The Extent of Consumer Product Involvement in Paediatric Injuries

Abstract

A challenge in utilising health sector injury data for Product Safety purposes is that clinically coded data have limited ability to inform regulators about product involvement in injury events, given data entry is bound by a predefined set of codes. Text narratives collected in emergency departments can potentially address this limitation by providing relevant product information with additional accompanying context. This study aims to identify and quantify consumer product involvement in paediatric injuries recorded in emergency department-based injury surveillance data. A total of 7743 paediatric injuries were randomly selected from Queensland Injury Surveillance Unit database and associated text narratives were manually reviewed to determine product involvement in the injury event. A Product Involvement Factor classification system was used to categorise these injury cases. Overall, 44% of all reviewed cases were associated with consumer products, with proximity factor (25%) being identified as the most common involvement of a product in an injury event. Only 6% were established as being directly due to the product. The study highlights the importance of utilising injury data to inform product safety initiatives where text narratives can be used to identify the type and involvement of products in injury cases.

Defective Assistive Device Involvement in Older Adult Emergency Department Visits

“…The 2 senior coders on the study team then verified and further classified the 317 potentially at-fault designations by using a more nuanced assessment of how the product contributed to the injury: Product Impact Factor (PIF) ( 14 ). PIF’s 8 assessment categories are shown in Supplementary Table 1A .…”

“…Past studies ( 14–16 ) have successfully used hospital narratives to draw valuable insight into the incidence rates of specific injury types in select, vulnerable populations. One study ( 14 ) used hospital narratives from the Queensland Injury Surveillance Unit to measure the extent of consumer product involvement in pediatric injuries.…”

“…Past studies ( 14–16 ) have successfully used hospital narratives to draw valuable insight into the incidence rates of specific injury types in select, vulnerable populations. One study ( 14 ) used hospital narratives from the Queensland Injury Surveillance Unit to measure the extent of consumer product involvement in pediatric injuries. Another study used hospital ED narratives, from the National Electronic Injury Surveillance System All Injury Program (NEISS-AIP) database, to quantify scald burn incidence among children under 3 years of age ( 15 ) and injuries associated with housing elements for children under 18 years of age ( 16 ).…”

Applying a public health approach to identify priorities for regulating child product safety

“…There are significant challenges with identifying product-related injury and emerging trends from Australian health datasets to detect unsafe products and inform reform strategies. 2,4,[12][13][14] Issues include the protracted time to access data from health datasets, a lack of clear identification of consumer products in health datasets and the need to text mine narratives to identify product involvement. However, notwithstanding these challenges, it is critical for evidence to inform policy and the health of vulnerable populations, and a precondition for advancing public safety and public health policy is the generation of more robust data.…”

“…Australia does not have a well‐established national injury surveillance system with only two states, Victoria and Queensland, conducting routine injury surveillance, and the National Coronial Information System partially fulfilling this function for deaths. There are significant challenges with identifying product‐related injury and emerging trends from Australian health datasets to detect unsafe products and inform reform strategies 2,4,12-14 . Issues include the protracted time to access data from health datasets, a lack of clear identification of consumer products in health datasets and the need to text mine narratives to identify product involvement.…”