title: A large-scale quantitative analysis of latent factors and sentiment in online doctor reviews.
abstract: Online physician reviews are a massive and potentially rich source of information capturing patient sentiment regarding healthcare. We analyze a corpus comprising nearly 60,000 such reviews with a state-of-the-art probabilistic model of text. We describe a probabilistic generative model that captures latent sentiment across aspects of care (eg, interpersonal manner). We target specific aspects by leveraging a small set of manually annotated reviews. We perform regression analysis to assess whether model output improves correlation with state-level measures of healthcare. We report both qualitative and quantitative results. Model output correlates with state-level measures of quality healthcare, including patient likelihood of visiting their primary care physician within 14 days of discharge (p=0.03), and using the proposed model better predicts this outcome (p=0.10). We find similar results for healthcare expenditure. Generative models of text can recover important information from online physician reviews, facilitating large-scale analyses of such reviews.
authors.affiliation: Department of Health Services Policy & Practice, Brown University, Providence, Rhode Island, USA.
authors.forename: Byron C
authors.initials: BC
authors.lastname: Wallace
authors.affiliation: Department of Computer Science, Johns Hopkins University, Baltimore, Maryland, USA.
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Paul
authors.affiliation: Department of Medicine, UCSF, San Francisco, California, USA.
authors.forename: Urmimala
authors.initials: U
authors.lastname: Sarkar
authors.affiliation: Department of Health Services Policy & Practice, Brown University, Providence, Rhode Island, USA.
authors.forename: Thomas A
authors.initials: TA
authors.lastname: Trikalinos
authors.affiliation: Johns Hopkins University, Human Language Technology Center of Excellence, Baltimore, Maryland, USA.
authors.forename: Mark
authors.initials: M
authors.lastname: Dredze
mesh_terms: D020407:Internet; D015233:Models, Statistical; D017060:Patient Satisfaction; D010817:Physician-Patient Relations; D010820:Physicians / Q000592:standards*; D011787:Quality of Health Care; D012044:Regression Analysis; D014481:United States
keywords: natural language processing; physician reviews; social media; topic modeling