DNP Capstone Defense - Naomi May Souza

Tuesday, March 25, 2025 at 3:00pm to 5:00pm

Project Title:

Utilization of an Artificial Intelligence (AI) Application in Psychiatric Mental Health Practitioners: Impact on Time Spent, Documentation, and Attitudes

Student name:
Naomi May Souza

Scholarly Project Committee:
Gulcan Bagcivan, PhD, RN, Faculty mentor, Chair
Natlie Correia, FNP-BC, DNP, Faculty mentor
Peeranuch LeSeure, Ph.D., RN, Second Reader
Valerie Seney, PhD, MA, LMHC, PMHNP-BC, FNAP, Residency Site Mentor

Date of Defense: March 25th
Time: 3pm-5pm 
via Zoom 

Abstract:

The healthcare system faces a provider shortage, with research linking burnout to electronic health record (EHR) documentation. This Doctoral Nurse Practitioner (DNP) project aimed to reduce documentation time and improve attitudes towards artificial intelligence (AI) by introducing an AI tool to psychiatric mental health nurse practitioners (PMHNPs) in outpatient clinics. Participants completed pre- and post-surveys assessing time spent on EHR documentation, documentation burden, and AI attitudes. The Burden of Documentation for Nurses and Midwives (BurDonsaM) and the Artificial Intelligence Attitude Scale (AIAS-4) were used for assessments. A follow-up survey collected feedback on the AI tool after the two-week intervention. Five PMHNPs participated in this project. Of the participants, 80% were female, 60% had been practicing for 1-4 years, 80% worked the day shift, saw 11 to 20 clients a day, had not used AI applications, and 40% spent 30 to 45 minutes documenting. The pre-qualitative data reported that participants had concerns about using AI applications and privacy, security, and transcription accuracy. The post-usage AI survey showed participants changed their initial concerns using AI applications. Participants stated that they found AI helpful in saving time for note-taking and reducing documentation burden. The pre- and post-BurDonsaM and AIAS-4 survey scores were not compared because it is not recommended with a small sample size of (n=5), which increases the risk of random error and could lead to misleading conclusions. Continued education and future studies are warranted to improve technology obstacles, reduce implementation barriers, and incorporate AI applications as the new status quo among PMHNPs.

ZOOM : Zoom link contact dhoffman@Umassd.edu
Deanna Hoffman
5089106487
dhoffman@umassd.edu