Literature DB >> 9346058

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

H B Weiss1.   

Abstract

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.

Entities:  

Mesh:

Year:  1996        PMID: 9346058      PMCID: PMC1067644          DOI: 10.1136/ip.2.1.61

Source DB:  PubMed          Journal:  Inj Prev        ISSN: 1353-8047            Impact factor:   2.399


  6 in total

1.  Consumer product aspiration and ingestion in children: analysis of emergency room reports to the National Electronic Injury Surveillance System.

Authors:  J S Reilly; M A Walter
Journal:  Ann Otol Rhinol Laryngol       Date:  1992-09       Impact factor: 1.547

2.  Exposure corrected risk estimates for childhood product related injuries.

Authors:  Y D Senturia; H J Binns; K K Christoffel; R R Tanz
Journal:  Accid Anal Prev       Date:  1993-08

3.  Comparison of in-line skating injuries with rollerskating and skateboarding injuries.

Authors:  R A Schieber; C M Branche-Dorsey; G W Ryan
Journal:  JAMA       Date:  1994-06-15       Impact factor: 56.272

4.  Patterns of walker use and walker injury.

Authors:  M J Rieder; C Schwartz; J Newman
Journal:  Pediatrics       Date:  1986-09       Impact factor: 7.124

5.  The infant walker: an unappreciated household hazard.

Authors:  S Marcella; B McDonald
Journal:  Conn Med       Date:  1990-03

6.  Poison exposures and use of ipecac in children less than 1 year old.

Authors:  P Gaudreault; M A McCormick; P G Lacouture; F H Lovejoy
Journal:  Ann Emerg Med       Date:  1986-07       Impact factor: 5.721

  6 in total
  6 in total

1.  NEISS and child injury data.

Authors:  H B Weiss
Journal:  Inj Prev       Date:  1996-06       Impact factor: 2.399

2.  Who can give a pediatric trauma history for children injured in bicycle crashes?

Authors:  F K Winston; J Posner; E Alpern; C M Vivarelli; P R Gallagher; K N Shaw; A Cnaan
Journal:  Annu Proc Assoc Adv Automot Med       Date:  2000

3.  Comparing pediatric intentional injury surveillance data with data from publicly available sources: consequences for a public health response to violence.

Authors:  D A Stone; S J Kharasch; C Perron; K Wilson; B Jacklin; R D Sege
Journal:  Inj Prev       Date:  1999-06       Impact factor: 2.399

4.  Youth injury data in the Canadian Hospitals Injury Reporting and Prevention Program: do they represent the Canadian experience?

Authors:  W Pickett; R J Brison; S G Mackenzie; M Garner; M A King; T L Greenberg; W F Boyce
Journal:  Inj Prev       Date:  2000-03       Impact factor: 2.399

5.  The Public Health Challenge of Consumer Non-Compliance to Toy Product Recalls and Proposed Solutions.

Authors:  Xiayang Yu; David C Schwebel
Journal:  Int J Environ Res Public Health       Date:  2018-03-17       Impact factor: 3.390

6.  An evaluation of comparability between NEISS and ICD-9-CM injury coding.

Authors:  Meghan C Thompson; Krista K Wheeler; Junxin Shi; Gary A Smith; Huiyun Xiang
Journal:  PLoS One       Date:  2014-03-21       Impact factor: 3.240

  6 in total

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