The Future of Medical Coding Isn't AI – It's Collaboration

One of my greatest concerns around AI isn’t that it’s going to one day go rogue and cause massive issues for some unfortunate provider. I believe the chances of that are slim to none. 

My deepest concern is potential missed opportunities. This is because AI promises so much to the healthcare revenue cycle – increase in quality and accuracy, efficient medical coding workflows, and, in the end, a profitable organization. And while that might be possible down the line, for the vast majority of healthcare providers, their path to revenue cycle success starts with something that’s much more accessible – collaboration. 

The key though, is collaboration from a multi-dimensional perspective. Revenue cycle leaders should be looking to build a culture of collaboration – one that pulls in clinical, billing, coding and external stakeholders like outsourcing companies and other vendors to support a holistic approach to revenue cycle management that helps your organization meet its goals. I’ve talked before about answering three critical questions to get started.

• How are we assessing costs and resources like staff time and processing costs?
• How are we handling PHI and what does our cybersecurity risk look like?
• What does our collaboration map look like so that we know what we’re aiming for?

But there is a fourth question, and that involves asking whether you’re missing out on low-hanging fruit because of the shiny promises of advancements in AI. It’s very possible that overly energetic perspectives on AI are obscuring issues like the fact that payers are dealing with archaic systems, an issue that’s been acknowledged as an impediment to implementation. But even internally, many providers' approaches to data is far from being ready for even simple AI solutions. 

Ultimately, healthcare revenue cycle leaders should take a step back to make sure they’re looking at the potential of AI realistically. I’m concerned that in the coming months and years, many are going to pay an opportunity cost that’s entirely too high simply because the hype around the technology has been so intense. For most, avoiding that cost will mean examining solutions that are a lot closer to home.