的局限性:与婴儿学步车相关的数据。

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摘要

OBJECTIVES: The US Consumer Product Safety Commission's National Electronic Injury Surveillance System (NEISS) is a primary source for children's consumer product injury surveillance data in the US. Differing interpretations of the emergency department based NEISS baby walker data by various parties prompted this detailed examination, reclassification, and analysis of the NEISS data to explain these discrepancies. METHODS: Case selection was performed by searching the NEISS 1982-91 database for the baby walker product code and various text strings for children less than 24 months old. False negative and false positive cases were identified and reclassified. Adjusted population rates were computed and the types and locations of hospitals contributing to the sample were examined. RESULTS: One per cent false positive and 4% false negative misclassification rates were observed. In 1991, two children's hospitals reported 14% of the baby walker related injuries, though these hospitals made up just 2% of the sample frame. Through random allocation, one state currently contains four acute care hospitals and the only two children's hospitals reporting to the NEISS system. These six hospitals contributed 18% of the walker cases whereas the state represents only 3% of the US infant population. CONCLUSIONS: Misclassification in NEISS baby walker reports is minimal, with false negatives outweighing false positives. For trend analysis of product related injuries at the frequency of occurrence observed for baby walkers, NEISS suffers from low sensitivity due to sampling error. For children's injuries, NEISS' estimates have been affected by children's hospitals coming in and out of the sample and currently reflects a random geographic imbalance because one state contributes both of the reporting children's hospitals. To overcome these problems improved multiple product coding, a unique baby walker code, and stratification of children's hospitals in an enlarged NEISS sample is recommended.
机译:目标:美国消费品安全委员会的国家电子伤害监视系统(NEISS)是美国儿童消费品伤害监测数据的主要来源。各方对急诊科基于NEISS婴儿学步车数据的不同解释促使对NEISS数据进行了详细的检查,重新分类和分析,以解释这些差异。方法:通过搜索NEISS 1982-91数据库中的婴儿学步车产品代码和24个月以下儿童的各种文本字符串来进行病例选择。假阴性和假阳性病例已被识别并重新分类。计算调整后的人口比率,并检查构成样本的医院的类型和位置。结果:观察到1%的假阳性和4%假阴性的误分类率。 1991年,两家儿童医院报告了14%的婴儿学步车相关伤害,尽管这些医院仅占样本框架的2%。通过随机分配,一个州目前拥有四家急诊医院,并且仅有两家向NEISS系统报告的儿童医院。这六家医院贡献了步行者病例的18%,而该州仅占美国婴儿人口的3%。结论:NEISS婴儿学步车报告中的错误分类极少,假阴性超过假阳性。为了以婴儿学步车观察到的发生频率对产品相关的伤害进行趋势分析,由于采样误差,NEISS灵敏度较低。对于儿童的伤害,NEISS的估算受到进出样本的儿童医院的影响,目前反映出一个随机的地理失衡,因为一个州同时参与了两个报告儿童医院的工作。为克服这些问题,建议使用多种产品编码,独特的婴儿学步车编码,并在扩大的NEISS样本中对儿童医院进行分层。

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  • 作者

    Weiss, H. B.;

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  • 年度 1996
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  • 原文格式 PDF
  • 正文语种 en
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