Objective: This study aims to investigate key considerations and critical factors that influence the implementation and adoption of smart glasses in fast-paced medical settings such as emergency medical services (EMS). Materials and Methods: We employed a sociotechnical theoretical framework and conducted a set of participatory design workshops with fifteen EMS providers to elicit their opinions and concerns about using smart glasses in real practice. Results: Smart glasses were recognized as a useful tool to improve EMS workflow given their hands-free nature and capability of processing and capturing various patient data. Out of the eight dimensions of the sociotechnical model, we found that hardware and software, human-computer interface, workflow, and external rules and regulations were cited as the major factors that could influence the adoption of this novel technology. EMS participants highlighted several key requirements for successful implementation of smart glasses in the EMS context, such as durable devices, easy-to-use and minimal interface design, seamless integration with existing systems and workflow, and secure data management. Discussion: Applications of the sociotechnical model allowed us to identify a range of factors, including not only technical aspects, but also social, organizational, and human factors, that impact the implementation and uptake of smart glasses in EMS. Our work informs design implications for smart glass applications to fulfill EMS providers’ needs. Conclusion: The successful implementation of smart glasses in EMS and other dynamic healthcare settings needs careful consideration of sociotechnical issues and close collaboration between different stakeholders.

The data was collected through a set of participatory design workshops with fifteen EMS providers. We constructed discussion questions guided by Sittig and Singh's sociotechnical framework and asked the participants to discuss key social, technical, and organizational considerations for using smart glasses in pre-hospital care. The workshops were conducted remotely via Zoom and all activities were audio and video recorded. We transcribed the discussions and loaded the transcripts into NVivo (QSR International, Version 12). Three researchers were involved in the data analysis process following the open coding techniques to identify salient patterns and classify them into the eight dimensions of Sittig and Singh's sociotechnical framework.