Date of Award

Spring 3-22-2024

Document Type

Open Access Thesis

Degree Name

Master of Medical Science (MMSc)

First Advisor

Andrea Asnes, MD, MSW

Abstract

Suspected child abuse in emergency departments is best managed by a specialist team trained to distinguish abuse from non-abuse. Previous researchers have developed clinical decision support tools to aid frontline clinicians recognize often subtle signs of child abuse. However, little is published about the success of integration of these tools into clinical practice. Our objective is to explore the efficacy of a natural language processing tool developed and validated by researchers at Yale by measuring changes in referral rates to Yale’s child protection team before and after implementation of the tool in the form of electronic medical record alerts. This quality improvement study will use a non-randomized, pre-post design, with an intervention group consisting of one local emergency department, and eight intra-system community emergency departments as a nonequivalent control group. We hypothesize that the implementation of the natural language processing tool will increase referrals to the child protection team.

Comments

This is an open access thesis.

Open Access

This Article is Open Access

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