What industry does artificial intelligence (AI) have the potential to transform most?
For many observers, healthcare is the obvious answer.
Yes — that healthcare. The same fragmented industry riddled with legacy manual processes where doctors, nurses, and administrators alike remain drowning in paperwork while rooting from the sidelines for the snail’s pace of healthcare’s ongoing digitization to speed up.
These problems, the ones costing providers significant amounts of time and resources, offer a change-the-game opportunity for the applications of AI models to create a connected, ambient patient environment that streamlines healthcare’s increasingly complex and sprawling administrative workflows.
Workflows that are frequently caught in the middle between digital modernizations and historical bottlenecks.
This, as Amazon Web Services (AWS) on Wednesday (July 26) debuted AWS HealthScribe, an AI for healthcare solution that leverages speech recognition and generative AI to generate clinical documentation, saving clinicians time summarizing patient visits and improving care delivery.
At the same time, Google Cloud and Mayo Clinic are already collaborating to use generative AI in healthcare themselves by providing solutions that to enable clinicians and researchers to find information in a way that is fast, seamless and conversational.
For its part, Microsoft last year spent $16 billion buying AI speech technology firm Nuance Communications, whose transcription technology offering designed for doctors serves more than 75% of U.S. hospitals.
Ambient clinical intelligent offers a sizably attractive greenfield opportunity for major tech players to plant their flag in the healthcare space.
But will generative AI prove to be the silver bullet in helping to leapfrog the healthcare industry straight from its present paper world into an always-on connected ecosystem powered by AI, where healthcare providers can focus on the patient and not on typing notes?
Most healthcare processes, from how to transfer types of information to ensuring that safety protocols around patients’ visits are in place, are still done manually today.
But AI for healthcare remains a bold bet, and not just on tidying up a messy history of documentation — but of reframing the entire provider-patient relationship around the opportunity of connected technologies that reduce or entirely remove the need for manual intervention and hand-typed transcriptions.
Faster, AI-assisted diagnoses have the potential to lead to faster treatment, in turn producing better and more repeatable outcomes.
Doing them right could change everything.
By using innovative generative AI tools to create an always-on, ambiently connected environment, providers can free themselves up to devoting more time to creating innovative clinical care and research solutions for their patients, while spending less time building, maintaining, and operating the foundational health data capabilities of their practice.
After all, AI for healthcare has never been about replacing doctors — but doctors who use AI might end up replacing those physicians who don’t.
He added, “AI doesn’t replace work; it changes how work is organized.”
Clinician and provider burnout remains a significant problem area for the healthcare industry.
That’s why the embedded potential for leveraging voice enabled AI solutions to automatically document patient encounters is so huge.
Findings from PYMNTS’ landmark March 2023 study, “How Consumers Want To Live In The Voice Economy,” reveal that around 4 in 10 consumers believe it will be less than five years until voice recognition technology is advanced enough to make speaking to voice assistants comparable to speaking with actual humans.
Ambient clinical intelligence can help connect historically disparate and fragmented data to give providers a more unified picture of patients, streamlining physician workflows by removing the need, and the time it takes, to cross-reference information pulled from mix of physical and digital documents.
This connected trend is gaining velocity as patients, health systems and insurers seek more seamless solutions to everything from initial diagnosis to final payment.
And with generative AI taking off exponentially, companies are promising labor- and cost-saving applications in every field, including Healthcare, according to “Preparing for a Generative AI World, a PYMNTS and AI-ID collaboration.
However, there doesn’t appear to the be prospect of any AI regulation in sight — and healthcare is an area rife with both opportunity and sensitive personal data.
AI models need data, and data is different in healthcare, which makes any successful integration of next-generation AI tools, especially those that affect care decisions, a challenge to scale while also ensuring patient safety.
While the healthcare industry charts its path forward amidst a tectonic shift in available technical capability, it is critical that the industry provide a leading example to other sectors as it relates to ensuring both patient-data-privacy protection and leveraging only the most relevant and professionally cleared data sets when tapping AI solutions to improve the quality of the product being provided.