Shuhan He

Emoji for the medical community

"Emoji for the Medical Community" explores the use of emojis to improve communication in healthcare, particularly focusing on enhancing how patients report outcomes. It introduces the Emoji-based Visual Analog Scale (EbVAS), which integrates emojis into patient feedback systems, such as pain assessments. This method aims to make patient communication more intuitive and relatable by utilizing digital, open-source emojis that complement traditional scales like the numeric and Wong-Baker FACES Pain Rating Scale.

The discussion delves into the potential of emojis to bridge cultural and language barriers in clinical settings, making it easier for patients to convey subjective symptoms like pain. The presentation reviews various studies comparing the effectiveness of the EbVAS with conventional pain assessment tools, suggesting that emojis could offer a more universally understandable and accurate means of expressing patient experiences.

Lastly, the presentation considers the broader implications of incorporating emojis into medical communication. It discusses the challenges of creating a standardized set of medical emojis, including issues of diversity and representation of different organ systems. Collaborations with entities such as the Unicode Consortium and medical societies are highlighted as crucial steps towards developing a comprehensive emoji-based communication tool in healthcare. The ultimate aim is to foster more inclusive and effective interactions between healthcare providers and patients by leveraging the simplicity and expressiveness of emojis.

Biography
Shuhan He, MD is a dual-board certified physician with expertise in Emergency Medicine and Clinical Informatics. He works at the Laboratory of Computer Science, clinically in the Department of Emergency Medicine and Assistant professor of Medicine at Harvard Medical School. He serves as the Program Director of Healthcare Data Analytics at MGHIHP and has interests at the intersection of acute care and computer science with a focus on patient centric technologies. 

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