Background: The rapid expansion of telehealth, which was accelerated by the COVID-19 pandemic, has outpaced standardized approaches to data capture, resulting in fragmented documentation and limited research infrastructure. A centralized telehealth taxonomy would be useful for improving documentation, evaluating utilization, and informing decision-making. However, no comprehensive telehealth taxonomy has been developed to date. Methods: A scoping literature review was conducted to identify the characteristics needed to build a comprehensive telehealth taxonomy that informs a data repository. Then, a hybrid hierarchical mind map taxonomy was built using the frameworks and concepts from the reviewed articles, along with insight and feedback from eight telehealth domain experts. The taxonomy was revised using an iterative process, and the final version was approved by the domain experts. Results: Ten articles were ultimately included in this scoping review. Based on the findings of those articles, the final taxonomy includes 14 core variables that span the full telehealth appointment, including previsit preparation, during-visit interactions, and postvisit follow-up. The variables are arranged across both patient and provider perspectives. The taxonomy includes four dimensions: synchronous and asynchronous modalities, user perspectives, functionality, and payment considerations. Furthermore, the taxonomy aligns with electronic health record data fields, thus promoting interoperability and structured data capture. Discussion: The unified framework developed herein aims to bridge gaps in telehealth research by providing a scalable, interoperable foundation for data repositories. Ultimately, this taxonomy lays the groundwork for improved telehealth data infrastructure and can enhance research, clinical care, and data-informed policy development.
Yalamanchi et al. (Thu,) studied this question.