Back

Physicians experiences with telemedicine during the COVID-19 pandemic in India

Nagaraja, V.; Ghosh Dastidar, B.; Suri, S.; Jani, A.

2024-02-11 health systems and quality improvement
10.1101/2024.02.10.24302616 medRxiv
Show abstract

BackgroundDigital health is an important factor in Indias healthcare system. Inclusive policy measures, a fertile technological landscape, and relevant infrastructural development with unprecedented levels of telemedicine adoption, catalysed by the COVID-19 pandemic, have thrown open new possibilities and opportunities for clinicians, end-users, and other stakeholders. Nevertheless, several challenges remain in properly integrating and scaling telemedicine in India. This studys objective was to understand the views of practising physicians in India on the use of telemedicine, with a particular focus on the period after the release of Indias Telemedicine Practice Guidelines in India, after which telemedicine was rapidly implemented. MethodsWe acquired data through an anonymous, internet-based survey (with a cross-sectional time perspective) of 444 physicians across India. These responses were subjected to qualitative data analysis (via inductive coding and thematic analyses) and descriptive statistics, as appropriate. ResultsMost responses (n=51) were categorised under a code indicating that telemedicine-led healthcare delivery compromised treatment quality. The second largest proportion of responses (n=22) suggested that Accessibility, quality and maturity of software and hardware infrastructure was a considerable challenge. ConclusionsDespite the considerable uptake, perceived benefits, and the foreseen positive role of telemedicine in India in delivering universal coverage, several challenges of telemedicine use (viz., technical, user experience-based integration, and non-user-based integration challenges) have been identified, which need to be addressed to realise telemedicines potential. Several relevant opportunities are suggested to inform policy and practice to ensure effective utilisation of telemedicine in India.

Matching journals

The top 1 journal accounts for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.