scholarly journals Academic Rhinologists’ Online Rating and Perception, Scholarly Productivity, and Industry Payments

2020 ◽  
pp. 194589242095836
Author(s):  
Khodayar Goshtasbi ◽  
Brandon M. Lehrich ◽  
Mehdi Abouzari ◽  
Dariush Bazyani ◽  
Arash Abiri ◽  
...  

Introduction The emergence of popular online rating websites, social media platforms, and public databases for industry payments and scholarly outputs provide a complete physician online presence which may guide choice and satisfaction. Methods Websites of all U.S. otolaryngology academic institutions were queried for fellowship-trained rhinologists. Additional well-known and academically active rhinologists were identified by the senior author. Online ratings and comments were collected from Google, Healthgrades, Vitals, and RateMD websites, and weighted rating scores (RS) were calculated on a 1–5 scale. Results A total of 210 rhinologists with 16 ± 9 years of practice were included, where 6901 online ratings (33 ± 47 per rhinologist) provided an average RS of 4.3 ± 0.6. RS was not different according to gender ( p = 0.58), geographic quartile ( p = 0.48), social media presence ( p = 0.41), or attending top-ranked medical school ( p = 0.86) or residency programs ( p = 0.89). Years of practice negatively correlated with RS (R = –0.22, p<0.01), and academic ranking significantly influenced RS, with professors, associate professors, and assistant professors scoring 4.1 ± 0.6, 4.3 ± 0.4, and 4.4 ± 0.6, respectively ( p = 0.03). Of the 3,304 narrative comments analyzed (3.1 ± 11.6 per rhinologist), 76% (positive) and 7% (negative) had elements of clinical knowledge/outcomes, 56% (positive) and 7% (negative) of communication/bedside manner, and 9% (positive) and 7% (negative) of office staff, cost, and wait-time. All negative comment categories had moderate negative correlation with RS, while positive comment categories regarding knowledge/competence and bedside manner weakly correlated with higher RS. Number of publications (48 ± 54) positively correlated with 2018 industry payments ($11,384 ± $19,025) among those receiving industry compensation >$300 (n = 113). Attending a top-ranked medical school was associated with higher industry payments ( p<0.01) and H-index ( p = 0.02). Conclusion Academic rhinologists’ online RS was not associated with gender, geographic location, or attending a top-ranked training program, and their scholarly productivity was significantly correlated with total industry payments.

2021 ◽  
pp. 000348942110059
Author(s):  
Krystyne Basa ◽  
Nicolette Jabbour ◽  
Matthew Rohlfing ◽  
Sarah Schmoker ◽  
Claire M. Lawlor ◽  
...  

Objectives: This study compares hospital-generated online ratings to patient-generated online ratings in academic otolaryngology and evaluates physician factors influencing these results. Methods: Websites of academic otolaryngologists were assessed for inclusion of hospital-generated Press Ganey surveys. Corresponding scores on Healthgrades and Vitals.com were identified via internet search. Hospital ratings were compared with patient-generated ratings, including score, demographics, and number of ratings. All data was collected between July 15th 2019 and August 22nd 2019. Results: 742 academic otolaryngologists with hospital-generated ratings were identified. Mean hospital-generated rating was significantly higher ((4.70, 95% CI 4.69-4.72) than patient-generated rating (Vitals:4.26, 95% CI 4.18-4.34, and Healthgrades:4.02, 95% CI 3.87-4.18; P < .001). In patient-generated rating, an increased number of rating scores (>20) was associated with male gender, professor ranking, and >30 years in practice ( P < .005). Physician demographics did not impact number of ratings in hospital-generated setting. With patient-generated, lower aggregate score was associated with professor ranking ( P = .001). In hospital-generated, lower score was associated with >30+ years in practice ( P = .023). Across all platforms, comprehensive otolaryngologists and neurotologists/otologists were rated lower in comparison to other specialties (PGS: P < .001,Vitals: P = .027,Healthgrades: P = .016). Conclusion: Hospital-generated ratings yield higher mean scores than patient-generated platforms. Between sources, Healthgrades.com scores were lower than those of Vitals.com . Professors with >30 years of practice generated more reviews in patient-generated ratings, and these physicians were generally rated lower. Access to patient-generated ratings is universal and physicians should be aware of variability between online rating platforms as scores may affect referrals and practice patterns.


2021 ◽  
Vol 8 ◽  
pp. 237437352110077
Author(s):  
Daliah Wachs ◽  
Victoria Lorah ◽  
Allison Boynton ◽  
Amanda Hertzler ◽  
Brandon Nichols ◽  
...  

The purpose of this study was to explore patient perceptions of primary care providers and their offices relative to their physician’s philosophy (medical degree [MD] vs doctorate in osteopathic medicine [DO]), specialty (internal medicine vs family medicine), US region, and gender (male vs female). Using the Healthgrades website, the average satisfaction rating for the physician, office parameters, and wait time were collected and analyzed for 1267 physicians. We found female doctors tended to have lower ratings in the Midwest, and staff friendliness of female physicians were rated lower in the northwest. In the northeast, male and female MDs were rated more highly than DOs. Wait times varied regionally, with northeast and northwest regions having the shortest wait times. Overall satisfaction was generally high for most physicians. Regional differences in perception of a physician based on gender or degree may have roots in local culture, including proximity to a DO school, comfort with female physicians, and expectations for waiting times.


2021 ◽  
Author(s):  
Meenakshi Bhilwar ◽  
Suzanne A Boren ◽  
Kunal Bhatia

BACKGROUND Physician rating websites are gaining popularity, however, data on their usability and influence on healthcare quality is limited. OBJECTIVE to provide an overview of physician rating websites in the US and find answers for the following questions: 1. What are the most commonly studied/rated physician rating websites in the US? 2. Which specialty of physicians/providers are most commonly studied/rated? 3. How many physicians were rated on the studied PRWs? 4. What is the average number of ratings on these websites and are they positive or negative? 5. How does the profile of providers influence their rating? 6. How are PRWs associated with healthcare quality? 7. How PRWs are associated with patient-physician relationship? METHODS A systematic literature search was conducted through Medline for peer-reviewed articles in the English language on studies conducted in the US. RESULTS 33 articles published in peer-reviewed journals were included in the final review. Most of the studies were conducted on surgeons. A significant number of studies observed no correlation of online ratings with gender, geographic location, and years of experience. Additionally, no significant correlation was found between PRWs and healthcare quality. CONCLUSIONS It has been observed that with the current structure of these websites, the reliability of information available on them is rather questionable, and hence more research is required to assess the credibility of these websites along with their cost-effectiveness, effect on the patient-physician relationship, and quality of healthcare delivery.


Author(s):  
Kristina Heinonen

Consumers are increasingly consuming, participating, contributing, and sharing different types of online content. This is influencing the marketing activities traditionally controlled and performed by companies. The aim of this chapter is to conceptualize the activities consumers perform in social media. Social media denote content created by individual consumers such as online ratings or verbal reviews, online message boards/forums, photos/video sites, blogs, tags, and social networking sites. A conceptual framework for consumers' social media activities is developed and qualitatively substantiated. Social media activities are based on the motives for the activities, including information, social connection, and entertainment. The chapter contributes to research on social media and online communities by describing user behavior and motivations related to the user-created services. Managerially, the study deepens the understanding of different challenges related to users' activities on social media and the motivations associated with those activities.


2020 ◽  
Vol 66 (1) ◽  
pp. 55-65
Author(s):  
Alta Pavin Banović ◽  
Sanja Dravinski

The goal of the paper is to show the results of a research conducted among students of Medical School Osijek on the use of social media as tools for exchanging educational content with their teachers, which leads to a better adoption of the content and better grades. Teachers and students learn about social media through preventive programs. The research method is an online survey conducted in 10 class departments. Results: Modern social media used in teaching enable better communication between students and teachers, faster information flow and easier preparation of students for school as well as development of a positive attitude on the use of social media in the teaching process.


2012 ◽  
Vol 54 (1) ◽  
pp. 49-63 ◽  
Author(s):  
Stuart E. Levy ◽  
Wenjing Duan ◽  
Soyoung Boo

The hotel industry continues to develop strategies for addressing consumer-generated online reviews, and particularly responding to poor reviews, which can have a damaging effect on a hotel’s reputation. To gain a greater understanding of the dynamics of poor reviews, this study analyzed 1,946 one-star reviews from ten popular online review websites, as well as 225 management responses from eighty-six Washington, D.C., hotels. A comprehensive complaint framework found that the most common complaints related to front desk staff, bathroom issues, room cleanliness, and guestroom noise issues. Complaints were also analyzed by hotel characteristics, including chain-scale segments, and reviewer characteristics, including purpose of travel and geographic location. Examining the reviews, highly rated hotels often respond to online complaints with appreciation, apologies, and explanations for what had gone wrong. Compensation adjustments are rarely mentioned by any hotel. The increasingly prominent role of social media necessitates that hotels use online reviews for market research and service recovery opportunities, regardless of whether they respond publicly.


2017 ◽  
Vol 40 (3) ◽  
pp. 188-195 ◽  
Author(s):  
David Ackerman ◽  
Christina Chung

This article looks at how marketing student ratings of instructors and classes on online rating sites such as RateMyProfessor.com can be biased by prior student ratings of that class. Research has identified potential sources of bias of online student reviews administered by universities. Less has been done on the sources of bias inherent in a ratings site where those doing the rating can see prior ratings. To measure how student online ratings of a course can be influenced by existing online ratings, the study used five different prior ratings experiment conditions: mildly negative prior ratings, strongly negative prior ratings, mildly positive prior ratings, strongly positive prior ratings, and a control condition of no prior ratings. Results of this study suggest prior online ratings, both positive and negative, do affect subsequent online ratings and bias them. There are several implications. First, both negative and positive ratings can have an impact biasing subsequent ratings. Second, sometimes negative prior ratings must be strong in valence in order to bias subsequent ratings whereas even mildly positive ratings can have an impact. Last, this bias can potentially influence student course selection.


Author(s):  
M. Yu. Kataev ◽  
◽  
V. V. Orlova ◽  

Social media analysis has become ubiquitous at a quantitative and qualitative level due to the ability to study content from open social networks. This content is a rich source of data for the construction and analysis of the interaction of social network users when forming various groups, used not only for statistical calculations, social areas of analysis, but also in trade or for the development of recommendation systems. The large number of social media users results in a huge amount of unstructured data (by time, type of communication, type of message and geographic location). This article aims to discuss the problem of analyzing social networks and obtaining information from unstructured data. The article discusses information extraction methods, well-known software products and datasets.


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