Best Practice For Hospital Credit Balance Resolutions

The experience acquired from working with clients indicates that an average hospital revenue cycle management employee takes a minimum of 15 minutes to research and resolve just one credit balance account using the conventional methods. That adds up to just 32 accounts per day (having a duration of 8 hours) or only 160 accounts per week. A medium-sized hospital’s patient accounting system creates at least thousands of credit balances per month. With a team member resolving as little as 32 accounts per day, it becomes difficult to resolve the daily churn of new credit balances.

Credit balance management is an overlooked aspect of every revenue cycle, in spite of the potential risks associated with neglect, including missed payment opportunities and the penalties associated with the regulatory and managed care requirements that are not met. To enable the streamlining of the credit balance resolution process and to make efficient use of valuable staff time, organizations should consider the option of using technologies to enhance and automate their reviews and resolutions.

Why automate the process?

Machine learning algorithms allow automated systems to learn how to resolve credit balances by following the below steps: 

1. Examining all the prior resolution activities 
2. Identifying patterns followed in the data
3. Using those patterns to predict the best way to resolve an account

This technology can help an organization with a faster resolution of credit balances. It also gives the team members more free time in hand so that they can focus more time on addressing accounts with complex decision points, including the account resolutions that require follow-up with the payers.

Steps to automation

Here are five steps an organization can take leading up to automating credit balance resolution through the use of technologies such as machine learning.

1. Identify resolutions to which technology can be applied. 

Accounts that are monotonous and simple and that don’t require much human judgment to resolve are the best ones that can be sent for automation. Some of the examples include correcting the adjustments made or resolving the credit balances created when a patient’s payment is made after a bad debt adjustment.

2. Determine the best resolution processes. 

The hospital management & administration should establish an organization’s performance standards by reviewing existing processes thoroughly and determining the process that yields the best results.

For example,  let us consider an organization having a team of 10 people resolving credit balances. Some team members are likely to be working more efficiently than others. The leaders should identify those high-performing team members and determine the processes followed by them to resolve credit balances. Also, leaders should exclude any underperforming processes that hamper the team’s workflow.

3. Standardize best practices for credit balance resolution. 

Armed with a comprehensive understanding of how to work credit balance accounts effectively and efficiently, leaders can agree on a set of the best processes for their organization to follow. These processes must be included in the documentation regarding credit balance resolution and should be communicated to all the staff as well as the technical resources with which the organization works. To help standardize best practices for resolving credit balances, an organization can take the following measures:

• Ensure that the staff are educated about the processes.
• Include defined reporting and tracking of staff performance.
• Align performance management related to the resolution of the credit balances with overall performance management metrics.
• Define a process to ensure that all staff members are following the same guidelines and using the same processes.

4. Systematize the best practices involved in the resolution. 

Once an organization has identified the most efficient processes for resolving credit balances and instituted them as its standard policies, it can go ahead with the integration of these processes throughout the hospital revenue cycle management system. Further, it can move towards the use of more advanced technologies, such as machine learning, to improve these processes.

5. Automate work steps within credit balance resolution. 

As an organization more proficiently incorporates technologies into its credit balance resolution workflows, it can fully and confidently automate certain resolution processes of the credit balance. Ideal types of accounts to be automated, are the ones that are tedious and do not require a human touch, but automation also can be extended to other types of credit balances too.

6. Have a look at the outside resources

Resolving credit balances can be a costly activity in terms of time and money. Automation is one way to improve the overall workflow and make optimum use of the available and valuable human resources.

Many organizations may not have the in-house technology or staff resources available to take advantage of the full benefits of technology. Healthcare organizations should consider outsourcing these services to third-party specialists who can have a better look at the patient’s accounts, transitions the organization to a more technology-based credit balance management process, leading to improved credit balance resolution while reducing organizational risk.