The AI revolution in healthcare is here and quickly evolving. In recent years, leading health systems have invested in an operational transformation to emulate what other asset-intensive service industries, like airlines and package delivery companies, have done by embracing the power of analytics, machine learning and AI. In particular, many have adopted progressively advanced analytics, going from the “descriptive and diagnostic” levels that simply display capacity limits or patient bottlenecks, to the “predictive and prescriptive levels” that use AI/ML to predict likely future patient volumes or appointment needs and suggest the best ways to meet them. Now the next level of this spectrum, generative AI, has emerged.
In a survey published by Bain & Company in August 2023, 75% of health system leaders responded that they believed generative AI is now at a point where it can transform the healthcare industry. Only 6%, however, stated they had a strategy in place to leverage the technology.
There is a clear opportunity for healthcare, formerly behind other industries in adopting new technologies, to embrace and lead this generative AI transformation. Building on the foundations created during the recent digitization of healthcare, and by beginning with small-scale, manageable use cases that have the potential to make a lasting impact on workforce experience, health systems can navigate and optimize this latest advancement in AI.
Leveraging Healthcare’s Rapid Digitization Experience to Adopt Generative AI
The challenges of the past few years have delivered increased innovation and adaptation in healthcare technology and its use. Health systems have leveraged technology to digitize care delivery where possible and to meet safety standards like social distancing requirements. Increasing constraints on physical capacity made operational improvements essential. Health systems adopted advanced analytics solutions to optimize the space and schedules they had to sustain revenue streams and maximize patient access. In doing so they also developed the knowledge, experience and infrastructures needed to continue adopting new technology successfully.
Many health system leaders have already established precedents for the change management strategies their organizations need to adopt this new technology. Likewise, many IT teams have implemented cloud infrastructures and set high standards for data hygiene. With these foundations in place, health systems are prepared to adopt generative AI, further streamline operations, and improve patient and clinician experiences at a time when patient demand and staff burnout are both rising.
How Generative AI Can Connect and Empower Staff for Better Outcomes
Generative AI is a working technology that can easily be applied to healthcare operations. It can draw on the wealth of existing and digitized healthcare data to give leaders, providers, and staff easy insights and predictions they most need to supplement their skills and expertise. Through the use of large language models, generative AI solutions can conduct human-like conversations with their users, giving immediate data-backed advice and responses in helpful terms.
Leading health systems are already seriously engaging with this new technology. To build quick wins and buy-in, they are beginning with focused, low-cost use cases with some near-term return on investment while developing the experience, knowledge and confidence needed to invest in a larger vision. In healthcare operations, three methods come immediately to mind to help healthcare staff enhance their decision-making, foster continuous improvement and deliver ROI:
- Get clear answers to crucial questions simply “through a conversation.”
With a generative AI solution, nurses can simply talk to a chatbot and get up-to-the-minute staffing or unit recommendations, leaders in the OR or infusion center could seek answers for optimizing schedules, and hospital administrators can ask for insights on volume or utilization trends. These conversations are founded on existing data and provide fast yet powerful insights and recommendations to smooth patient flow and optimize capacity, day-to-day and in the long term.
- Receive instant warnings and suggested solutions.
Even when staff are not actively engaged with technology tools, generative AI has the capacity to proactively alert them to potential issues. Automated emails and text message alerts on all staff devices can flag capacity issues like potential discharge barriers and recommend next steps to address them. Staff can then take prompt action and stay ahead of obstacles, using their expertise to drive efficiency, minimize disruptions and grow more adept at foreseeing future capacity issues before they arise.
- Problem-solve “in the moment.”
By continually monitoring processes and data, generative AI can immediately detect and flag deviations from standard protocols. This equips users to address potential safety or operational issues before they escalate. Generative AI tools can also give immediate mitigation recommendations to flex assets and resources from underutilized areas to those that are at capacity, enabling staff to act accordingly and ensure the highest level of patient safety and quality of care.
As it helps and empowers healthcare staff in critical areas of their work, generative AI enables data-driven decision-making, enhances operational efficiency and promotes a culture of learning, discovery and innovation. This new technology is positioned to not only improve outcomes but to drive the future of healthcare forward—and healthcare, now, is positioned to adopt it.A trusted partner who understands the applications of analytics and the cutting edge of AI, as well as the best use cases to generate immediate ROI, can help fulfill the potential of generative AI to transform operations and optimize staff. Learn more about generative AI and how it can help your health system by scheduling an Executive Briefing.
Sanjeev Agrawal is president/COO, LeanTaaS.
A Premier Corporate Partner of ACHE, LeanTaaS provides software solutions that combine lean principles, predictive, prescriptive analytics, and machine learning to transform hospital and infusion center operations. For more information, visit ache.org/LeanTaaS.