Influence of Health Literacy on Effects of Patient Rating Websites: Survey Study Using a Hypothetical Situation and Fictitious Doctors

Evaluating Pediatric Ophthalmic Care Using Sentiment Analysis of Physician Review Sites

PURPOSE

To assess patient satisfaction within pediatric ophthalmology and identify trends in patient sentiment.

METHODS

Pediatric ophthalmologists in the United States were identified using the American Association for Pediatric Ophthalmology and Strabismus member directory. Demographic data were recorded using publicly available websites. Online written reviews and Stars ratings were obtained from Healthgrades.com. A sentiment analysis package, Valence Aware Dictionary for Sentimental Reasoning (VADER), was used to generate a compound score of reviews, and word frequency analyses were applied.

RESULTS

A total of 377 pediatric ophthalmologists (2,640 online reviews) were evaluated. Physicians received an average of 4.22/5 Stars and a compound sentiment score of 0.56, indicating positive sentiment. No differences in scores were observed by gender or location, although physicians with fewer years in practice had higher Stars ratings compared to peers (P < .001). The three most common words in the word frequency analysis of all reviews were "surgery," "staff," and "time," with heavy emphasis on bedside manner and addressing patient concerns.

CONCLUSIONS

This study demonstrates overall high patient satisfaction in pediatric ophthalmology care, with differences in sentiment based on physician demographic features. The study highlights that patient perspective is influenced by non-clinical features of care. These data may be used by pediatric ophthalmologists seeking to improve health care delivery. [J Pediatr Ophthalmol Strabismus. 2024;61(3):211-218.].

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.

Using Sentiment Analysis to Understand What Patients Are Saying About Hand Surgeons Online

BACKGROUND

Physician review websites have influence on a patient's selection of a provider. Written reviews are subjective and difficult to quantitatively analyze. Sentiment analysis of writing can quantitatively assess surgeon reviews to provide actionable feedback for surgeons to improve practice. The objective of this study is to quantitatively analyze large subset of written reviews of hand surgeons using sentiment analysis and report unbiased trends in words used to describe the reviewed surgeons and biases associated with surgeon demographic factors.

METHODS

Online written and star-rating reviews of hand surgeons were obtained from healthgrades.com and webmd.com. A sentiment analysis package was used to calculate compound scores of all reviews. Mann-Whitney U tests were performed to determine the relationship between demographic variables and average sentiment score of written reviews. Positive and negative word and word-pair frequency analysis was also performed.

RESULTS

A total of 786 hand surgeons' reviews were analyzed. Analysis showed a significant relationship between the sentiment scores and overall average star-rated reviews (r2 = 0.604, P ≤ .01). There was no significant difference in review sentiment by provider sex; however, surgeons aged 50 years and younger had more positive reviews than older (P < .01). The most frequently used bigrams used to describe top-rated surgeons were associated with good bedside manner and efficient pain management, whereas those with the worst reviews are often characterized as rude and unable to relieve pain.

CONCLUSIONS

This study provides insight into both demographic and behavioral factors contributing to positive reviews and reinforces the importance of pain expectation management.

A sentiment analysis on online psychiatrist reviews to identify clinical attributes of psychiatrists that shape the therapeutic alliance

Background

While online reviews from physician rating websites are increasingly utilized by healthcare providers to better understand patient needs, it remains difficult to objectively identify areas for improvement in providing psychiatric care.

Objectives

To quantitatively characterize the sentiment of online written reviews of psychiatrists to determine clinical attributes that can be strengthened to improve psychiatrists' therapeutic alliance with their patients.

Materials and methods

Sentiment scores of 6,400 written reviews of 400 US-based psychiatrists on a US-based online physician rating website were obtained through a natural-language-processing-based sentiment analysis. Relationships among sentiment scores, average star ratings, and demographics were examined. Linguistic analyses determined words and bigrams that were highly associated with reviews with the most positive and negative sentiment.

Findings

Sentiment scores were significantly correlated with average star ratings of the psychiatrists (R = 0.737, p < 0.001). Psychiatrists who were younger (< 56 years old) and/or practiced in the Northeast had significantly higher average star ratings than those older and/or practicing in the Southwest. Frequency analysis showed that positive reviews most frequently contained "time" (N = 1,138) and "caring" (N = 784) while negative reviews most frequently contained "medication" (N = 495) and "time" (N = 379). Logistic regression analysis revealed that reviews were more likely to be considered positive when they included "great listener" (OR = 16.89) and "comfortable" (OR = 10.72) and more likely to be negative when they included "meds" (OR = 0.55) and "side effect" (OR = 0.59).

Conclusion

Psychiatrists who are younger and located in the Northeast receive more positive reviews; there may be potential for demographic bias among patient reviewers. Patients positively rate psychiatrists who make them feel heard and comfortable but negatively rate encounters centered around medications and their side effects. Our study lends quantitative evidence to support the importance of thorough and empathetic communication of psychiatrists in building a strong therapeutic alliance.

Physician Review Websites: Understanding Patient Satisfaction with Ophthalmologists Using Natural Language Processing

Introduction

The presence and influence of physician review websites (PRW) have increased significantly in the field of medicine. This study aims to better understand determinants of patient satisfaction and the sentiment of ophthalmologists using natural language processing of Healthgrades reviews.

Methods

Healthgrades is a PRW where patients submit verified reviews, containing a star rating and a narrative review, of US-based ophthalmologists. This was a quantitative observational study conducted on May 23, 2022. We identified associations between physician demographics and both the sentiment analysis scores of narrative reviews and star ratings using the Student's t-tests and one-way ANOVA tests. After natural language processing the reviews, a logistic regression explored the impacts of the most frequent words on the positivity of a given review.

Results

This study examined a total of 16700 reviews of 1125 ophthalmologists. Ophthalmologists of younger age and male gender received statistically significantly higher star ratings and sentiment analysis scores; analysis of location of practice did not affect scores. Textual analysis revealed that words describing the physician's personality, such as "friendly" and "caring," increased the likelihood of reviews being positive more than descriptors of the visit's effectiveness, such as "results" and "efficient."

Conclusion

Younger and male ophthalmologists received higher star ratings and sentiment analysis scores. Additionally, results indicated that words describing the ophthalmologist's pleasant personality and the visit's effectiveness most positively impacted a review, whereas descriptors of a wait or an unpleasant personality most negatively impacted a review.

Awareness of and interaction with physician rating websites: A cross-sectional study in Austria

To date, the digital assessment of service experiences represents a decisive process step of a feedback culture in numerous economic areas. In view of this digitalization of service assessments, the importance of Physician Rating Websites (PRWs) has also increased steadily in recent years. Even though these websites could be perceived as a powerful communication tool for the exchange of health specific information, the knowledge about whether and how different population segments use these portals has been limited so far. For this reason, our aim was to investigate the level of awareness regarding PRWs among the study population and to discover how users interact with this specific type of online portals. We performed an online survey including 558 participants. To ensure the attention and integrity of participants, attention checks were included in the questionnaire. Study participants who did not exceed the mentioned security levels were excluded from the study. Statistical analyses were carried out, using IBM SPSS Statistics 27. To illustrate the relationship between demographic variables and dependent variables, two tailed chi square tests were performed. Comparison of means and t-testing was used to investigate the relationship between psychographic variables and the dependent variables. In addition to that, the awareness levels regarding different rating portals were evaluated using descriptive methods. Our results suggest that the general awareness regarding PRWs is relatively high (75.6%, 423/558), especially among female (x21 = 9.880, P = .002), middle-aged (x29 = 26.810, P = .002), more highly educated (x24 = 19.038, P = .001), urban (x21 = 6.274, P = .012), digitally literate (t203 = 2.63, P = .009) individuals and particularly among respondents with a higher eHealth literacy (t203 = 2.37, P = .019). Even though more than three quarters of the respondents know that PRWs exist, compared to other rating platforms, they are only in the lower midfield. The upper ranks are taken by websites on which restaurant visits (98.9%, 552/558), hotel stays (97.7%, 545/558) or movies (95.5%, 533/558) can be rated. The most popular PRWs in Austria include Docfinder.at (31.3%, 175/558; 77.8%, 434/558) followed by the evaluation tools provided by Google.at (8.24%, 46/558; 70.3%, 392/558) and Herold.at (1.61%, 9/558; 44.8%, 250/558). In Austria, PRWs seem to be characterized by a high degree of interaction (89.2%, 498/558) with a wide variety of different types of interactions. While many respondents use PRWs to retrieve general information (83.2%, 464/558), there are significantly fewer who read physicians' reviews (60.9%, 340/558) and use this portal to select a physician (60.6%, 338/558). Respondents who have already rated a doctor themselves belong to the smallest group accounting for just 14.7% (82/558). Significant effects regarding the interaction with PRWs exist between different genders, ages, education levels, marital statuses, occupations and areas of living. In addition to that, respondents with better feelings towards the internet, greater digital literacy as well as a higher eHealth literacy were also characterized with a higher interaction rate regarding PRWs. According to the high level of awareness of and interaction with PRWs within our study population, PRWs appear to be a successful medium for health-related communication. Especially for female, middle-aged, more highly educated, urban and more technology savvy population segments, PRWs seem to represent an effective tool to support the health-specific decision-making process.

Building better pediatric surgeons: A sentiment analysis of online physician review websites

PURPOSE

Physician review websites are a heavily utilized patient tool for finding, rating, and reviewing surgeons. Natural language processing such as sentiment analysis provides a comprehensive approach to better understand the nuances of patient perception. This study utilizes sentiment analysis to examine how specific patient sentiments correspond to positive and negative experiences in online reviews of pediatric orthopedic surgeons.

METHODS

The online written reviews and star ratings of pediatric surgeons belonging to the Pediatric Orthopaedic Society of North America were obtained from healthgrades.com. A sentiment analysis package obtained compound scores of each surgeon's reviews. Inferential statistics analyzed relationships between demographic variables and star/sentiment scores. Word frequency analyses and multiple logistic regression analyses were performed on key terms.

RESULTS

A total of 749 pediatric surgeons (3830 total online reviews) were included. 80.8% were males and 33.8% were below 50 years of age. Male surgeons and younger surgeons had higher mean star ratings. Surgeon attributes including "confident" (p < 0.01) and "comfortable" (p < 0.01) improved the odds of positive reviews, while "rude" (p < 0.01) and "unprofessional" (p < 0.01) decreased these odds. Comments regarding "pain" lowered the odds of positive reviews (p < 0.01), whereas "pain-free" increased these odds (p < 0.01).

CONCLUSION

Pediatric surgeons who were younger, communicated effectively, eased pain, and curated a welcoming office setting were more likely to receive positively written online reviews. This suggests that a spectrum of interpersonal and ancillary factors impact patient experience and perceptions beyond surgical skill. These outcomes can advise pediatric surgeons on behavioral and office qualities that patients and families prioritize when rating/recommending surgeons online.

LEVEL OF EVIDENCE

IV.

The Impact of Social Influence on the Intention to Use Physician Rating Websites: Moderated Mediation Analysis Using a Mixed Methods Approach

BACKGROUND

Physician rating websites (PRWs) have become increasingly important in the cross-section between health and digitalization. Social influence plays a crucial role in human behavior in many domains of life, as can be demonstrated by the increase in high-profile influential individuals such as social media influencers (SMIs). Particularly in the health-specific environment, the opinion of family and friends has a significant influence on health-related decisions. However, so far, there has been little discussion about the role of social influence as an antecedent of behavioral intention to use PRWs.

OBJECTIVE

On the basis of theories of social psychology and technology acceptance and theories from the economic perspective, this study aimed to evaluate the impact of social influence on the behavioral intention to use PRWs.

METHODS

We conducted 2 studies by applying a mixed methods approach including a total of 712 participants from the Austrian population. The impact of social influence on the behavioral intention to use PRWs was investigated through linear regression and mediation and moderated mediation analysis using the PROCESS macro 4.0 in SPSS 27 (IBM Corp).

RESULTS

The 2 studies show similar results. In study 1, an experiment, no direct effect of social influence on the behavioral intention to use PRWs could be detected. However, an indirect effect of social influence on the behavioral intention to use PRWs via credibility (b=0.572; P=.005) and performance expectancy (b=0.340; P<.001) could be confirmed. The results of study 2, a cross-sectional study, demonstrate that social influence seems to have a direct impact on the behavioral intention to use PRWs (b=0.410; P<.001). However, when calculating the proposed mediation model, it becomes clear that this impact may partly be explained through the 2 mediator variables-credibility (b=0.208; P<.001) and performance expectancy (b=0.312; P<.001). In contrast to the observed direct and indirect effect, neither demographic nor psychographic variables have a significant moderating impact on the influencing chain in study 2.

CONCLUSIONS

This study provides an indication that social influence has at least an indirect impact on the behavioral intention to use PRWs. It was observed that this impact is exerted through credibility and performance expectancy. According to the findings of both studies, social influence has the potential to boost the use of PRWs. As a result, these web-based networks might be a promising future interface between health care and digitalization, allowing health care practitioners to gain a beneficial external impact while also learning from feedback. Social influence nowadays is not just limited to friends and family but can also be exerted by SMIs in the domain of PRW use. Thus, from a marketing perspective, PRW providers could think of collaborating with SMIs, and our results could contribute to stimulating discussion in this vein.

Factors Associated with the Patient/Client Use of Report Cards, Physician Rating Websites, Social Media, and Google for Hospital and Physician Selection: A Nationwide Survey

Objective: To explore the factors associated with the different uses of report cards, physician rating websites, social media, and Google, including awareness, physician finding, and decision-making based on reviews from the patient/client perspective. Methods: We used computer-assisted telephone interviews to conduct a nationwide representative survey in Taiwan. Results: The urbanization level of the area, income, and long-term health conditions were not associated with the three kinds of usage of the websites studied. Seeking health information was an important factor in the three kinds of website use. The employment industry was associated with awareness, and education level was associated with physician seeking and actions based on reviews. Conclusions: Different factors influenced the three kinds of usage: awareness, actual use (i.e., finding an appropriate physician), and decision-making based on reviews. Seeking health information is of primary importance regardless of how the websites are used. Practical implications: Policy-makers should focus on educating individuals working outside the health care sector to increase awareness of these websites and to assist individuals with low levels of education in increasing their use of these websites.

Examining the Determinants of Patient Perception of Physician Review Helpfulness across Different Disease Severities: A Machine Learning Approach

(1) Background. Patients are increasingly using physician online reviews (PORs) to learn about the quality of care. Patients benefit from the use of PORs and physicians need to be aware of how this evaluation affects their treatment decisions. The current work aims to investigate the influence of critical quantitative and qualitative factors on physician review helpfulness (RH). (2) Methods. The data including 45,300 PORs across multiple disease types were scraped from Healthgrades.com. Grounded on the signaling theory, machine learning-based mixed methods approaches (i.e., text mining and econometric analyses) were performed to test study hypotheses and address the research questions. Machine learning algorithms were used to classify the data set with review- and service-related features through a confusion matrix. (3) Results. Regarding review-related signals, RH is primarily influenced by review readability, wordiness, and specific emotions (positive and negative). With regard to service-related signals, the results imply that service quality and popularity are critical to RH. Moreover, review wordiness, service quality, and popularity are better predictors for perceived RH for serious diseases than they are for mild diseases. (4) Conclusions. The findings of the empirical investigation suggest that platform designers should design a recommendation system that reduces search time and cognitive processing costs in order to assist patients in making their treatment decisions. This study also discloses the point that reviews and service-related signals influence physician RH. Using the machine learning-based sentic computing framework, the findings advance our understanding of the important role of discrete emotions in determining perceived RH. Moreover, the research also contributes by comparing the effects of different signals on perceived RH across different disease types.

Patient Utilization of Online Information and its Influence on Orthopedic Surgeon Selection: Cross-sectional Survey of Patient Beliefs and Behaviors

Background

Patient attitudes and behavior are critical to understand owing to the increasing role of patient choice. There is a paucity of investigation into the perceived credibility of online information and whether such information impacts how patients choose their surgeons.

Objective

The purpose of this study was to explore the attitudes and behavior of patients regarding online information and orthopedic surgeon selection. Secondary purposes included gaining insight into the relative importance of provider selection factors, and their association with patient age and education level.

Methods

This was a cross-sectional study involving five multispecialty orthopedic surgery groups. A total of 329 patients who sought treatment by six different orthopedic surgeons were asked to anonymously answer a questionnaire consisting of 25 questions. Four questions regarded demographic information, 10 questions asked patients to rate the importance of specific criteria regarding the selection of their orthopedic surgeon (on a 4-point Likert scale), and 6 questions were designed to determine patient attitude and behaviors related to online information.

Results

Patient-reported referral sources included the emergency room (29/329, 8.8%), friend (42/329, 12.8%), insurance company (47/329, 14.3%), internet search/website (28/329, 8.5%), primary care physician (148/329, 45.0%), and other (34/329, 10.3%). Among the 329 patients, 130 (39.5%) reported that they searched the internet for information before their first visit. There was a trend of increased belief in online information to be accurate and complete in younger age groups (P=.02). There was an increased relative frequency in younger groups to perceive physician rating websites to be unbiased (P=.003), provide sufficient patient satisfaction information (P=.01), and information about physician education and training (P=.03). There was a significant trend for patients that found a surgeon’s website to be useful (P<.001), with the relative frequency increased in younger age groups.

Conclusions

This study shows that insurance network, physician referrals, appointment availability, and office location are important to patients, whereas advertising and internet reviews by other patients were considered to be not as helpful in choosing an orthopedic surgeon. Future studies may seek to identify obstacles to patients in integrating online resources for decision-making and strategies to improve health-seeking behaviors.

Examining Different Factors in Web-Based Patients' Decision-Making Process: Systematic Review on Digital Platforms for Clinical Decision Support System

(1) Background: The appearance of physician rating websites (PRWs) has raised researchers’ interest in the online healthcare field, particularly how users consume information available on PRWs in terms of online physician reviews and providers’ information in their decision-making process. The aim of this study is to consistently review the early scientific literature related to digital healthcare platforms, summarize key findings and study features, identify literature deficiencies, and suggest digital solutions for future research. (2) Methods: A systematic literature review using key databases was conducted to search published articles between 2010 and 2020 and identified 52 papers that focused on PRWs, different signals in the form of PRWs’ features, the findings of these studies, and peer-reviewed articles. The research features and main findings are reported in tables and figures. (3) Results: The review of 52 papers identified 22 articles for online reputation, 15 for service popularity, 16 for linguistic features, 15 for doctor–patient concordance, 7 for offline reputation, and 11 for trustworthiness signals. Out of 52 studies, 75% used quantitative techniques, 12% employed qualitative techniques, and 13% were mixed-methods investigations. The majority of studies retrieved larger datasets using machine learning techniques (44/52). These studies were mostly conducted in China (38), the United States (9), and Europe (3). The majority of signals were positively related to the clinical outcomes. Few studies used conventional surveys of patient treatment experience (5, 9.61%), and few used panel data (9, 17%). These studies found a high degree of correlation between these signals with clinical outcomes. (4) Conclusions: PRWs contain valuable signals that provide insights into the service quality and patient treatment choice, yet it has not been extensively used for evaluating the quality of care. This study offers implications for researchers to consider digital solutions such as advanced machine learning and data mining techniques to test hypotheses regarding a variety of signals on PRWs for clinical decision-making.