Why Managed Service Partnerships Transform Healthcare Voice AI: The Parlance Difference
The Human Element Behind Healthcare Voice AI
As a conversational AI designer and software engineer at Parlance and a mother of two young children, I understand firsthand how challenging it can be to manage healthcare needs while juggling life’s many responsibilities. Whether you’re driving kids to soccer practice or caring for aging parents, those moments in the car often become the only time to handle personal tasks —rescheduling appointments, contacting a nurse’s line, or asking billing questions.
This is why my work at Parlance matters so much to me. I design intelligent virtual assistants that make these interactions easier, faster, and more human for the millions of patients who still rely on the phone as their primary healthcare communication channel.
Bridging Design and Engineering
Before joining Parlance in 2021, I spent three years building AI–powered chatbots integrated with EHR systems—helping patients schedule appointments, view test results, and manage their care digitally.
My work now sits at the intersection of two worlds:
- Conversational design, where I craft intuitive, natural dialog flows that support patients with empathy.
- Software engineering, where I build backend logic, APIs, and routing systems that make those conversations intelligent and reliable.
Every health system operates differently. A faith-based hospital network has different routing rules than an academic medical center. A regional system with 20 clinics functions differently from a national network with hundreds of facilities. My job is to ensure that each organization gets a voice assistant tailored precisely to their unique workflows and patient needs.
Solving the Challenge of Proper Names in Speech Recognition
Speech recognition in healthcare is far from perfect. Background noise, diverse accents, and complex medical terminology often lead to transcripts that don’t match what callers actually said. A patient might clearly say “Dr. Molina,” and the speech engine might return something like “Carolina” or “Melina.”
To overcome these issues, I combine natural language understanding (NLU) with phonetic vector search techniques. NLU helps interpret the caller’s intent by analyzing context, linguistic patterns, and domain-specific cues. At the same time, phonetic vector search maps spoken input into a phonetic vector space, allowing the system to compare what the speech engine heard against known entities — provider names, patient names, medications, departments, and more. This dual approach enables Parlance to determine not just what the transcript says, but what the caller most likely meant.
It’s especially powerful when dealing with proper names, one of the hardest challenges in healthcare voice AI:
- patient names
- provider names
- clinic and department names
- medication names and diagnoses
Parlance has built proprietary tools that merge NLU reasoning with phonetic similarity scoring to find the best match — even when the speech recognition output is inaccurate. This capability is one of our strongest differentiators. In a domain where a single misheard name can derail a call, our ability to reliably identify proper names directly improves patient access and call routing accuracy.
Keeping Conversations Short and Effective
Great voice AI respects people’s time. Calls should be direct, efficient, and goal-oriented. If someone wants to schedule an appointment, the IVA needs to guide them to the correct workflow immediately — or connect them to a human agent if necessary. If the system cannot confidently understand the caller, it should gracefully route to a live support person.
The goal is always the same: get callers to the right help as quickly as possible.
The Managed Service Advantage
What truly sets Parlance apart is our managed service model. We don’t sell software and hope for the best. We take ownership of performance.
When onboarding a new client, I collaborate with their teams and our solutions engineers to define exactly how the IVA should behave — its conversational flows, business rules, routing logic, and success criteria.
Then we test, refine, and adjust. Healthcare requirements change often, and we evolve with them. Once the system goes live, the real work begins. We monitor closely, especially in the early weeks, to ensure:
- no misroutes
- no broken conversations
- no self-service failures
- no unnecessary call transfers
When issues appear, we fix them immediately. Each error represents a real person who may be struggling to get help, and we treat that responsibility seriously.
Health system IT teams are experts in clinical technology — not in optimizing switchboard operations or designing conversational AI. That’s why Parlance operates as a managed service partner. We deliver continuous improvement, real accountability, and long-term ROI
Why This Work Matters
I feel genuinely fortunate to contribute to improving patient experiences. When someone is sick or caring for a loved one, they shouldn’t have to wait eight or ten minutes to reach help. By reducing routine call burdens on agents and operators, we free them to assist patients with complex needs who need human support the most.
At the same time, we help health systems operate more efficiently and responsibly, ensuring they can continue serving their communities. As a working mother who often manages family healthcare needs on the phone while waiting in the school pick up line, I’m proud to design technology that makes these interactions less stressful for everyone — patients, caregivers, and healthcare staff alike.
By Ahlem Triki
