A recent analysis report from Accenture showed that the market of AI in the healthcare market would
grow to around $6.6 Billion by the end of 2021. It also showed applications of AI in revenue cycle
management could create savings of $150 billion every year for healthcare organizations by the end
of 2026. But how do these AI applications work? Are they fruitful for use in both an independent
clinic and hospital chain setup? What are the investment and maintenance costs required? These are
the questions that cloud the minds of healthcare financial leaders when embarking on their digital
transformation journey.
Keeping yourselves updated on the real applications of AI in revenue cycle management will show you
how the returns surpass the investment and maintenance charges. These applications streamline the
workflow, assist providers in clinical setups, and improve the organization’s overall efficiency.
Here are a few advanced technologies that some of the large health systems use to ramp up their
efficiency.
Minimizing Delay in Charge Capture
According to the revenue cycle leaders, the charge entry lag is one of the crucial areas to focus
on. However, few organizations give it the required attention.
A survey published in Healthcare Finance showed that though 78% of the healthcare organizations
admitted that charge entry lag should be minimized, only 40% discussed it every month.
As per the revenue cycle leaders, the best practices say that the charge entry lag, the difference
in the number of days between charge capture and services rendered, should not exceed three days.
Some health systems are trying to incorporate the practice of capturing codes at the time of service
itself with the help of AI in revenue cycle management.
They often use mobile tools like customized apps which the providers carry on their phone during the
time of service.
Healthcare technology companies coming up with these applications say that these tools are designed
in a way that any provider without any prior
experience of charge entry
can use easily.
The providers can keep a tab on their most frequently used CPT codes and enter them into the system
once the visit is over. The entry sheet then reaches the coding team, who makes sure everything is
on point and sends it for claim submission.
Integrating the entire workflow in a single system has helped the organizations cut down on the
charge entry lag time, thus expediting the claim submission procedure and improving the efficiency
of the revenue cycle management in the organization.
Apart from these AI applications, the monitoring reports on charge entry lag can also help the
management make the right call on the changes in the system.
Tracking Key Performance Metrics
Improving the efficiency of the revenue cycle management requires the staff to collect regular
financial data and analyze them to know the areas in the workflow that need change or advancement.
However, amidst the tightly wound schedule of the providers, it is unreasonable to set such a goal
where they will analyze these reports.
This is where modern applications of AI in revenue cycle management come into play. They have
identified the pain points in your financial management journey and come up with solutions to the
specific problems.
Revenue cycle management leaders are of the opinion that improving financial efficiency is a dynamic
affair and therefore needs regular monitoring of the key performance metrics.
Advanced AI healthcare tools work in a similar way and come up with analysis reports on a weekly or
monthly basis. Depending on the layout of the tools, you can also customize your dashboards, and
subsequently, the data reports that you need.
Leading revenue cycle management companies come up with homegrown solutions of their own to help you
excel in these areas. In some other cases, if you already have an RCM partner, they might send you
such reports so that you can keep the parameters in check.
The AI applications also simplify the physician’s work routine significantly. For example, these
applications keep the entire organization in a loop with a cloud or server storage for clinical
information.
The providers save up on time looking for their clinical notes and charge capture sheets since they
find it all in one place. These AI applications thus transform the workflow of the organization for
the better while keeping the metrics available for viewing.
Physician Engagement in Financial Management
Engaging physicians in improving the overall efficiency of the organization is crucial to see any
real difference in the organizational functionalities.
Experts believe that physicians suffer the most under the burden of paperwork and other formalities.
Coupled with tight time schedules, it leaves them with little time to offer.
The best way to engage physicians in financial management functions is to enable them with advanced
tools of AI in revenue cycle management. Integrating the entire work ecosystem within a single
platform can prove to be highly beneficial in this case.
The other great way to achieve financial scalability goals is to partner with a leading RCM company
that can provide these services for you.
They use data optimization tools within their organization and send you the required reports on a
monthly basis, highlighting the areas where you need to scale your system.
They also provide homegrown customizable solutions with good customer support services to help your
team operate the software on their own.
Experts believe that the ultimate goal is to improve the patient’s clinical outcome while boosting
productivity and yet maintaining a healthy work-life balance. Though these goals seem far-fetched,
AI in revenue cycle management can help you advance in that direction.
Tracking the number of patient encounters in a day, capturing the codes without delay, collecting
the data, and analyzing those reports for a rational prediction will structurally improve the
revenue cycle management of the organization.
We hope this article helped you understand how you can ramp up your organizational efficiency with
AI in revenue cycle management. For any queries, connect with us in the comment section below.
Please subscribe to our blog for more such articles on healthcare technology and management. Follow
us on LinkedIn,
Twitter,
Instagram, and
Facebook.