ArticleJournal of medical Internet research2019
Online Ratings of Urologists: Comprehensive Analysis.
Article in Journal of medical Internet research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Data Quality Issues With Physician-Rating Websites: Systematic Review.Journal of medical Internet research · 2020Pooled it
- Coverage, Traits, and Geographic Distribution of Online Surgeon Reviews: Large-Scale Cross-Sectional Analysis.JMIR formative research · 2026Article
- Differences of patient empowerment between elective and contracted physicians in internal medicine in Austria: a quantitative content analysis.BMC health services research · 2025Article
- Article
- Online patient ratings in ophthalmology.Indian journal of ophthalmology · 2023Article
- Patient-Centered Insights and Biases Regarding Cardiologists Via Online Review Platform Analysis.Journal of the American Heart Association · 2023Article
- Quantifying the relationship between specialisation and reputation in an online platform.Scientific reports · 2022Article
- Experiences and Challenges of Emerging Online Health Services Combating COVID-19 in China: Retrospective, Cross-Sectional Study of Internet Hospitals.JMIR medical informatics · 2022Article
- One Decade of Online Patient Feedback: Longitudinal Analysis of Data From a German Physician Rating Website.Journal of medical Internet research · 2021Article
- Digital Footprint of Academic Vascular Surgeons in the Southern United States on Physician Rating Websites: Cross-sectional Evaluation Study.JMIR cardio · 2021Article
- Factors Associated With the Actual Behavior and Intention of Rating Physicians on Physician Rating Websites: Cross-Sectional Study.Journal of medical Internet research · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPhysician-rating websites are being increasingly used by patients to help guide physician choice. As such, an understanding of these websites and factors that influence ratings is valuable to physicians.
objectiveWe sought to perform a comprehensive analysis of online urology ratings information, with a specific focus on the relationship between number of ratings or comments and overall physician rating.
methodsWe analyzed urologist ratings on the Healthgrades website. The data retrieval focused on physician and staff ratings information. Our analysis included descriptive statistics of physician and staff ratings and correlation analysis between physician or staff performance and overall physician rating. Finally, we performed a best-fit analysis to assess for an association between number of physician ratings and overall rating.
resultsFrom a total of 9921 urology profiles analyzed, there were 99,959 ratings and 23,492 comments. Most ratings were either 5 ("excellent") (67.53%, 67,505/99,959) or 1 ("poor") (24.22%, 24,218/99,959). All physician and staff performance ratings demonstrated a positive and statistically significant correlation with overall physician rating (P<.001 for all analyses). Best-fit analysis demonstrated a negative relationship between number of ratings or comments and overall rating until physicians achieved 21 ratings or 6 comments. Thereafter, a positive relationship was seen.
conclusionsIn our study, a dichotomous rating distribution was seen with more than 90% of ratings being either excellent or poor. A negative relationship between number of ratings or comments and overall rating was initially seen, after which a positive relationship was demonstrated. Combined, these data suggest that physicians can benefit from understanding online ratings and that proactive steps to encourage patient rating submissions may help optimize overall rating.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.