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We recently joined Xavier Villarreal, Vice President of Critical Markets at Zebra Technologies, on the Zebra Podcast's ISV series. Our Director of Clinical Informatics, Sarah Visker MSN,RN, NI-BC sat down with him to talk about something every nurse feels but few systems are built to fix: what it actually takes to deliver care when your attention is split across a dozen different tools.
Here's what stood out from the conversation.
Most people in healthcare know about the documentation burden. Charting eats up 25 to 40% of a nurse's shift. What gets far less attention is the second burden sitting right next to it: the technology burden.
"Sometimes nurses will have to interact with upwards of 13 different fragmented systems," Sarah explained. Each one has its own login, its own location, its own way of working. Need a video interpreter? Go find the iPad on a stick, and hope it's charged and hasn't been borrowed by another unit. Need to check a policy? Find the right computer. Need to submit a service request? Maybe find another computer.
Every one of those steps is a context switch. And every context switch is an interruption that pulls a nurse away from the patient.
"Nurses did not go into nursing to be administrative data entry specialists," Sarah said. People become nurses because they're passionate about caring for patients. When the technology keeps pulling them out of the room, the work that actually fulfills them gets crowded out by the work many nurses describe as "soul sucking." That's a direct line to burnout.
So Aiva and Zebra are bringing all of those fragmented technologies under one voice-activated interface – and getting nurses back to the bedside.
The examples Sarah walked through all follow the same principle. Keep your eyes on the patient, and use your voice for everything else.
Interpretation. Instead of hunting down a shared tablet, a nurse using the Zebra HC50 can press a button and say, "call the Polish interpreter." Video interpretation lands right in their pocket.
Patient safety observation. When a patient needs constant observation, a nurse's eyes are supposed to stay on them at all times. Yet safety documentation is often required every 15 minutes, which normally means looking away at a computer. With voice, the nurse can stay focused on the patient and chart hands-free.
Communication. Using the Zebra badge, a nurse can say, "hey Zebra, text the cardiologist on call, my patient in room 302 is having chest pain and I'd like them to come evaluate." No directory search, no leaving the room. Even better, the patient hears it happen, so they're included in their own care instead of watching a nurse click away in silence. The badge also carries safety features Sarah loves, including a safe word that can alert colleagues when a nurse needs help.
The smart room. Nurses can control blinds, lights, and the exam light by voice, mute a blaring TV, or play a fall-prevention video, all without breaking eye contact with the patient.
BayCare Hospital, featured in a Spectrum News segment, is seeing wins from voice-enabled documentation.
Liza Redmond, Nurse Manager at Baycare’s St. Anthony’s Hospital said: “The team is super excited about the whole thing. It gives them a lot more time face to face with their patients and less away, you know, behind a computer screen.”
Across a single 12-hour shift, a nurse can log upward of 800 discrete data points, often repeating the same assessments hour after hour. With Aiva, they can simply talk. Sarah's example: "my patient in room 302 is having abdominal pain, it's a three out of ten in the left lower quadrant, I'm giving a warm pack, and they only ate 25% of breakfast." No flowsheet speak required.
The AI works in the background to translate that natural conversation into structured flowsheet data, then sends it to the Zebra device to validate. The nurse sees the transcript, confirms the patient with three identifiers (name, date of birth, Medical Record Number), and reviews a grid of the documentation. Aiva can even add friendly reminders, like a nudge to capture pain quality if it wasn't mentioned. One tap on accept, and it flows straight to the EHR. No computer required.
The payoff is timeliness, which is really patient safety. When a nurse types documentation into a computer, it lands in the record an hour to an hour and a half after the observation actually happened. That means sepsis alerts, early-warning systems, and predictive models are all running on old data. When nurses chart by voice at the bedside, that same information reaches the whole care team in minutes. Organizations are seeing documentation latency drop by 80 to 90%. Patients are happier too, because the nurse is present with them instead of clicking in the corner.
Speaking assessments out loud is new, and there's a whole generation of nurses who have never worked without flowsheet checklists. Sarah compares it to memorizing phone numbers: once you stop having to do it, the skill fades.
So we don't ask organizations to go from zero to fully ambient overnight. We start where it matters most. Where are the biggest pain points for nurses, and where do you most need better compliance for patient safety or regulatory reasons? For many organizations that's intake and output, or pain reassessment. Start there, build comfort with the workflow, and expand from a position of confidence.
Sarah's closing "pearl of wisdom" was the through-line of the entire conversation: the number one key to success is having a nurse at the table.
And not just informatics nurses. Nursing leadership from the CNO and CNIO down to directors and unit managers, plus the direct-care nurses and nursing assistants who will actually use the product every day. Treat them as co-innovators, not end users handed a finished product.
"Too often that doesn't happen," Sarah said, "and nurses are given a finished product that we hope will work in their workflows. That's when you get the feeling that technology is being done to me, versus this is something that's going to help me." Her advice: engage your direct-care nurses early and often.
Physicians have been getting AI help with documentation for years. Nurses have been asking for the same support for just as long, but the way nurses and physicians document is fundamentally different. Physicians narrate in paragraphs, which is straightforward for a language model to predict. Nursing documentation looks more like a spreadsheet of dropdowns, and the models simply weren't smart enough to handle it until recently. Now they are. The opportunity is to build a tool designed specifically for nursing, with nurses, and finally give the largest workforce in healthcare the help it has been waiting for.