The Use of Recommendations on Physician Rating Websites: The Number of Raters Makes the Difference When Adjusting Decisions

Effect of Negative Online Reviews and Physician Responses on Health Consumers' Choice: Experimental Study

BACKGROUND

The COVID-19 pandemic has highlighted the importance of online medical services. Although some researchers have investigated how numerical ratings affect consumer choice, limited studies have focused on the effect of negative reviews that most concern physicians.

OBJECTIVE

This study aimed to investigate how negative review features, including proportion (low/high), claim type (evaluative/factual), and physician response (absence/presence), influence consumers' physician evaluation process under conditions in which a physician's overall rating is high.

METHODS

Using a 2×2×2 between-subject decision-controlled experiment, this study examined participants' judgment on physicians with different textual reviews. Collected data were analyzed using the t test and partial least squares-structural equation modeling.

RESULTS

Negative reviews decreased consumers' physician selection intention. The negative review proportion (β=-0.371, P<.001) and claim type (β=-0.343, P<.001) had a greater effect on consumers' physician selection intention compared to the physician response (β=0.194, P<.001). A high negative review proportion, factual negative reviews, and the absence of a physician response significantly reduced consumers' physician selection intention compared to their counterparts. Consumers' locus attributions on the negative reviews affected their evaluation process. Physician attribution mediated the effects of review proportion (β=-0.150, P<.001), review claim type (β=-0.068, P=.01), and physician response (β=0.167, P<.001) on consumer choice. Reviewer attribution also mediated the effects of review proportion (β=-0.071, P<.001), review claim type (β=-0.025, P=.01), and physician response (β=0.096, P<.001) on consumer choice. The moderating effects of the physician response on the relationship between review proportion and physician attribution (β=-0.185, P<.001), review proportion and reviewer attribution (β=-0.110, P<.001), claim type and physician attribution (β=-0.123, P=.003), and claim type and reviewer attribution (β=-0.074, P=.04) were all significant.

CONCLUSIONS

Negative review features and the physician response significantly influence consumer choice through the causal attribution to physicians and reviewers. Physician attribution has a greater effect on consumers' physician selection intention than reviewer attribution does. The presence of a physician response decreases the influence of negative reviews through direct and moderating effects. We propose some practical implications for physicians, health care providers, and online medical service platforms.

The Influence of Paid Memberships on Physician Rating Websites With the Example of the German Portal Jameda: Descriptive Cross-sectional Study

BACKGROUND

The majority of Germans see a deficit in information availability for choosing a physician. An increasing number of people use physician rating websites and decide upon the information provided. In Germany, the most popular physician rating website is Jameda.de, which offers monthly paid membership plans. The platform operator states that paid memberships have no influence on the rating indicators or list placement.

OBJECTIVE

The goal of this study was to investigate whether a physician's membership status might be related to his or her quantitative evaluation factors and to possibly quantify these effects.

METHODS

Physician profiles were retrieved through the search mask on Jameda.de website. Physicians from 8 disciplines in Germany's 12 most populous cities were specified as search criteria. Data Analysis and visualization were done with Matlab. Significance testing was conducted using a single factor ANOVA test followed by a multiple comparison test (Tukey Test). For analysis, the profiles were grouped according to member status (nonpaying, Gold, and Platinum) and analyzed according to the target variables-physician rating score, individual patient's ratings, number of evaluations, recommendation quota, number of colleague recommendations, and profile views.

RESULTS

A total of 21,837 nonpaying profiles, 2904 Gold, and 808 Platinum member profiles were acquired. Statistically significant differences were found between paying (Gold and Platinum) and nonpaying profiles in all parameters we examined. The distribution of patient reviews differed also by membership status. Paying profiles had more ratings, a better overall physician rating, a higher recommendation quota, and more colleague recommendations, and they were visited more frequently than nonpaying physicians' profiles. Statistically significant differences were found in most evaluation parameters within the paid membership packages in the sample analyzed.

CONCLUSIONS

Paid physician profiles could be interpreted to be optimized for decision-making criteria of potential patients. With our data, it is not possible to draw any conclusions of mechanisms that alter physicians' ratings. Further research is needed to investigate the causes for the observed effects.

A meta-analysis of the weight of advice in decision-making

The degree to which people take advice, and the factors that influence advice-taking, are of broad interest to laypersons, professionals, and policy-makers. This meta-analysis on 346 effect sizes from 129 independent datasets (N = 17, 296) assessed the weight of advice in the judge-advisor system paradigm, as well as the influence of sample and task characteristics. Information about the advisor(s) that is suggestive of advice quality was the only unique predictor of the overall pooled weight of advice. Individuals adjusted estimates by 32%, 37%, and 48% in response to advisors described in ways that suggest low, neutral, or high quality advice, respectively. This indicates that the benefits of compromise and averaging may be lost if accurate advice is perceived to be low quality, or too much weight is given to inaccurate advice that is perceived to be high quality. When examining the three levels of perceived quality separately, advice-taking was greater for subjective and uncertain estimates, relative to objective estimates, when information about the advisor was neutral in terms of advice quality. Sample characteristics had no effect on advice-taking, thus providing no evidence that age, gender, or individualism influence the weight of advice. The findings contribute to current theoretical debates and provide direction for future research.

Social Media in Hip Arthroscopy Is an Underused Resource That Enhances Physician Online Reputation

Purpose

To analyze the impact of professional social media (SM) presence, activity level, and physician practice–specific variables on online ratings and rating frequency for hip arthroscopists across 3 leading physician review websites (PRWs).

Methods

The Arthroscopy Association of North America and American Orthopaedic Society of Sports Medicine directories were queried to identify practicing hip arthroscopists. Physicians included were residency-trained surgeons practicing within the United States. Surgeon ratings, comments, and reviews were compiled from 3 PRWs (Google, Healthgrades, Vitals). Google searches assessed for professional Facebook, Twitter, and Instagram accounts and demographic information. Surgeons were considered active if they posted the month before data collection. Logistical regression and a univariate model analyzed effects of demographic factors and other variables on SM use and PRW statistics.

Results

In total, 555 surgeons met inclusion criteria (93.2% male, 6.8% female); 41% had a professional SM account (27.4% Facebook, 24.3% Twitter, 12.1% Instagram). Few surgeons with SM actively posted (30.5% Facebook, 43.7% Twitter, 37.3% Instagram). Surgeons with any SM had significantly greater number of ratings on all review websites (P < .001). Linear regression revealed academic physicians had lower number of ratings (P = .002) and average ratings (P < .001). Instagram users had an average 12.4 more ratings. Surgeons more likely to use SM resided in greater population cities (990 vs 490 [per 1,000]) with higher surgeon density (3.3 vs 2.2).

Conclusions

Most hip arthroscopists have no professional SM, and fewer frequently post content. SM presence significantly increases the number of ratings on PRWs but does not affect overall rating. Surgeons using SM practice in more populous cities with more competition. Academic surgeons had fewer ratings and lower average ratings. A professional Instagram account can increase the number of online ratings.

Clinical Relevance

Understanding how SM presence affects an orthopaedic surgeon’s practice may provide information on how surgeons best connect with patients.

Marketing Your Practice: Setting Yourself Apart in a Competitive Market, Online Reputation Building, and Managing Patient Experience/Satisfaction

The days of making a first impression when you meet your patients in person are numbered. Rather, in today's digital age, your prospective patients have likely already formed opinions about you and your practice before they meet you. And these opinions are largely influenced by the information they discover about you online. While you cannot completely control your personal brand or reputation as a physician, you can certainly try by controlling your online narrative: communicate your expertise and your value by effectively using social media, by regularly updating your practice website, and by proactively managing patient satisfaction reflected on physician rating websites. Set yourself apart in a competitive market today by building a strong digital presence.

Data Quality Issues With Physician-Rating Websites: Systematic Review

BACKGROUND

In recent years, online physician-rating websites have become prominent and exert considerable influence on patients' decisions. However, the quality of these decisions depends on the quality of data that these systems collect. Thus, there is a need to examine the various data quality issues with physician-rating websites.

OBJECTIVE

This study's objective was to identify and categorize the data quality issues afflicting physician-rating websites by reviewing the literature on online patient-reported physician ratings and reviews.

METHODS

We performed a systematic literature search in ACM Digital Library, EBSCO, Springer, PubMed, and Google Scholar. The search was limited to quantitative, qualitative, and mixed-method papers published in the English language from 2001 to 2020.

RESULTS

A total of 423 articles were screened. From these, 49 papers describing 18 unique data quality issues afflicting physician-rating websites were included. Using a data quality framework, we classified these issues into the following four categories: intrinsic, contextual, representational, and accessible. Among the papers, 53% (26/49) reported intrinsic data quality errors, 61% (30/49) highlighted contextual data quality issues, 8% (4/49) discussed representational data quality issues, and 27% (13/49) emphasized accessibility data quality. More than half the papers discussed multiple categories of data quality issues.

CONCLUSIONS

The results from this review demonstrate the presence of a range of data quality issues. While intrinsic and contextual factors have been well-researched, accessibility and representational issues warrant more attention from researchers, as well as practitioners. In particular, representational factors, such as the impact of inline advertisements and the positioning of positive reviews on the first few pages, are usually deliberate and result from the business model of physician-rating websites. The impact of these factors on data quality has not been addressed adequately and requires further investigation.