Artificial Intelligence In Revenue Cycle Management

1. Introduction

We heard about AI taking over people's jobs and recreating the world. Now the AI has turned to solving some pressing issues in the revenue cycle.

Surely a machine can analyze a huge amount of data in a commendable amount of time, but what else can it do? Let us explore the idea of AI in the revenue cycle management. Before we dig deep into why AI is being introduced in dealing with RCM let us understand what AI is.

3. What Is Revenue Cycle Management?

The healthcare business is booming with the recent outrage of a pandemic and by the overall increase in healthcare awareness amongst people. RCM is a process in this very sector of managing and collecting payment for various medical services. It is charging a patient for the medical facilities that were provided by the healthcare organization.

RCM is an important part of any healthcare organization as this is to cover the costs and generate a profit so that the organization can run smoothly. Any healthcare organization needs a successful RCM for running the practice. But why the sudden need of AI to handle the Revenue Cycle Management? What has changed?

It seems that the new healthcare policies have all shifted towards holistic health of the patient and so is the treatment provided to them. Rather than trading just the illness, healthcare organizations also take into consideration the mental health of the patient. With this approach there is a need for practices to change their revenue cycle management.

4. How Will AI Assist In Managing The Revenue Cycle?

As described earlier AI is an efficient assistant who manages to do all the human tasks with more ease and accuracy. And recently AI has been introduced into Revenue Cycle Management. This Artificial Intelligence has brought many ideas and solutions to the table which is beneficial to healthcare providers by resulting in increased revenue.

The most important task that AI has taken over is preparing medical bills with no possibility of human error. With the increasing complication in the Revenue Cycle , AI is here to help out with the crucial task of accurate billing. Here's how AI will modernize the whole process of Revenue Cycle Management:

Claim Denial:

• With the help of AI a revenue cycle manager can easily identify troublesome claims.

• With the help of AI the process of payment will become faster and there will be lots in revenue

• Moreover the healthcare organization would need to pay the loss of claim denial or insurance Denial

Capturing Revenue:

• From the recent survey conducted by National Association of Healthcare Revenue Integrity, the most crucial step I'm revenue cycle management is collecting the charges.

• This is where the AI comes into picture which can perform documentation and coding without leaving room for mistake.

• With over 70,000 billable codes it is impossible for humans to manage to put the right charges.

• With the help of AI, detection of all the missing charges can be done before the claim has been filled.

Patient Financial Experience:

• In this high economy, even consumers need to be considered as they are the ones who will be paying for all the charges.

• With more competition, it is important for healthcare organizations to not lose their customers.

• Due to one human error in medical billing, it can cause a permanent loss to the specific practitioner or the organization.

• Here with the help of AI accurate Billings and charges will improve the financial experience of the patient and ensure the bonding of the patient with the organization for future.

Staying updated about changing policies:

• Many HealthCare providers face issues during billing and claim settlement due to the unannounced changes in the policies.

• It is also not possible for staff to keep track of all the changes happening in the policies which lead to delay in reimbursement, claim denials, more billing cost and in turn loss of income to the organization.

• This lack of communication can be avoided by AI. With daily email digests, the staff can be kept updated about the recent developments in the policies and hence developing a successful RCM.

Efficiency in claim verification:

• The troublesome claims may slip the human eyes but that won't be the case with an AI

• The machine will analyze all the past data and will be able to use it to understand such at-risk claims in the future.

• This will be done before sending the wrongful claims to the payer, hence keeping the integrity of the organization and securing a trust with the customer

Digitalization

• Digitization of data helps patients to store their data at one place.

• Moreover, with digitalization patients data can be made easily available to practitioners so that the patients get better treatment.