Navigating the Landscape of Telemedicine Research: A Topic Modeling Approach for the Present and Future

Introduction: Telemedicine, which is the provision of remote clinical services via telecommunication technology, has undergone an upsurge since the COVID-19 pandemic. To capture this paradigm, this study surveyed telemedicine literature, including postpandemic publications, to identify dominant research themes and temporal trends and suggest directions for future research. Methods: A corpus of 56,445 telemedicine studies is sourced from PubMed. Latent Dirichlet allocation (LDA) topic modeling performed using the Konstanz Information Miner platform. The textual data for topic modeling were processed by following standard procedures for natural language processing. Moreover, the term frequency-inverse document frequency approach was used to capture the importance of words within the corpus. We assessed perplexity, coherence, and the elbow method to determine the optimal number of topics for modeling. Results: The findings confirm the surge in telemedicine research after 2020, signifying its prominence. LDA topic modeling reveals seven distinct research themes, with the most prominent topic being "patient satisfaction" (21.38%) followed by "perspectives and challenges" (17.95%), and "smartphone apps" (14.32%). Furthermore, the results demonstrate a noticeable shift in topics from screening to therapeutic applications of telemedicine. Conclusions: This study serves as a guide for a broad range of telemedicine research topics. This synthesis of themes reflects the commitment of scholars to address the changing dynamics and health care needs, such as the COVID-19 pandemic, aging in place, smartphone usage, and technological advancement. The analysis also reveals flexible research responses to policy and contextual shifts, highlighting the collective drive to broaden the application of telemedicine in community health care.