Medical billing has undergone a series of transformations in the last few years, especially since
the pandemic. While these changes have severely affected the workflow functionality of the billing
and coding professionals, there have also been some changes on the patient’s end. With the changing
healthcare ecosystem in the last couple of years, the responsibility of the patients has
significantly increased, thus increasing the pressure of collections with the healthcare
organizations.
Reports from TransUnion Healthcare suggest that patient balance after insurance (PBAI) jumped from a
mere 12% in 2012 to 67% in 2017. The numbers continue to grow, putting excess pressure on the
collection team of the healthcare organizations to retrieve the revenue flow. Adding value to the
billing ecosystem is not a simple task in such changing situations. Experts believe that AI in
healthcare is the only way to move forward if you want to make the most out of your current
management system. Artificial intelligence-induced tools and deep learning functions will help you
move forward in your medical billing system while adding value to your organization.
Reduction in Cost
Reducing the cost of the revenue cycle management function is one of the top goals of any
organization when it comes to deciding on investment in technology.
Reducing the overall expenditure of the whole procedure adds great value to the system. But without
the proper knowledge on the implementation of AI in healthcare, most medical organizations shy away
from using them.
Manual collection of revenue and payment posting process leads to several errors, which in turn
increases the different costs related to the revenue cycle management.
Organizations realize that they lose out on a significant amount of profit when they factor in the
repeated labor costs that entail when manual mistakes occur.
At the same time, manual processes do not offer sufficient insights related to claim denials and
remittance posting, which could help the organizations to strategize their future plan of action.
Modernizing AI in Healthcare
AI in healthcare has taken huge leaps in some healthcare organizations, while some health systems
are still not on their road to digital transformation at the enterprise level.
Streamlining the infrastructure of the billing ecosystem is crucial when it concerns improving the
procedures and adding value to the organization.
Modernization of artificial intelligence-based systems helps solve complex issues of the revenue
cycle system while supporting the billing teams in their usual functions.
With modernized AI systems in healthcare, you can easily prioritize your goals in the organizational
workflow. These features will help you work towards your long-term goals while simultaneously
working on the regular functions.
Superior technology platforms in healthcare will also enable the billing staff to work better,
eliminate clerical errors and do away with unnecessary delays in revenue movement.
Stopping the Patient Payment Leakage
The patient’s responsibility for the medical bills has been on the rise for the last few years.
Healthcare organizations need to keep track of these issues while managing their billing system.
Medical billing management focuses primarily on the government and commercial payers while
strategizing their future action plans. But manual processing of billing systems provides minimal
insights into the patient’s account.
This is the reason why most healthcare organizations are suffering from undue loss, often termed in
the system as ‘patient payment leakage.’
With the right tools of AI in healthcare, you can keep a separate maintenance file on patients’
responsibilities and how you can approach them to ensure maximized collections.
AI tools have the ability to extract and analyze crucial data from the EOBs/EOPs, provider’s
organizations, and their RCM system. With a deeper view of the transactional details and unique
situational factors, organizations will be able to know how they can improve their patient
experience while decreasing their due collection time.
Automated Remittance Posting decreases Risk
Healthcare organizations depending on manual payment posting processes are bordering on risky
workflow management related to the revenue cycle, which is a crucial factor in maintaining the
organization’s financial health.
According to a report from the market research firm called Eliciting Insights, about one-third of
the hospitals have not deployed any automation system to handle their payment posting services.
The manual servicing of these duties, on the one hand, can lead to uncalled-for mistakes in the
payment cycle. The critical issue is that these mistakes often go unnoticed till the very end till
the claim undergoes denial.
The labor charge for the repeated functions adds to the financial stress of the organizations while
also delaying the revenue flow. All these factors increase the cost to collect for the organization.
Using
automated remittance posting systems decreases
the possibility of these risks and simultaneously improves the efficiency of the revenue cycle
management, thus adding value to it.
Hybrid Electronification
Some healthcare systems have admitted that they have not started on their AI journey due to the lack
of guidance on what to do with the previous paperwork.
Hybrid electronification combines your historical data storage done manually along with the current
digital files.
Deep learning as part of AI in healthcare could help you overcome these issues and provide you with
the right mix of opportunities to jumpstart your digitization journey.
Some health organizations have increased their presence on online portals and downloadable PDF files
to mark one step ahead in the game. However, deep learning technologies can take you way further by
digitizing EOBs/EOPs and PDFs and converting them into data.
For proper assistance on these platforms, it is advisable to talk to professionals from healthcare
software companies who can guide you through the entire process according to the organization’s
unique needs.
You can get in touch with professionals from leading revenue cycle management companies too, who
have already absorbed the digital tools in their organization. You can also outsource your
end-to-end revenue cycle management or specific services to these teams of competent domain experts.
We hope this article helped you get a deeper understanding of how you can add value to your medical
billing system with the help of AI in healthcare. For any queries, connect with us in the comment
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