How Online Reviews and Services Affect Physician Outpatient Visits: Content Analysis of Evidence From Two Online Health Care Communities

Wei, Lu; Wu, Hong

doi:10.2196/16185

Cited by 24 publications

(32 citation statements)

References 47 publications

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“…Online reviews integrate information from various sources providing online word-of-mouth (WOM) to healthcare consumers who lack WOM [ 13 ]. Extant studies on the patients’ choice of physician outlined that information gathered from peers or other patients are always amongst the top influencing factors [ 9 , 26 ].…”

Section: Theoretical Background and Research Hypothesismentioning

confidence: 99%

“…Online reviews have also gained interest from researchers in the healthcare field. A variety of investigations were performed using different PRWs in different countries, such as the average rating score of a physician, review volume [ 8 , 9 , 10 ], and qualitative analysis of OPRs to mine patients’ interests [ 11 ]. In addition to these studies, several other studies have examined the impact of physician star ratings and textual feedback on patients’ choice [ 10 , 12 , 13 , 14 ].…”

Section: Introductionmentioning

confidence: 99%

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Exploring the Impact of Linguistic Signals Transmission on Patients’ Health Consultation Choice: Web Mining of Online Reviews

Shah

Ali

Qayyum

et al. 2021

IJERPH

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Background: Patients face difficulties identifying appropriate physicians owing to the sizeable quantity and uneven quality of information in physician rating websites. Therefore, an increasing dependence of consumers on online platforms as a source of information for decision-making has given rise to the need for further research into the quality of information in the form of online physician reviews (OPRs). Methods: Drawing on the signaling theory, this study develops a theoretical model to examine how linguistic signals (affective signals and informative signals) in physician rating websites affect consumers’ decision making. The hypotheses are tested using 5521 physicians’ six-month data drawn from two leading health rating platforms in the U.S (i.e., Healthgrades.com and Vitals.com) during the COVID-19 pandemic. A sentic computing-based sentiment analysis framework is used to implicitly analyze patients’ opinions regarding their treatment choice. Results: The results indicate that negative sentiment, review readability, review depth, review spelling, and information helpfulness play a significant role in inducing patients’ decision-making. The influence of negative sentiment, review depth on patients’ treatment choice was indirectly mediated by information helpfulness. Conclusions: This paper is a first step toward the understanding of the linguistic characteristics of information relating to the patient experience, particularly the emerging field of online health behavior and signaling theory. It is also the first effort to our knowledge that employs sentic computing-based sentiment analysis in this context and provides implications for practice.

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Section: Theoretical Background and Research Hypothesismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Exploring the Impact of Linguistic Signals Transmission on Patients’ Health Consultation Choice: Web Mining of Online Reviews

Shah

Ali

Qayyum

et al. 2021

IJERPH

View full text Add to dashboard Cite

show abstract

“…Interestingly, they found a U-shaped relationship between the number of ratings and the overall mean, with a mean nadir occurring at 21 patient ratings. 7 A study from China 21 found that their population valued the number of reviews more than average rating score; however, the impact of those differences was not evaluated. The study evaluated all ambulatory care visits and found that patients valued the number of ratings more so than the mean rating when selecting a provider.…”

Section: Discussionmentioning

confidence: 99%

Online Reputations: Comparing Hospital- and Patient-Generated Ratings in Academic Otolaryngology

Basa

Jabbour

Rohlfing

et al. 2021

Ann Otol Rhinol Laryngol

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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.

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“…Such communities provide virtual forums for patients to obtain services and discuss treatment experiences. Researchers have started to investigate the benefits and user behaviors of such communities, from the perspective of doctors [19,22] and patients [23][24][25]. For doctors, Ni and Sun [26] studied the willingness of doctors to work on online platforms and associated benefits.…”

Section: Online Health Communitiesmentioning

confidence: 99%

The Influence of Doctors’ Online Reputation on the Sharing of Outpatient Experiences: Empirical Study (Preprint)

Wang¹,

Wu²,

Lei³

et al. 2019

Preprint

Self Cite

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BACKGROUND Reviews are important for consumers to make informed decisions in online communities and for organizations to predict sales in the future. Most existing literature are conducted in product fields, with little attention paid to healthcare. Whether patients prefer to use these new platforms to discuss the reputation of doctors has so far remained an open question. OBJECTIVE We investigate how patients’ propensity to post the treatment experiences (PPPTE) changes with doctors’ (individual) online reputation (medical quality and service attitude) for outpatient care service. We also investigate the moderating effects of hospital (organizational) online reputation and disease severity. METHODS The fractional logistic regression under the GLM framework based on data from 7,183 doctors within a Chinese online health community are used to get the empirical results. RESULTS Our results show that patients prefer to share their treatment experiences for doctors who have higher medical quality and service attitude and work in higher online reputation hospitals. Comparing with the doctors who treat less severe diseases, PPPTE is smaller for doctors who treat severe diseases. In addition, the hospital’s online reputation positively (negatively) moderates the relationship between medical quality (service attitude) and PPPTE. Further, the moderating effects of disease severity on the doctor’s online reputation are negative. CONCLUSIONS Our research contributes to both theory and practice by researching the impact of individual reputation on consumer behavior, investigating the moderating effects of organizational reputation and consumer characteristics in healthcare.

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How Online Reviews and Services Affect Physician Outpatient Visits: Content Analysis of Evidence From Two Online Health Care Communities

Cited by 24 publications

References 47 publications

Exploring the Impact of Linguistic Signals Transmission on Patients’ Health Consultation Choice: Web Mining of Online Reviews

Exploring the Impact of Linguistic Signals Transmission on Patients’ Health Consultation Choice: Web Mining of Online Reviews

Online Reputations: Comparing Hospital- and Patient-Generated Ratings in Academic Otolaryngology

The Influence of Doctors’ Online Reputation on the Sharing of Outpatient Experiences: Empirical Study (Preprint)

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