Healthcare

The neglected end of healthcare RCM

Why should billing and coding get all the AI love?

After all, the payments portion (say that three times fast) of RCM is the engine that drives all of healthcare. And the patient parts of the process (ok, we’re done with tongue twisters now) have been the most neglected segment.

But we see you, patient payments people! (Ok, we lied.)

It’s time to put AI to work to relieve you of the frustrating and repetitive parts of your job too.

Why we started putting AI to work in coding and billing first

Early parts of the RCM process were ripe for intervention from artificial intelligence. AI excels at repetitive tasks and the kind of precision and pattern-finding people often find frustrating or difficult.

So we started with automated coding assistance. Medical coders no longer had to manually review complex medical records and assign the correct billing codes, a time-consuming and error-prone process. 

Instead, AI-powered coding systems can now analyze patient data, identify relevant diagnosis and procedure codes, and suggest appropriate codes based on the provided information. This not only reduces the risk of coding errors but also accelerates the billing process significantly.

WIth its skill at recognizing patterns, AI is highly proficient at uncovering anomalies that often signify fraudulent claims or errors in healthcare data. Putting this capability to work prevents substantial financial losses for healthcare providers.

But what about the rest of the revenue cycle?

So with billing and coding teams relieved of their rote tasks, where’s the love for payments?

As part of AI’s impact on automating billing, we’ve been able to put it to work on both the provider and insurer side of the payment equation. 

From automating prior authorization to claims processing , AI solutions have eased the communications between providers and insurers.

And for patients, automated eligibility verification has taken a lot of the surprise out of the process, and increasing adoptions of self-serve account portals have met their needs as consumers.

But we’re still not there yet.

Healthcare is a people business

The patient payments process in particular (ok, we’re not even trying now!) offers challenges exacerbated by complex insurance policies and the rise of HDHPs. 

In a time where patient responsibility for healthcare costs is on the rise, effective patient financial engagement is crucial for successful RCM and medical debt collections.

And medical payments and collections by definition are human processes, requiring manual follow-up and empathetic and clear communication with patients.

When patients are reluctant to pay - or are confused by - their medical bills, RCM and medical debt collection teams must connect with them to explain insurance and bills and discuss payment responsibilities and arrangements.

AI is great for what it’s great at, but sometimes you just need to talk to a person, you know?

How to bring AI to patient payments

There’s the puzzle: bringing AI to patient payments without losing the human connection.

It starts by targeting common inefficient payments workflows. 

By shifting the way your teams work, you can improve patient financial representative productivity and job satisfaction, accelerate traditional manual processes, and see boosts to payments and revenue.

We can start by targeting inefficient workflows with AI solutions, like:

  1. Automating conversation summaries
  2. Improving QA and compliance audits
  3. Supporting agent training and reducing ramp time

And now things get really interesting

Because the right AI for your patient financial RCM team is trained on financial conversations like the ones you have every day, it’s got an expertise that you can use.

In the same way we’ve put AI to work examining historical data to forecast future billing trends and predict which claims may be rejected or denied, you can use it to mine every patient interaction for insights that can transform your business.

Because patients tell you about their financial lives when you communicate with them - via phone, email, text, or chat - you can use those details to manage individual accounts and strategize across them.

Here’s just a sampling of what you could do with AI on your patient payments team:

  • Optimize communications by learning which messages, channels, and times are the best to contact patients
  • Customize payment plans based on common life events
  • Find patterns in delinquent accounts so you can spot the warning signs and act before things go south
  • Accurately identify and capture complaints so you can develop self-service tools to address patient concerns
  • Capture patient sentiment to evaluate their intentions for everything from payment to switching providers

The list is endless. So buck up, patient payments teams. Your time to join the RCM revolution is now.