Date of Completion

2026

Document Type

Thesis

Degree Name

Bachelor of Science in Physical Therapy

Keywords

Artificial Intelligence, AI-assisted documentation, Physical Therapy interns, Telehealth

Abstract

In clinical practice, physical therapy interns are required to balance patient management with accurate and timely documentation. However, completing documentation during patient consultations can be challenging, affecting workflow efficiency. With the increasing use of artificial intelligence (AI) in healthcare, AI-assisted documentation systems have been introduced to help interns organize patient information and support the documentation process. Thus, this study aimed to determine the use of Artificial Intelligence-based PT documentation in improving the accuracy and usability of physical therapy documentation within the Telehealth Care Coordinating Unit. In this study, usability is operationalized through two components: efficiency and intern satisfaction. Using a descriptive quantitative research design, the study utilized the adapted tools, PDQI-9 and EHRQAAT (accuracy), and Health-ITUES to determine usability, specifically its subdomain efficiency and intern satisfaction, which were distributed to the TCCU interns and faculty. Results for accuracy and usability showed overall mean scores of 4.31 (SD = 0.69) and 3.99 (SD = 1.15), respectively, with the variability of responses ranging from moderate to high accuracy and usability, which were somewhat consistent. These findings, overall, suggested that AI has good usability features with minor usability gaps related to user control, system integration within existing workflows, and variability in intern satisfaction, which requires refinement to further improve the documentation quality and overall user experience.

First Advisor

Aljin E. Nepomuceno

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