Voice AI boosts healthcare efficiency with human-centric innovation

The global healthcare system is facing unprecedented challenges: physician burnout affects 63 percent of clinicians, administrative costs account for 25 percent of hospital budgets, and patient waiting times continue to grow. In this context, Voice AI has the potential to be disruptive, with a projected reduction of $150 billion to the healthcare system by 2026, when Voice AI is a harmony and widely adopted.

We believe that progress with technology happens not with removing the human contribution, but with increasing it, which can be further defined by three basic principles: by keeping the human in the center, being omnipresent yet invisible, and having agentic AI autonomy.  The largest impact Voice AI can have is bringing the health and care system back to its center - human beings.

Clinicians spend upwards of 44 percent of their work day involved in EMR documentation which we know is directly related to increasing rates of burnout. Voice-enabled solutions are now able to decrease charting time by 50 percent through on-site, real-time speech-to-text capabilities, which help physicians to facilitate handwriting natural notes without removing eye contact from the patient.

This returns human interaction to patient care - just like a nurse can monitor a critical case and without needing to constantly use their hands to track documentation verbally, Voiced AI is effective technology that works with humans.

For patients, voice interfaces are a way to narrow the gap on the accessibility of health care. Rural populations benefit from 24/7 triage support, through multi-lingual AI assistants programmed to recognize 50 regional dialects,  as well as elderly patients may not be tech-savvy but can easily schedule MRI scans through voice commands, shortening no-show rates  by 18 per cent with the modified process. In addition, it is possible that brokering these systems may even use emotional recognition algorithms to pick up inflexions in anxiety or pain sequences to elicit empathetic responses and escalate urgent requests.

 The most effective technology in healthcare is typically woven into the flow of work rather than demanding engagement.  Voice AI technology can seamlessly insert digitally preserved per-provider-patient conversations, use NLP to distill down to relevant medical entities, fill in fields in EMR,  and it does it all without having to leave the screen view. Your days of flipping back and forth between screens are over - it’s the same dynamic to your body’s interaction with oxygen - oxygen is essential, useful, but unnoticed.  The similar invisibility has been incorporated into infrastructure where this kind of voice AI tech systems are integrated into IoT structures.

For example, surgeons can now verbally amend notes while in surgery and radiologists can independently retrieve prior scans while consulting the group. The voice-data pipelines are also embedded in back-end processes which ultimately serve predictive analytics models where early episodic phases in disease detection practice with an example of determining bouts of sepsis is detectable nearly 12 hours in advance of the traditional medically-based determination process. These examples demonstrate that when the systems incorporate AI to help humans with their intent similar to human’s experiences rather than serving as a standalone interface, the result is enormously impactful.