As healthcare organizations struggle to serve an aging patient population, address more complex and serious disease states, and deal with rising costs and labor shortages, they rely more heavily on insurance companies to expedite claims processing to effectively manage their revenue cycles. These insurance companies, however, face their own challenges in 2022. Here are the top five challenges for claims processing–and the best way to overcome them.
1. The Great Resignation
Although lack of skilled and engaged workers is a problem in many industries, it is reaching epic proportions within the insurance sector - specifically, within claims processing. In the aftermath of the COVID-19 global pandemic, there are 4.3 million more job openings in claims processing than people looking to fill them. Additionally, roughly 58 percent of all claims processors stay in the same job for less than two years, which means that employers are contending with retention in addition to The Great Resignation.
2. Decreasing Premiums
With a greater focus on value-added care, both payers and providers face downward cost pressures to provide more services for less. In fact, a study by one insurance expert found premiums for the Affordable Care Act plans essentially staying the same in 2022 despite rampant inflation. This clearly affects revenue generation, with overall profits falling 15 percent since 2019.
3. Increasing Data Volumes
Not only does the increasing number of patients boost the volume of data, but more sophisticated technology generates a rising number of data points per patient as well. As a result, claims processing must find ways to read, categorize, manage, and use this data more efficiently. Data volumes - and the inability to effectively harness the information - is a problem plaguing many industries. According to Fortune, “the bottom line is that too much data results in too much noise and compromises the performance, profitability and security of any enterprise.”
4. Tight Regulations and Timeframes
As government regulators try to address some of these issues, they increase compliance requirements and shorten timeframes. For example, the recent No Surprises Act specifies tight timeframes for filing initial claims as well as dealing with ones that require further review. This adds to the costs for insurance companies in potential fines for missing deadlines or inability to collect on claims that have fallen outside specified timeframes or requirements.
5. Increasing Costs to Process Documents
Overall wages are rising; fewer people are interested in repetitive, boring work; and the rapid turnover in the claims processing industry means high recruiting, retention, and retraining costs. These increased costs - along with the rising volumes and downward cost pressures - make it unsustainable to rely solely on employees to process claims for the long run. Even traditional options such as business process outsourcing are less effective, as the shared services industry is facing the same challenges as the insurance industry.
Overcoming These Challenges
Artificial intelligence technology today is able to step in and provide true relief to these claims processing challenges. Roots Automation Document Vision is an advanced plug-and-play solution technology that automatically reads common insurance documents, including the widely used CMS-1500 and the UB-04 forms.
The system makes human-like inferences about which boxes are checked even if they are not exactly marked, can effectively read blurry or skewed scans, and manages incomplete forms. Document Vision recognizes a wide range of other documents as well including medical or pharmacy ID cards, policy documents, and more to extract needed data.
By essentially “employing” automated digital assistants that can handle claims processing around the clock, insurance companies have an infinitely scalable solution that can meet increasing volumes at an affordable cost.
Read more about how our Document Vision solution can improve your document processing cycle time, reduce cost and free your people from mundane work.