Sentiment Analysis of Online Patient-Written Reviews of Vascular Surgeons.

BACKGROUND

Online patient reviews influence a patient's choice of a vascular surgeon. The aim of this study is to examine underlying factors that contribute to positive and negative patient reviews by leveraging sentiment analysis and machine learning methods.

METHODS

The Society of Vascular Surgeons publicly accessible member directory was queried and cross-referenced with a popular patient-maintained physician review website, healthgrades.com. Sentiment analysis and machine learning methods were used to analyze several parameters. Demographics (gender, age, and state of practice), star rating (of 5 stars), and written reviews were obtained for corresponding vascular surgeons. A sentiment analysis model was applied to patient-written reviews and validated against the star ratings. Student's t-test or one-way analysis of variance assessed demographic relationships with reviews. Word frequency assessments and multivariable logistic regression analyses were conducted to identify common and determinative components of written reviews.

RESULTS

A total of 1,799 vascular surgeons had public profiles with reviews. Female gender of surgeon was associated with lower star ratings (male = 4.19, female = 3.95, P < 0.01) and average sentiment score (male = 0.50, female = 0.40, P < 0.01). Younger physician age was associated with higher star rating (P = 0.02) but not average sentiment score (P = 0.12). In the Best reviews, the most commonly used one-words were Care (N = 999), Caring (N = 767), and Kind (N = 479), while the most commonly used two-word pairs were Saved/Life (N = 189), Feel/Comfortable (N = 106), and Kind/Caring (N = 104). For the Worst reviews, the most commonly used one-words were Pain (N = 254) and Rude (N = 148), while the most commonly used two-word pairs were No/One (N = 27), Waste/Time (N = 25), and Severe/Pain (N = 18). In a multiple logistic regression, satisfactory reviews were associated with words such as Confident (odds ratio [OR] = 8.93), Pain-free (OR = 4.72), Listens (OR = 2.55), and Bedside Manner (OR = 1.70), while unsatisfactory reviews were associated with words such as Rude (OR = 0.01), Arrogant (OR = 0.09), Infection (OR = 0.20), and Wait (OR = 0.48).

CONCLUSIONS

Female surgeons received significantly worse reviews and younger surgeons tended to receive better reviews. The positivity and negativity of reviews were largely related to words associated with the patient-doctor experience and pain. Vascular surgeons should focus on these 2 areas to improve patient experiences and their own reviews.