IDENTIFYING DETERMINENTS OF TELE MEDICINE ADOPTION AMONG PATIENTS IN INDIA

Back ground and purpose: Tele health services has witnessed a sudden surge during Covid 19. To manage patients and meet the needs of communities during Covid, transformative and innovative systems were required for patient care as this was very novel crisis. During this crisis, virtual care or Tele health care was a boon for the patients because easy to use systems and technologies were provided to the patients. It has been observed that during Covid, tele health services usage has increased from 11% to 70% and the satisfaction level among the patients is around 78% in US and China. In this regard the purpose of the present study is to identify what leads to adoption of telemedicine among patients. Experimental Approach: Study adopted empirical approach, where primary data was collected from citizens across India. A total of 18 items have been selected in the to identify the factors that lead to tele medicine adoption. Exploratory Factor Analysis (EFA) using SPSS version 21 has been conducted to group items into factors leading to the phenomenon. Further, reliability test was conducted via Cronbach Alpha for all the factors and the scale as a whole. Finally, to test the scale for its validity, convergent discriminant validity has been tested. For establishing convergent validity, values of Average Variance Extracted (AVE) and Scale Composite Reliability has been computed; to establish discriminant validity it is ensured that the square root of AVE of each construct is greater than the inter-construct correlation coefficients of that construct with each other construct. Key Results: Applying EFA, the 18-item scale adopted for the study gets clubbed under four factors namely; familiarity level, willingness to use, easy to adopt and cost effectiveness & accessibility. The reliability of the scale was established since the Cronbach Alpha values were more than 0.7 for all the factors and for composite scale as well. The validity of the scale was also established since the values of AVE and SCR of all the factors were well above the acceptable range. Discriminant validity was also established for the model. Conclusion and Implications: The study resulted in a model for adoption of telemedicine services in India. The model is open for testing for its applicability; future studies may adopt the resulted model for its testing using advanced statistical techniques. Further, telemedicine companies may use the model to approach their customers in more effective manner keeping in mind the aspects important for adoption of telemedicine services.