Understanding potential benefits and drawbacks of using emoji in medical charts

Shuhan He, MD, a physician-scientist in the Department of Emergency Medicine at Massachusetts General Hospital and instructor of Medicine at Harvard Medical School, as well as the program director for the Masters in Science in Data Analytics offered at the Mass General Institute of Health Professions. He is the lead author of a new commentary published in JAMA Network Open, Interpreting Emoji: A Language for Enhancing Communication in Healthcare.

What question were you investigating?

The use of emoji in medical charts is a relatively new and emerging topic, and there is a lack of research and understanding around its potential benefits and drawbacks.

My commentary is a contribution to the ongoing conversation around the use of emoji in medical charts, and hopefully helping to shape the direction of future research and practice in this area-;particularly the idea that emoji have the potential to improve communication, patient outcomes and provider-patient relationships in healthcare.

What methods or approach did you use?

My piece is an invited commentary on a study regarding the interpretation of emoji in medical charts. This is important for several reasons:

 – Emerging topic: The use of emoji in medical charts is a relatively new and emerging topic, and there is a lack of research and understanding around its potential benefits and drawbacks. Consider an example: if a physician responds to a question with �� in responding to a consult or page, is that considered a legal medical order?

– Impact on healthcare communication: The use of emoji in medical charts has the potential to significantly impact healthcare communication and delivery. Consider the scale ��������☹️�� that physicians use every day to ask pediatric patients how they feel. Effective communication is essential in providing quality healthcare, and any new tools or methods that can improve communication should be explored and evaluated.

My commentary can help to shed light on how emoji use can impact communication and what factors need to be considered in its implementation.

– Guidance for further investigations: My commentary offers recommendations for future research in this area, focusing on the utilization of advanced data analytics tools such as machine learning in healthcare. For instance, imagine a nurse having access to a comprehensive sentiment chart that tracks how a patient's nausea and vomiting improve after administering Zofran, an anti-nausea medication. Additionally, consider the potential for a physical therapist to closely monitor and measure the impact of daily walking on an individual's quality of life following a knee replacement surgery. These examples highlight the potential benefits of leveraging precision medicine tools to enhance patient care and outcomes.

What are the clinical implications?

The implications of the findings discussed in this commentary are significant and far-reaching.
The ongoing efforts to increase representation of medical emoji, such as the anatomical heart and lung developed at MGH in 2020, demonstrate a growing recognition of the potential benefits of using emoji in healthcare. This signifies a shift in how we perceive and utilize this communication tool. With the availability of more medical emoji, healthcare providers can now utilize them to improve communication with patients and effectively convey complex medical information in a simple and intuitive manner. This holds the potential to foster increased acceptance and integration of emoji in healthcare.

Second, emoji usage in patient reported outcomes (PROs) has the potential to enhance our understanding of patient experiences, particularly in relation to pain, emotions, and sentiment. By incorporating emoji to capture these experiences, healthcare providers can gain deeper insights and effectively address patient needs, resulting in enhanced patient outcomes and satisfaction. To facilitate this, a groundbreaking development at MGH in 2022 validated the use of an emoji-based visual analogue scale, akin to the widely recognized Wong Baker scale. This innovative approach empowers healthcare providers to efficiently and accurately capture patient experiences using a simple and intuitive visual tool, ultimately leading to more precise diagnoses and more effective treatments.

What are the next steps?

We need to conduct research to develop new machine learning methods to interpret emoji in the healthcare setting and create more characters in the emoji language including anatomical kidney, stomach, intestine.

I also invite anyone interested in leadership, research , or education in health data analytics to learn more through our MGHIHP data analytics program page. We also have a series of teaching webinars on how to utilize healthcare data analytics in health that is free to sign up. You can also find me on twitter where I am passionate about teaching about healthcare data analytics.