Common holes in the revenue cycle
Hospitals are constantly battling denials
as payers require authorization for more types of procedures or adjust policies without any notification to providers. A denied claim triggers effects that spill over to disrupt other aspects of the hospital’s finances, too. For example, after a payer denies a claim, administrators are forced to chase the denial, which often requires multiple calls to the ordering physician and working closely with the payer. This is a time-consuming, and not always rewarding, process. The claim then sits in accounts receivable until it is adjudicated, which can take weeks – even months.
Reprocessing claims drives up labor costs as billing staff is forced to devote more time to unpaid claims. According to research
from the American Medical Association, the industry could save $15.5 billion each year if companies processed claims correctly the first time.
The hospitals and health systems I have worked with have pointed toward lower dollar accounts as another key area where revenue is lost or delayed. That is because hospitals often lack sufficient resources — such as staff or budget — needed to touch each and every patient account. What ends up happening is organizations focus primarily on the high-dollar accounts, which means many low-dollar accounts slip through the cracks. Unfortunately, all those missed payments from low-dollar accounts add up.
Hospitals often turn to an outsourced vendor
to tackle these low-value, high-volume accounts. But similar to in-house teams, these outside partners aren’t always able to physically act on all accounts.
On the bright side, there’s a potential solution for this persisting challenge: inserting AI into revenue cycle processes.
Improving the revenue cycle, starting with artificial intelligence and automation
As leaders devise revenue cycle improvement plans, they should consider how various solutions could affect bottom lines and operating margins. Leaders should also determine the resources needed to fulfill plans, such as an outsourced partner or a tool built in-house or purchased elsewhere. AI-enabled automation is one such tool that may help.
This intelligence-based category of automation tools frees staff from necessary but redundant and time-consuming tasks, and it enables the organization to reposition skilled workers toward meaningful work like quality assurance programs within the revenue cycle. Automating some processes within the revenue cycle is an affordable way for organizations to reduce labor costs and recover leaked revenue because it enables organizations to touch both high- and low-dollar accounts.
When hospitals automate portions of the revenue cycle, they can execute a higher volume of claims at a cost-effective rate and regain their edge. And as the machine learning components of this automation learns, it unleashes meaningful insights to the organization and allows for continued opportunities for efficiencies and increased revenue recognition.