Understanding the influence of professional status and service feedback on patients' doctor choice in online healthcare markets

Abstract

PurposeDespite the prevalent use of professional status and service feedback in online healthcare markets, the potential interaction relationship between two types of information is still unknown. This study used the signaling theory to examine the substitute relationship between professional status and service feedback in patients' doctor choice, as well as the moderating effect of illness severity.Design/methodology/approachTo test the paper's hypotheses, we constructed a panel data model using 418 doctors' data collected over a period of six months from an online healthcare market in China. Then, according to the results of the Hausman test, we estimated a fixed-effects model of patients' choice in online healthcare markets.FindingsThe empirical results showed that the effect of a doctor's professional status and service feedback on a patient's doctor choice was substitutable. Moreover, patients' illness severity played a moderating role, in that the influence of professional status on a patient with high-severity illness was higher than that on a patient with low-severity illness, whereas the influence of service feedback on a patient with low-severity illness was higher than that of a patient with high-severity illness. In addition, we found that illness severity negatively moderated the substitute relationship between professional status and service feedback on a patient's choice.Originality/valueThese findings not only contribute to signaling theory and research on online healthcare markets, but also help us understand the importance of professional status and service feedback on a patient's choice when seeking a doctor online.

Internal or External Word-of-Mouth (WOM), Why Do Patients Choose Doctors on Online Medical Services (OMSs) Single Platform in China?

“…This platform has gathered about 240,000 real-name registration of doctors from different hospitals and served more than 74 million patients by the end of 2021. We chose this platform as the research sample for the following reasons: (1) The platform is a popular OHC in China, and widely used in relevant research [ 8 , 9 , 11 , 17 , 18 , 60 , 61 , 62 ]; (2) The platform provides reasons why some health consumers choose a doctor in the patient review section; and (3) There are enough patients on the platform to vote for doctors. Figure 2 presents an example of one physician’s patient review section; this section includes the purpose of patients, treatment, efficacy satisfaction, attitude satisfaction, costs, state of illness, way of registration, and reasons for patient choice.…”

“…Patient-generated information provides information to patients about the services that other patients have received, and system-generated information includes basic information about the doctor, online activities, and comprehensive evaluation provided by OHCs. Researchers have suggested that seeing a doctor’s information in OHCs reflects the doctor’s trustworthiness [ 5 ], personal qualities [ 7 ], capital [ 8 , 9 ], service quality and attitude [ 6 , 8 , 10 , 11 ], reputation [ 7 , 12 , 13 , 14 , 15 ], and online efforts [ 10 , 13 , 16 ]. Patients can also learn about doctors’ interactions with patients [ 9 , 11 , 17 ], knowledge sharing [ 14 , 15 , 18 , 19 ], and log-in behavior [ 16 , 20 ].…”

“…Patients can also learn about doctors’ interactions with patients [ 9 , 11 , 17 ], knowledge sharing [ 14 , 15 , 18 , 19 ], and log-in behavior [ 16 , 20 ]. This information generates a doctor’s internal WOM and has proven to have a positive impact on patient choices in OMSs [ 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 ]. In addition, some studies involving patient choices of doctor teams online discussed the impact of team diversity [ 21 , 22 ].…”

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

“…Patients' perceptions of the level of popularity on PRWs may support them in evaluating the quality of their treatment and predicting service delivery [ 56 ]. Moreover, a high volume of PORs enhances the likelihood of obtaining correct information that can assist patients in assessing the quality of healthcare services [ 58 ]. Researchers discussed that the more the information a patient has, the more likely s/he will make a better decision [ 59 ].…”

Antecedents and Consequences of Online Healthcare Community Usage: A Grounded Theory Approach

“…Previous research has explored and made outstanding contributions to the understanding of online healthcare community platforms and the relationship between doctors and patients [ 1 , 2 , 3 ]. However, it is worth noting that most previous studies on the relationship between the use of online healthcare communities and doctor–patient interactions have been conducted from the perspective of single patient and doctor, and their conclusions have not been entirely consistent [ 4 , 5 ]. The reasons for this are as follows: the dimension, intensity, and platform characteristics of the use of online healthcare communities affect the mechanisms of the doctor–patient relationship.…”