When a Doctor Knows, It Shows: An Empirical Analysis of Doctors’ Responses in a Q&A Forum of an Online Healthcare Portal

Abstract

Healthcare portals are gaining in popularity, connecting doctors with potential consumers of healthcare services. As online search and transaction marketplaces, they bring both sides of the market onto the same platform. Managers or platform owners seek to create value by increasing the number of users on either side of demand and supply of services. User-generated activity on Q&A forums of such sites reduces information asymmetry and indicates an increased adoption by either side. In this study, we have provided insights into understanding drivers for increased recommendations for doctors in online healthcare-services marketplace. The identification of these drivers and their directionality, interplay, and magnitude of impact are all of direct relevance to site promoters and managers as well as users. We find that the introduction of doctors’ responses has a significant causal impact on demand-side user perception of medical services offered. More importantly, our research suggests that doctors’ specialty, experience, qualifications, transparency in appointment booking, service fees, and response quality moderate the effect of doctors’ Q&A responses on user recommendations.

Seeking or contributing? Evidence of knowledge sharing behaviours in promoting patients’ perceived value of online health communities

“…As shown in Table 1, early research primarily focused on the antecedent factors influencing users' health knowledge sharing behaviours. Since meeting users' expectations and enriching their health outcomes are critical for users' continuous use of OHCs and the sustainability of OHCs, 7,19,20,54 recent studies have begun to explore the consequences of their health knowledge sharing behaviours, for example the impacts of informational support in OHCs on patients' health conditions, health attitude and e-health literacy. 9,28,29,43,55 Although engaging in OHCs can improve users' perception of value, 29,56 few studies have examined the impacts of patients' health knowledge sharing behaviours and other factors on their perceived value of OHCs.…”

“…OHCs are a type of health-related virtual community (VC) designed particularly for different health-related stakeholders, for example health insurance, pharmaceutical companies, hospitals, health professionals, patients, and patients' relatives or friends. [1][2][3][4][5][6][7][8][9] There are different types of OHCs in which users can conduct different health-related activities, including transactions, appointment scheduling, counselling, social networking and health-related Q&As. 1,[10][11][12][13][14][15][16] In this study, we particularly focus on problem-solving communities where both health professionals and patients can participate and collaborate for health knowledge exchange, for example Q&A forums on health conditions, 13,17 mental health-focused Q&A forums, 18,19 pregnancy forums such as Babytree.com, 20 and cancer-focused communities.…”

“…For example, some studies on health professionals have examined the impacts of factors such as professional capability, reputation and economic rewards. 7,8,19,20,31,38,39 Other studies, focused on patient users, have examined the impacts of extrinsic and intrinsic motivations [4][5][6]20,33,34,40 and potential hindering factors such as trust and privacy protection. 6,24,30 As social networking is an important feature of OHCs and users in OHCs also pursue social interactions, 1,3,22 some studies have also explored the impacts of users' social capital in OHCs.…”

Containing COVID-19 through physical distancing: the impact of real-time crowding information

“…Li & Wu, 2018). Previous information systems (IS) research related to CI primarily investigated how users interpret demand information, such as the number of patient recommendations for a doctor (Khurana et al, 2019;. Findings mainly indicate that individuals are attracted to highly demanded and thus often crowded locations as high demand is interpreted as a signal of high quality (Becker, 1991;Chen & Davison, 2019;X.…”

“…Li & Wu, 2018). For example, highly demanded doctors are believed to provide greater service quality (Khurana et al, 2019;, reflecting expertise and safety to receive competent support, which seems particularly important during the COVID-19 pandemic. Yet, this attraction to demanded and thus often crowded locations implies a serious threat in times of COVID-19: If users are attracted to crowded locations, do DSS that display CI in good faith unintentionally make users select more crowded locations and hence add fuel to the fire of spreading COVID-19?…”