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Leveraging artificial intelligence to drive accurate risk adjustment and quality performance

Podcast - July 21, 2020

Coding & Documentation

Business Operations Technology

Data Analytics & Reporting

Andy Stonehouse MA

The advent of artificial intelligence (A.I.) has made the complex work of data analysis a more simplified and strategic tool in the world of clinical documentation. By leveraging technology to streamline what is often a time-intensive process, healthcare managers are discovering multiple benefits and improved quality in implementing clinical data in real time. In value-based environments, A.I. can be an even more valuable asset.

Matt W. Lambert, MD, chief medical officer, Curation Health, Washington, D.C., and Kyle Swarts, chief growth officer, Curation Health, have both experienced the advantages an A.I.-enriched clinical documentation improvement (CDI) program can have for patient care, provider workflow and risk adjustment.

On a recent episode of the MGMA Insights podcast, Lambert said providers struggle as their documentation needs and protocols vary between traditional fee-for-service patients and new value-based contracts. 

“Sometimes within a practice, you’ll have three or four different contracts that all have different quality incentives,” he said. “It makes it really challenging to figure out what is what.”
Swarts said the new digital analysis tools offered by CDI help to offer a new level of simplified, actionable interpretation for the litany of biometrics and information culled from every patient.
“I think that’s the secret sauce, and I think that’s the challenge that many healthcare organizations have faced today,” he said. “They have access to tons of data, but what do we do with it? But if you’re going to ask the providers to change their process or document a little bit differently, we need to make it really easy for them.”

By pairing A.I. with human intervention, even before the provider begins to work with a patient, Lambert said that time can be better spent interpreting that synthesized health data and providing optimized care. Learning to effectively integrate CDI at the point of care is also critical to the success and the overall performance of a new program, added Swarts. 

“In a risk-adjusted world, it doesn’t matter what you do pre-visit, and it doesn’t matter what you code,” he said. “If the doctor didn’t document it, it didn’t count. So, all of the pre and the post is important, but we have to make sure that we’re minimizing the disruption and not over-teching the providers at the point of care, so they can focus on clinically relevant opportunities and patient care outcomes.”

You can hear more from Lambert and Swarts about leveraging CDI technology to improve clinical outcomes at October’s virtual Medical Practice Excellence Conference, where they’ll present a session called, “Driving Accurate Risk Adjustment and Quality Performance with A.I.”

Additional resources:

If you like the show, please rate and review it wherever you get your podcasts. Subscribe on Apple PodcastsGoogle PlaySpotifyStitcher or countless other platforms to make sure you never miss an episode. If you have topics you'd like us to cover or experts you'd like us to interview, email us at, or reach out to MGMA Sr. Editor and MGMA Insights podcast host Daniel Williams on Twitter at @MGMADaniel

MGMA Insights is presented by Decklan McGee, Rob Ketcham and Daniel Williams.

Thanks to CareCredit for sponsoring this episode. 
  • Click here to learn how CareCredit is providing patients with payment flexibility and helping providers deliver a better patient financial experience.

About the Author

Andy Stonehouse MA
Freelance Writer and Educator Colorado

Andy Stonehouse, MA, is a Colorado-based freelance writer and educator. His professional credits include serving as editor of Employee Benefit News and a variety of financial and insurance publications, in addition to work in the recreation and transportation fields.


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