Reducing Bottlenecks in Healthcare Systems
with voice technology
- Voice & Chat
With a focus on forward-thinking innovation, we explored user problems in the healthcare space with industry stakeholders. We discovered an opportunity to address an operational bottleneck resulting from patient confusion around treatment and appointment information.
We extended our voice and chat framework with a domain specific natural language processor and symptom diagnosis engine. It provided patients with a personalized experience, providing assistance specific to their care throughout the full lifecycle of an appointment. Attention to detail included driving directions, reminders, custom Q&A, and follow-up information.
The solution proved effective in diagnosing patients quickly. The framework was tested to carry out diagnoses on 520 unique patients. Based on keyboard inputs, the engine took an average of 41 seconds to give an accurate diagnosis. Voice inputs also resulted in an impressive 53 seconds average time to diagnosis.
Seconds - Average Time to Diagnosis (Keyboard)
Seconds - Average Time to Diagnosis (Voice)
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