A Cost Analysis of a Validated Screening Tool for Pediatric Abusive Head Trauma

Cohrs, Austin C.; Agbese, Edeanya; Leslie, Douglas L.; Hymel, Kent P.

doi:10.1007/s10826-017-0925-z

Cited by 2 publications

(1 citation statement)

References 19 publications

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“…However, several recent studies have considered the impact of case identification via clinical prediction rules. This includes assessing if the Predicting Abusive Head Trauma clinical prediction rule alters clinicians' abusive head trauma probability estimates [61], emergency clinicians' experience with using the Burns Risk Assessment for Neglect or Abuse Tool in an emergency department setting [62], and cost estimates for identification using the Pediatric Brain Injury Research Network clinical predication rule as compared to assessment as usual [63]. Additional research on these clinical predication rules may determine if such rules are more accurate than a clinician's intuitive estimation of risk factors for potential maltreatment or how the tool impacts patient-important outcomes.…”

Section: Discussionmentioning

confidence: 99%

Identifying children exposed to maltreatment: a systematic review update

et al. 2020

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Background: Child maltreatment affects a significant number of children globally. Strategies have been developed to identify children suspected of having been exposed to maltreatment with the aim of reducing further maltreatment and impairment. This systematic review evaluates the accuracy of strategies for identifying children exposed to maltreatment. Methods: We conducted a systematic search of seven databases: Medline, Embase, PsycINFO, Cumulative Index to Nursing and Allied Health Literature, Cochrane Libraries, Sociological Abstracts and the Education Resources Information Center. We included studies published from 1961 to July 2, 2019 estimating the accuracy of instruments for identifying potential maltreatment of children, including neglect, physical abuse, emotional abuse, and sexual abuse. We extracted data about accuracy and narratively synthesised the evidence. For five studies-where the population and setting matched known prevalence estimates in an emergency department setting-we calculated false positives and negatives. We assessed risk of bias using QUADAS-2. Results: We included 32 articles (representing 31 studies) that evaluated various identification strategies, including three screening tools (SPUTOVAMO checklist, Escape instrument, and a 6-item screening questionnaire for child sex trafficking). No studies evaluated the effects of identification strategies on important outcomes for children. All studies were rated as having serious risk of bias (often because of verification bias). The findings suggest that use of the SPUTOVAMO and Escape screening tools at the population level (per 100,000) would result in hundreds of children being missed and thousands of children being over identified. Conclusions: There is low to very low certainty evidence that the use of screening tools may result in high numbers of children being falsely suspected or missed. These harms may outweigh the potential benefits of using such tools in practice (PROSPERO 2016:CRD42016039659).

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Section: Discussionmentioning

confidence: 99%