athenahealth, a national network-enabled software and service leader for healthcare practices and systems, revealed a set of new practice and revenue cycle management (RCM) AI-driven innovations intended to decrease manual administrative work and speed reimbursement. These innovations, part of the company’s growing athenaOne platform, are designed to enable ambulatory practices to get paid quickly, fully, and with less effort.
“Curing complexity throughout the revenue cycle has always been central to athenahealth. Accelerating AI progress, combined with our decades-long history, are allowing us to make another groundbreaking leap in lowering customers’ workload and enhancing revenue cycle performance for our practices,” said Paul Brient, athenahealth’s chief product and operations officer. “With our AI-born, cloud-based co-sourcing model, we will deliver revenue cycle outcomes unimaginable a year ago – near 99% clean claim rates, time to bill in low single digit days, and confidence that our practices capture every dollar that they should. We can do all of this and wick away half the work that our practices have traditionally done.”
athenahealth’s new AI capabilities are based on its single-instance, SaaS foundation, taking advantage of the company’s deep network and direct relationships with national and regional payers. Through the processing of billions of claims, payer policy changes, and denial resubmissions, the system automatically applies AI-based insights throughout the revenue cycle, automating time-consuming tasks, producing cleaner claims, and speeding reimbursement.
Principal athenaOne features augmented by these AI capabilities include:
Automated Insurance Selection – Now available, this feature applies AI to recognize accurate coverage from images of insurance cards, reducing patient insurance-related denials by 13% and insurance-related claim holds by 35%.
“athenahealth’s automated insurance functionality simplifies my ability to easily locate the appropriate insurance package, enroll patients sooner and prevent surprise downstream denials that harm my practice and the patient experience,” explained Michelle Gilreath, Owner/PMHNP-BC, Mindwell.
Patient Liability Estimation – During pre-Alpha development, this AI functionality estimates a commercially insured patient’s out-of-pocket responsibility, enhancing transparency and allowing practices to receive more patient payments.
Waitlist Scheduling – Coming next into Alpha testing, this feature automatically discovers available appointment times from cancelled appointments and alerts patients by text, enhancing access to care and patient satisfaction while maximizing provider schedules.
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Express Coding with Real-time Clinical Documentation Improvement – In development and Alpha testing, AI reveals suggested procedure codes and offers real-time documentation and diagnosis suggestions to clinicians, affirming precise and thorough billing.
AI Payer Portal Agents and Voice AI – Already in Alpha testing, AI agents monitor payer websites for policy changes, automate prior authorizations, and automate tracking of claim status, making practices more efficient and faster with improved results.
Automated Denial Advice – Now available, this capability uses AI to create real-time claim correction recommendations for coding-related denials, boosting recovery by 26.4% over manual corrections alone.
With 19 years of Best in KLAS recognition and decades of practice and revenue cycle management expertise, athenahealth delivers consistently measurable results: a 5.7% median initial denial rate (compared to industry average >10%), 98.4% clean claim rate, and a 78% patient pay yield.
Since inception, athenahealth has been dedicated to using innovation to push administrative work out of the business of medicine, so that practices can concentrate on their patients and get compensated adequately for the care they’re delivering to their communities,” said Bob Segert, chairman and chief executive officer at athenahealth. “We have a cloud-based, AI-native architecture that enables the speedy deployment of AI capabilities, and this makes it possible for us to innovate faster, transforming work in RCM for our practices and setting them up for long-term success.”
