How to Build a Back to the Basics Approach to Revenue Cycle Management?

Most of the healthcare revenue cycle leaders emphasize on how they plan on putting more money into their technologies for boosting revenue and eliminating the risk of human error so that efficiency can be enhanced. 

However, the major hurdle that organizations face, which prevents them from improving their performance, comes in the form of data.

Despite digital innovation and automation making waves, it does appear that healthcare organizations have a lot to do. They have to address the concerns of the consumers who are worried about the increasing costs that lead to slow payment. They need to give attention to improve the patients’ experience with regards to finances as well. 

Furthermore, initial denial rates have to be reduced while the performance is optimized.

Some steps to take

There are some measures that can make things easier, for example, improved price transparency while increasing patient financial engagement.

Transparency is something that needs to be given the utmost attention by healthcare leaders. If health systems fail to provide consumers with adequate price transparency, they will find it challenging to engage them in financial responsibility. 

Data analysis is used by leading health systems for a variety of reasons. They determine out-of-pocket costs and also access the ability of the patient to pay the bills. The data analysis also allows them to gauge the chances of the patient paying the bill considering his past behavior in this regard. 

Accessing this data can ensure that revenue cycle leaders focus on those accounts where there would be more chances of receiving the payment. This enhances efficiency and also reduces the cost of collection.

Determine hurdles in prompt payment

Data analysis can allow revenue cycle leaders to determine the breakdown in the cycle at initial stages. This is of immense importance. 

For instance, if an organization has a high rate of discharges not being billed, it prevents speedy claim submission, and their cash flow is affected. Data analysis can make it easier for such organizations to determine which medical records can be used for holding claim submission, and where to focus on preventing these instances. 

They can also determine if certain staff has been taking longer to provide information supporting medical necessity. Hidden inefficiencies in claim handling can be uncovered via analyzing the claim processing. 

When they have all the required information at hand, revenue cycle leaders will be able to make the right decision, allowing staff to work around the specific type of claims effectively. 

Preventing denials

Data analysis makes sure that revenue cycle leaders get a clear idea about the origination of errors in claim processing and claim rejections. Perhaps proper authorization is not obtained beforehand, or some additional documentation is needed. 

A timely filing can be another reason.

Detailed analysis can make sure that these denials are prevented, and no process is hindered due to them. Health systems can make use of software that allows them to verify the eligibility of the patient and his information during registration. 

Learn how our AllPayor® Software is saving other organizations $$MILLIONS!

If you are interested in a free demo of our AllPayor® Software, please go HERE or you can register for a FREE webinar HERE