Using AI (Artificial Intelligence) to Identify Potential Workplace Violence Risk

  • Room: Potomac D
  • Session Number: 302
Monday, October 16, 2023: 11:30 AM - 12:30 PM

Speaker(s)

Faculty
Catherine Harris MSN, RN, NEA-BC
Director
Continuum Home Health/ Univ. of Virginia Health
Faculty
Ha Do Byon PhD, MPH, MS, RN
Assistant Professor
University of Virginia School of Nursing Family, Community & Mental Health Systems
Faculty
Mary Crandall PhD, RN
Nurse Scientist
University of Virginia Health System
Faculty
Max Topaz PhD, MA, RN, FAAN
Associate Professor of Nursing, Columbia University
VNS Health

Description

Workplace violence presents a unique challenge to home health, hospice, and private duty clinicians and their managers as the underreporting of violent incidents can have a dangerous impact on our clinicians. Our research investigated the use of natural language processing to help better identify violence incidents not reported to leadership. This session reviews research of nearly 600,000 home health clinical notes to identify type II workplace violence prevalence data and a comparative analysis of established reporting results. The researchers will review the innovative use of machine learning and the procedures to use natural language processing to help home health, hospice, and private duty agencies identify and address potential violence insight opportunities. The team will identify how automated algorithms were designed and discuss why this innovative use of technology can better inform agency leaders to help keep staff members safe.


Topic(s)


Methodology

Course Level: Intermediate; 1.2 Accounting CPEs (NASBA/PHR) 1 Nursing CNEs contact hours, 1 Nursing Home/Asst. Living Adm. CEs (NAB/NCERS)

Handout(s)


Additional Info

Learning Objective 1:
Identify management staff opportunities for protecting clinicians using machine learning/AI.

Learning Objective 2:
Identify the natural language processing used to identify workplace violence.

Learning Objective 3:
Discuss the results of the research and the opportunities to use the format of machine learning/AI to enhance clinician safety.

Primary Target Audience:
Home Health,Hospice