Solving the challenges of Voice AI for the Life Sciences Industry

Anik Dey, Senior Product Owner - Voice Platform and Jessica Naman, Director of Marketing at conversationHEALTH

In a fast-changing digital world where convenience and efficiency are consistently being optimized, there is a significant increase in demand for voice technologies. According to a survey done by voicebot.ai in 2020, over 87 million Americans have a smart speaker at home — a 32% increase from 2019. Consumers have become digital first when it comes to sourcing information, and this is no different when it comes to health. Health professionals, patients, and consumers want answers to their medical and product questions 24/7/365.

Of course, when a patient engages with a life sciences company over a voice platform such as Google Home or Amazon Alexa, they expect the same level of accuracy as they would speaking to a health professional. When a physician asks, “Hey Company X, does my patient need a second dose of medication Y?”, she expects to receive the same answer as she would have communicating with a Medical Science Liaison. Therefore, It is essential that voice assistants deliver medical information as precisely as the best expert human resource would.

Where the challenge lies is that non-healthcare natural language understanding (NLU) engines are — at most — accurate 65% of the time. These powerful but “lay” engines are simply not optimized for medical conversations and will fail to correctly transcribe medical jargon and molecule names over 1/3 of the time. This risks changing the meaning of the sentence and providing health professionals or patients with wrong answers to their questions. For example, “Can you inform me about the common side effects of the covid treatment?” gets transcribed to “Can you inform me about the common side effects of the Cove achievements?” completely missing the intent of the question — not an acceptable risk.

This is one of the many problems that we are solving for at conversationHEALTH. Voice in health is particularly challenging given the complexity of medical language and regulatory-medical-legal requirements, while also accounting for health literacy, different users — health professionals vs. patients vs. consumers, different personas — security and privacy, and integration into key health tech stacks, i.e. IQVIA, Salesforce, Veeva etc. In real time! And of course, this must be scalable across markets, languages, dialects, etc., consistent with the needs of global life sciences companies. In short, deeply verticalizing our SaaS platform allows us to best meet the mission-critical needs of life sciences companies and their customers, including unique and complex data regulation and compliance requirements — out of the box.

We should all be excited about the adoption and use of voice solutions in health. This is all about increasing the supply of medical engagement and conversations for better health outcomes. As life sciences companies look to engage health professionals, patients and consumers with conversational AI, the demand for voice solutions will grow exponentially. Hey Company X, are you ready?

Curious about what is involved in deploying conversational agents? Book a meeting with one of our conversational AI experts to learn how you can best leverage digital solutions to engage HCPs, patients & consumers.