Generative AI could augment 40% of healthcare working hours

That's just one of the findings from new Accenture research showing how the algorithms behind apps like ChatGPT could fundamentally transform healthcare processes and clinical workflows.
By Bill Siwicki
10:29 AM

Rich Birhanzel, Accenture’s global health industry lead

Photo: Rich Birhanzel

A new report on generative artificial intelligence from research and consulting firm Accenture shows how advances in large language AI models – the technology that powers applications like ChatGPT – can transform the future of healthcare.

According to the report, the positive impact of generative AI on human creativity and productivity will be massive:

  • 98% of healthcare providers and 89% of healthcare payer executives agree that advancements in generative AI are ushering in a new era of enterprise intelligence.

  • 40% of all working hours in healthcare could be supported or augmented by language-based AI.

  •  Half of healthcare organizations plan to use ChatGPT for learning purposes, and more than half are planning pilot cases this year.

To dig into this new research and further explore the explosive topic of generative AI, we interviewed Rich Birhanzel, Accenture’s global health industry lead.

Q. So what's the big picture? How can advances in language-based AI – the tech behind ChatGPT – transform the future of healthcare?

A. The meteoric rise of ChatGPT has captivated the world’s attention on the power of generative AI to augment human capability. This technology has a massive opportunity to transform everything from science to business and beyond, impacting the creativity and productivity of people across industries – but the opportunity in healthcare is significant.

Generative AI, which consists of trained large language models (LLMs) that generate responses to specific natural language questions, can perform tasks like text classification, translation, summarization and question answering.

Trained on massive amounts of literature, LLMs can learn and understand the patterns and relationships between words and sentences and their meaning in context. They’ve not only cracked the code on language complexity, enabling machines to learn context, infer intent and be independently creative, they also can be quickly fine-tuned for a wide range of different tasks.

The biggest potential for generative AI in healthcare right now is to free up scarce clinical resources from many of the administrative tasks so they can work at the top of their license. A strong digital core and investments in people will be the key to reaping the full value of generative AI in a responsible and authentic way.

Organizations need to recognize that, in order to gain the full benefit of generative AI, they will also have to remodel the work done by human beings. Generative AI will take over some tasks, but not whole jobs. Those jobs in turn become different, and the people will need to have a way to repurpose that time to generate a benefit for themselves, their organization and society.

The key to unlocking value is understanding how to harmonize the technology with the humans doing the work.

Q. Your report contends half of healthcare organizations plan to use ChatGPT for learning purposes, and more than half are planning pilot cases this year. What would you caution these organizations about when jumping on ChatGPT so quickly?

A. People need to be the top priority. Generative AI applications in healthcare will depend on people to guide them based on human experience, perception and expertise. That means the organizations that focus on training people to work alongside generative AI will have a significant advantage.

Leaders will invest more in skills and advancing the organization’s abilities, rather than the technology itself. For example, we can expect a large number of new tasks for people to perform, such as ensuring the accurate and responsible use of generative AI systems.

Helping people – both clinicians and patients – keep up with technology-driven change will be the biggest factor in leveraging generative AI to create greater access, better experiences and improved outcomes.

Organizations also need to get their proprietary data ready. Foundation models for generative AI need vast amounts of curated data to learn, which means organizations need to take a strategic and disciplined approach to acquiring, refining, safeguarding and deploying data.

Fine-tuning the pretrained large language models with organization-specific data will allow for more accurate usage. Organizations need a modern enterprise data platform built on cloud with a trusted set of data products.

Lastly, there will be an urgent need to build in controls for assessing risks at the experimentation phase and embed responsible AI principles and approaches throughout the organization. The speed of technology evolution and adoption requires organizations to pay close attention to any legal, ethical and reputational risks they may be incurring.

Q. According to your new reports, 98% of healthcare provider executives agree advancements in generative AI are ushering in a new era of enterprise intelligence. What does this mean to healthcare provider organization C-suite executives and other health IT leaders at providers?

A. It’s clear from our survey that healthcare executives agree the positive impact of generative AI on human creativity and productivity will be massive. Our clients are already starting to look at what gen AI can do to help their organizations improve healthcare access, experience and outcomes.

Generative AI can help healthcare providers streamline the patient services process by automating many of the manual and time-consuming tasks, while also improving patient education.

One of the near-term opportunities for this technology to transform healthcare is the potential for it to substantially replace the need for active documentation and reporting that is done today by clinicians – both physicians and nurses alike.

Instead of a nurse or doctor recording information – from vitals to treatment plans – gen AI can listen to the conversation during the appointment and create a summary that can be added to an electronic health record. Additionally, the technology can also simplify complex medical language into summaries that patients can understand, and that can be easily translated into any language.

We are working with clients in the near-term to focus on exploring, experimenting and executing on generative AI adoption. The industry is optimistic about the potential of generative AI to radically change how work is done in healthcare, but also realistic about the challenges that come with rethinking how the organization works.

Q. Your report says 40% of all working hours in healthcare could be supported or augmented by language-based AI. Please elaborate.

A. Organizations will use generative AI to reinvent the way work is done. Every role has the potential to be reinvented. Humans working with AI copilots that can dramatically amplify what people can do will become the norm. Generative AI will impact tasks in many ways – some will be automated, some will be transformed through AI assistance, and some won’t be affected at all.

Healthcare organizations already have an enormous need to radically rethink how work gets done. The global clinician shortage is growing worse – healthcare workers are overburdened and organizations cannot hire or train their way out of this situation – they need to reinvent how care is delivered through the combined power of technology and human ingenuity.

Generative AI can create value by improving the efficiency, quality and performance of the workforce by reducing the time clinicians spend documenting and allowing them to spend more time with patients. Organizations that take steps now to decompose jobs into tasks and invest in training people to work differently, alongside machines, will have a big leg up on less imaginative competitors.

Follow Bill's HIT coverage on LinkedIn: Bill Siwicki
Email the writer: bsiwicki@himss.org
Healthcare IT News is a HIMSS Media publication.

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