Patient 2.0 - What Predicts Usage of Physician-Rating Apps?

Background: There is an increasing interest by physicians, patients, and industry inPhysician-Rating Websites (PRWs). Similar to developments in mostconsumermarkets, it can be expected that patients will increasingly access such PRWsvia mobile apps. However, there has been little discussion about what kind ofvariables may predict usage of mobile PRW apps.

Objective: The study analyses sociodemographic, psychographicvariables and variables of Internet usage in order to predict evaluation of, willingnessto make use of and willingness to pay for mobile PRW apps.

Methods: An online survey of 1006 randomly selectedGerman patients was conducted. Data were analysed by using three multipleregression models (calculated with SPSS, version 20); missing values, multicollinearityand normality were checked.

Results: Evaluation of a mobile PRW app can bepredicted by the sociodemographic variables gender (B=-.252, p=.032) and age(B=-.014, p=.004). According to that men and younger patients are more prone toappreciate such an app. Feelings about the Internet and Web 2.0 in general (B=.342,p=.000), trust in Physician-Rating Websites (PRWs) (B=.199, p=.001) andjudgement of the usefulness of Rating-Websites compared to other informationsources like family etc. (B=.206, p=.001) were significant predictors. Additionally, one factor contributed alsosignificantly to the prediction of evaluation: personality of the patient asinformation seeker (B=.113, p=.010). Digital literacy (B=.107, p=.101) did notexcert a significant influence. Use of different technologies (i.e. smartphone,tablet, B=.277, p=.001), total daily Internet private use for health relatedinformation (B=.102,p=.014) and the frequency of using apps for health relatedinformation search (B=.123, p=.007) also influenced evaluation of mobile PRWapps significantly. The variables explained 39.7 % of variance of evaluation ofmobile PRWs app.

A second multiple regression was calculated withthe same predictors above for the dependent variable “willingness to use suchan app.” The variables explained 41.8 % of variance. A difference emerged forthe total daily Internet private use for health related information (B=.036,n.s.), which was no significant predictor in this multiple regression. A thirdmultiple regression was calculated with the same predictors for the dependentvariable “willingness to pay for such an app” leading to 30.4 % of explainedvariance, with only some of the variables above remaining significant:frequency of using apps for health related information search (B=.267, p=.000),trust in Physician-Rating Websites (PRWs) (B=.253, p=.000), the personality ofthe patient as information seeker referring to visiting a doctor (B=.162,p=.000), feelings about the Internet and Web 2.0 in general (B=.107, p=.045) anduse of different technologies (i.e. smartphone, tablet, B=.149, p=.035).Additionally, the perceived ease of use of the Internet for searching healthrelated information contributed significantly (B=.170, p=.009) in thisregression, not in the others.

Conclusion: A PRW app may be very useful in certain circumstancese.g. when a patient is on a journey or a physician’s ordination is unexpectedlyclosed. Sociodemographic, psychographic and behavioralvariables of Internet use contribute to the evaluation of, willingness to makeuse of and willingness to pay for mobile PRW apps. The results of this study are useful forcreators of mobile PRW apps.