P6. A BIG DATA APPROACH TO UNDERSTANDING PATIENT SATISFACTION WITH MASTOPEXY SURGERY

Abstract

PURPOSE: A physician’s online footprint is becoming increasingly important in the age of social media. Therefore, understanding what drives patient satisfaction and behavior on social media is paramount to increasing patient satisfaction and maintaining a pristine online image. This study utilizes data obtained from Realself.com, a social media platform that allows patients to leave reviews of their plastic surgery experiences, to further elucidate the drivers behind patient satisfaction. METHODS: Patient reviews from the ‘Mastopexy’ category of Realself.com were collected using Scrapy, a python web crawling software that collects textual data from websites. Patient review data includes star ratings 1-5 in overall rating and various subcategories, as well as a free text entry, and cost data. Each entry was manually reviewed and categorized. Additionally, multiple regression was performed to assess independent predictors of overall satisfaction on the overall experience. RESULTS: A total of 968 mastopexy reviews were collected, 85.6% positive and 14.4% negative. The most common reasons for positive experience were aesthetic appearance (66.5%) and good physician bedside manner (21.7%). Similarly, negative reviews also most frequently cited appearance(58.3%) and bedside manner (26.6%). Several independent predictors of overall satisfaction were identified. Physician bedside manner (p<0.001), after-care follow up(p<0.001), staff professionalism and courtesy(p=0.016) and wait times (p=0.011) were independently associated with a positive overall review. CONCLUSION: We found that physician bedside manner, after-care follow up, staff professionalism and courtesy and wait times are independent predictors of overall patient satisfaction. Understanding the importance of these factors will increase rates of patient satisfaction and improve their overall online footprint.