JMIR Publications

ABSTRACT

Background:

Electronic clinical decision support (CDS) can improve the recognition of child physical abuse.

Objective:

We sought to develop and test the usability of a natural language processing-based child abuse CDS system, known as the CA-CDS, to alert emergency department (ED) clinicians to high-risk injuries suggestive of abuse in infants’ charts.

Methods:

Informed by available evidence, a multidisciplinary team, including an expert in user design, developed a CA-CDS prototype that provided evidence-based recommendations for evaluation and management of suspected child abuse when triggered by documentation of a high-risk injury. Content was customized for medical versus nursing providers and initial versus subsequent exposure to the alert. To assess usability and refine the CA-CDS, we interviewed twenty-four clinicians from four EDs about their interactions with the prototype. Interview transcripts were coded and analyzed using conventional content analysis.

Results:

Five main categories emerged: 1. CA-CDS benefits included providing an extra layer of protection, evidence-based recommendations, and alerting the entire clinical ED team. 2. User-centered, workflow-compatible design included soft-stop alert configuration, editable and automatic documentation, and attention-grabbing formatting. 3. Recommendations for improvement included consolidating content, clearer design elements, and adding a hyperlink with additional resources. 4. Barriers to future implementation included alert fatigue, hesitancy to change, and concerns around documentation. 5. Facilitators of future implementation included stakeholder buy-in, provider education, and sharing test characteristics. Based on user feedback, iterative modifications were made to the prototype.

Conclusions:

With its user-centered design, the CA-CDS can aid providers in the real-time recognition and evaluation of infant physical abuse.