How an automated patient education module improves patient outcomes and informs the quality-of-care measures for providers within a minimally invasive aesthetic medicine practice.

WCU Author/Contributor (non-WCU co-authors, if there are any, appear on document)
Wendi L Harper-Lonabaugh (Creator)
Institution
Western Carolina University (WCU )
Web Site: http://library.wcu.edu/
Advisor
Angie Trombley

Abstract: Background: This quality improvement project was implemented to meet the needs of aesthetic patients and providers by providing automated education before the patient comes in for treatment. Objectives: To create an automated patient education module that provides consistent, accurate, uniform information to every patient who views it, which in, turn would give providers more time to treat the patient, generating greater revenue. Methods: Three surveys were used along with electronic health records (EHR) metrics, indicating patient check in and out times prior to and over the duration of the six-week study. Descriptive statistics were used to examine the demographics of aesthetic patients. Two-tailed Mann-Whitney U tests were run on both check-in/out times and revenue. There were 201 patient visits six weeks before the study and 316 patient visits during the study. Results: The demographics showed expected trends. The most common treatment sought was a neurotoxin, followed by dermal filler. Most patients had at least some college education, were female, and were married. The highest age group was age 50- to 59-year-olds. The change in check-in and out times was significant (alpha value of .05, U= 23417.5 and p < .001), and appointments got shorter. Revenue made was also significant (alpha value of .05, U= 3215 and p < .037). Conclusions: There was improvement of patient understanding before being treated. A longer study with a greater number of patients will be needed to better correlate the trends of how this impacts provider time spent with patients and practice revenue.

Additional Information

Publication
Dissertation
Language: English
Date: 2022
Keywords
aesthetic medicine, aesthetic patient education, automated education, cosmetic injectables, cosmetic patient learning, minimally invasive aesthetic medicine
Subjects
Surgery, Plastic
Surgery, Elective
Patient education
Web-based instruction

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