By Valerie Barckhoff, principal and healthcare advisory practice lead, Windham Brannon.
Hospitals and health systems throughout the country are constantly looking for ways to streamline finances and fine tune operating margins. Many are now looking outside the box for solutions to help increase their operating revenue and combat the continued pressure to stretch budgets to include data security, attracting top talent and facility upgrades. Artificial Intelligence (AI), as an example, is showing promising results in healthcare to more effectively address revenue cycle inefficiencies.
AI has penetrated nearly every touchpoint in medicine, from the way emergency medical technicians (EMTs) are dispatched to assisting physicians during surgery. AI is enabling smart devices to detect cancer or a stroke, and consumers can even get help to quit smoking or address opioid addictions with the help of AI. So, it was only a matter of time to apply AI to tackle health revenue cycle inefficiencies. But how?
RCM Represents Prime Opportunities for AI
Even as revenue cycle management (RCM) becomes increasingly more complicated, there are a number of repetitive and predictable processes involved that make it an area perfect for the efficiencies that AI and intelligent automation offer?for instance, prior authorizations.
Prior authorizations, the process by which insurance companies and payers determine if they will cover a prescribed procedure or medication, are meant to help patients avoid surprise bills and unexpected out-of-network costs. However, this largely manual process is time-consuming and error-prone, resulting in $30 billion in annual costs for wrongful denials, inefficiencies and clerical errors. AI can reduce the need to assign resources to repetitive, “simple” pre-authorization requests, allowing healthcare leaders an opportunity to deploy staff to more complex, acute requests that require additional clinical information, peer-to-peer review, and/or other payer required information
Studies show that 84% of physicians surveyed said the burdens associated with prior authorization were high or extremely high, and 86% said the burdens associated with prior authorization have increased significantly (51%) or increased somewhat (35%) during the past five years.
The ability to apply AI to the revenue cycle provides yet another tool to identify inefficiencies, then allow hospitals to redesign their processes and re-allocate internal resources to maximize their net revenues going forward? to focus on more patient care instead of administrative burdens. There is a huge opportunity to gain 25- to 50-percent efficiencies for hospitals and health systems.