The topic of cutting costs from the U.S. healthcare system rightfully garners a lot of attention. American consumers continue to grow concerned about the affordability of healthcare and health insurance—while healthcare spending is expected to grow 5.5% annually over the next decade as the population continues to age. From the provider perspective, healthcare systems face shrinking reimbursements, business transformation, and legislative uncertainty that are driving a relentless focus on cost reduction and the ability to generate additional revenue.
In fact, according to a recent survey from The Health Management Academy (“The Academy”), 90% of executives rank cost reduction as a “high or very high priority.” Moreover, almost all of the responding executives indicated that the priority level of cost reduction has increased in the last year. Respondents indicate that system-wide, they are focusing cost reduction efforts in the areas of labor, such as holding off on new hires and new positions; supply chain; and pharmacy, while remaining hesitant to cut costs in cybersecurity and IT including electronic medical records (EMR) implementations.
In addition, about one-third of respondents to The Academy’s survey indicate that generating additional revenue will have the greatest impact on their organization’s finances over the next five years.
As healthcare organizations face continued cost pressures, they are turning to the newest generation of clinical documentation technologies that rely on artificial intelligence (AI) and machine learning to help them realize financial improvements.
Let me give you some statistics: Nuance’s AI-powered solutions adapt to existing, natural workflows to improve productivity by up to 54%, and to free up about two hours per clinician, per shift. Productivity improvements certainly contribute to cost-reduction efforts. But more importantly, the extra time in a clinician’s day means spending more time with patients and less time on documentation, a combination that leads to greater satisfaction and potentially a positive impact on the mounting problem of provider burnout.
AI-powered solutions also make a more secure path to reimbursement achievable—from guaranteed case mix index (CMI) improvements to significant increases in Medicare admission reimbursement. For example, AI enables real-time clinical guidance to help providers capture patient stories more fully and accurately, and with this higher-quality documentation, it becomes much easier to receive appropriate reimbursements for the care provided.
We at Nuance expect AI-powered solutions to be among those strategies that produce the most value for health systems in the coming years—and we’re not alone. In a research report entitled “Artificial Intelligence: Healthcare’s New Nervous System,” Accenture indicates that the AI market is not only seeing “explosive growth,” but is estimated to generate $150 billion in annual savings for the U.S. healthcare economy by 2026.
It is truly an exciting time to be working in this space, and the conditions are right to make big moves that position the health systems for long-term success.