Voice tech is a hot topic in healthcare, and for good reason. Healthcare is built on personal interactions, and voice technology can replicate and even replace the human interviewing experience. Voice has other valuable benefits in healthcare like being hands-free—for someone who is recovering from surgery and mobility challenged this might mean being able to get information without getting up. In the hospital setting, the hands-free interface has obvious benefits for hygiene.
At Wellpepper we first started experimenting with voice-enabling our interactive care plans in early 2017, and dug deeper into the topic, prototyping voice powered devices and testing with real people as part of our winning entry in the Alexa Diabetes Challenge. I’ll be talking more about this at the Voice Summit July 24-26, 2018 in Newark.
However, voice experiences in healthcare are not new. This week the Seattle Design for Healthcare meetup Ilana Shalowitz, Voice Design UI Manager, from EMMI Systems (part of Wolters-Kluwer) talking about best practices for voice design based her work on their interactive voice response system. This system effectively does outreach through “robocalls” to help influence people’s behavior, like getting them to schedule general health primary care visits, or get a flu shot. The pathways are designed to guide the patient through specific material, ensuring a basic understanding of the topic, and moving to take action (although not actually taking action), since that was not possible in the interface.
While they have been effective at changing patient behavior, the talk got me thinking about the differences between the interaction model for more traditional, non-AI based interactive voice response and the voice assistants like Alexa and Okay Google popping up in the home, the challenges of each, and the opportunities in healthcare.
Interactive voice response (IVR) can provide a structured pathway, which could be akin to an intake form or an interview. However, it doesn’t allow for an end-user driven experience. In her session, Shalowitz talked about designing a path to give the end user the illusion of control, where a yes or no answer to a knowledge question actually ended up in the same place. Compare that to the home voice experiences where the end user can drive any experience. The upside of this experience is that the end-user is in control, which is often not the case in healthcare, and can drive the direction of the conversation.
Here’s a common experience interacting with a Wellpepper care plan.”
Person: “Alexa, tell Wellpepper I have pain.”
Alexa: “Okay, what is your pain on scale of 0-10 where 0 is no pain, and 10 is the worst pain imaginable.”
Alexa: “Okay, I’ve recorded your pain as 4 out of ten. Is that correct?”
Alexa: “Anything else?”
The difference between this and a typical IVR communication is that the end-user is the initiator. However, the drawback with this type of scenario is that the end-user needs to know what they want to do. This is a notorious problem with headless interfaces like voice. In fact, each week, I get an email from the Alexa team that tells me what new thing I can do with Alexa, essentially a print-guide for the voice interface. Discoverability, context, and capabilities remain problems with these interactions even while they put the end-user at the center.
However, the benefits of these new consumer tools is that, they are designed to not anticipate each pathway in advance, and rather than the pre-recorded prompts of traditional IVR, they are learning systems where continual improvement can be made by examining successful and failed intents. We saw this is in our testing when a patient told Alexa he was “ready when you are.”
I’m excited to be heading to the Voice Summit this coming week, where we’ll talk about what we learned in the Alexa Diabetes challenge, and how we’re applying voice to all our patient experiences at Wellpepper. It’s still early days, but we see a lot of promise, and patients love it.
“Voice gives the feeling someone cares. Nudges you in the right direction.”
Test patient with Type 2 diabetes