Literature DB >> 31137955

What We Can Learn From Failure: An EHR-Based Child Protection Alert System.

Conrad Krawiec1, Seth Gerard2, Sarah Iriana3, Rachel Berger4, Benjamin Levi3,5.   

Abstract

This study aimed to evaluate the efficacy of a newly implemented Child Protection Alert System (CPAS) that utilizes triggering diagnoses to identify children who have been confirmed/strongly suspected as maltreated. We retrospectively reviewed electronic health records (EHRs) of 666 patients evaluated by our institution's child protection team between 2009 and 2014. We examined each EHR for the presence of a pop-up alert, a persistent text-based visual alert, and diagnoses denoting child maltreatment. Diagnostic accuracy of the CPAS for child maltreatment identification was assessed. Of 323 patients for whom child maltreatment was confirmed/strongly suspected, 21.7% (70/323) had a qualifying longitudinal diagnosis listed. The pop-up alert fired in 14% of cases (45/323) with a sensitivity and specificity of 13.9% (95% CI [10.4%, 18.2%]) and 100% (95% CI [98.9%, 100.0%]), respectively. The text-based visual alert displayed in 44 of 45 cases. The CPAS is a novel simple way to support clinical decision-making to identify and protect children at risk of (re)abuse. This study highlights multiple barriers that must be overcome to effectively design and implement a CPAS to protect at-risk children.

Entities:  

Keywords:  abuse; decision-making; prevention

Mesh:

Year:  2019        PMID: 31137955     DOI: 10.1177/1077559519848845

Source DB:  PubMed          Journal:  Child Maltreat        ISSN: 1077-5595


  3 in total

1.  Developing machine learning-based models to help identify child abuse and neglect: key ethical challenges and recommended solutions.

Authors:  Aviv Y Landau; Susi Ferrarello; Ashley Blanchard; Kenrick Cato; Nia Atkins; Stephanie Salazar; Desmond U Patton; Maxim Topaz
Journal:  J Am Med Inform Assoc       Date:  2022-01-29       Impact factor: 4.497

Review 2.  Electronic Health Record Tools to Identify Child Maltreatment: Scoping Literature Review and Key Informant Interviews.

Authors:  Laura Stilwell; Megan Golonka; Kristin Ankoma-Sey; Madeleine Yancy; Samantha Kaplan; Lindsay Terrell; Elizabeth J Gifford
Journal:  Acad Pediatr       Date:  2022-02-04       Impact factor: 2.993

3.  Predictive value of indicators for identifying child maltreatment and intimate partner violence in coded electronic health records: a systematic review and meta-analysis.

Authors:  Shabeer Syed; Rachel Ashwick; Marco Schlosser; Arturo Gonzalez-Izquierdo; Leah Li; Ruth Gilbert
Journal:  Arch Dis Child       Date:  2020-08-11       Impact factor: 3.791

  3 in total

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