Adoption and diffusion of digital health consultation: a patients’ perspective study in urban India

Purpose The purpose of this paper is to understand the degree of diffusion of digital health consultation (DHC) among patients in the urban India. This study measures the factors influencing the adoption decision (AD) and continued usage decision of DHC. This study used the Unified Theory of Acceptance and Use of Technology (UTAUT2) framework and all the factors used in UTAUT2 for the adoption of the technology. Design/methodology/approach This study is based on the primary data collected from 580 patients from six metros, semi-metros and Tier 1 cities (Delhi, Pune, Hyderabad, Bhubaneswar, Indore and Bhopal) of India using convenient sampling method. The set of hypotheses proposed are tested using structural equation modeling. Findings This study examined nine constructs in the conceptual model, seven constructs relationship toward AD and continued usage intention (CUI) of DHC among patients. This study found performance expectancy (PE), social influence (SI), effort expectancy, facilitating condition positively influences the AD and CUI, whereas hedonic motivation (HM), price value (PV) and habit (H) do not influence. The negative B-coefficient still has the positive impact towards the adoption and continued usage by the patients. This study also measures the degree of diffusion of DHC among patients. Research limitations/implications The investigation’s primary limitation lies in confined market segments such as metro, semi-metro and Tier 1 city. The information collection methods used in research became a limitation. If research relied solely on self-reported data from surveys or interviews, there could be inherent biases and inaccuracies in the responses provided by participants. Using alternative data collection techniques, such as observational studies, experimental designs or data mining approaches, could help validate and complement the findings obtained through traditional survey methods, thus improving the robustness of the research results. Temporal factors pose another limitation, as the patients’ AD can evolve gradually in response to technological, economic as well as societal changes. This study was conducted during a specific time; the findings may have failed to capture the overall trends because this study could not deal with the dynamic nature of patients’ AD. Practical implications This investigation has practical implications because strategists, planners, policymakers, service design teams and technology developers can use these findings to strategize the successful execution and implementation of DHC services. Social implications SI, HM, PV and H do not influence the ADs among the patients. Valuable additional incentives such as loyalty points, lucrative programs and free coupons can be planned to increase frequency, creating mouth-to-mouth publicity and forming a habit to foster the ADs and CUI toward DHC service at a large scale in Indian cities. Originality/value This study conceptually strengthens the present body of literature on the AD and CUI by contributing new dimensions using the UTAUT2 frame work. The findings will help policymakers, service providers and government to strategize in their promotional design to widespread DHC.