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Oracle Health launches 5 AI revenue cycle tools to prevent denials
Oracle Health will roll out five embedded AI capabilities in its revenue cycle solutions that target prior authorizations, coding and charge capture to prevent claim denials.
Oracle Health has announced new revenue cycle management capabilities that use AI toward the front-end of the revenue cycle to prevent denials in the first place.
Revealed at the Oracle Health and Life Sciences Summit yesterday, the health IT giant said five AI capabilities for RCM will be embedded within its revenue cycle solutions in the coming months. The capabilities include AI-driven prior authorizations, clinical document quality integrity, charge capture and integrity, medical coding for professional fees and appeals management.
The company said the new capabilities aim to mitigate reimbursement problems early in the patient and payment journey by targeting common areas for errors, such as missing information, authorization issues and inaccurate charges.
"AI gives us an opportunity to prevent revenue cycle problems before they lead to denials and delayed payments," Seema Verma, executive vice president and general manager of Oracle Health and Life Sciences, said in a press release.
With the new capabilities, Oracle Health hopes to feature AI across each part of the revenue cycle -- front, middle and back -- to connect clinical and financial workflows, from registration through payment, according to Verma.
"This can help healthcare organizations reduce administrative work and revenue leakage, get paid faster, and strengthen their financial stability so they can stay focused on delivering excellent patient care," she stated.
RCM remains a fragmented, often manual process despite major technological advancements in the administrative side of healthcare. AI is largely contributing to greater efficiencies in certain areas, but RCM vendors are increasingly looking to connect capabilities to deliver a more seamless experience across the revenue cycle.
This can help address some of the leading causes for claim denials, they argue. Missing or inaccurate data, patient registration and eligibility errors, and prior authorization failures are among the top reasons for providers' claim denials, followed by coding mistakes.
Typically, providers receive denials and must rework the claim to obtain reimbursement. But getting information, precertification and clinical documentation right from the start can prevent delayed or rejected reimbursements.
Oracle also revealed product plans to further connect reimbursement workflows with enterprise financial operations, including financial reconciliation, revenue accounting, treasury management and analytics through solutions such as Oracle Fusion Cloud Applications.
The company said this product direction should link reimbursement activities, financial operations and enterprise analytics to enable better operational and financial decisions.
Oracle's health AI vision
But Oracle's aim isn't automation for automation's sake, Verma reiterated during her keynote speech at the Summit.
"The goal is not to automate every step of a broken process," she said. "It is to redesign our processes across the entire health ecosystem by connecting clinical, financial, research, clinical trials, claims data with analytics and AI, so we can automate routine transactions and reserve human attention for decisions that require judgment."
"This isn't faster bureaucracy; it's less bureaucracy," she continued.
That's the North Star behind Oracle's mission of building AI specifically for healthcare. The company debuted last year its "AI-first" EHR solution, built from the ground up on Oracle Cloud Infrastructure, rather than on top of Cerner's foundation. Oracle bought Epic's main rival, Cerner, for $28.4 billion in June 2022.
"This is where I believe that Oracle has a unique role to play," Verma said. "We're building the capabilities for an AI-driven healthcare future, including excellent cloud infrastructure."
The Oracle database, she continued, is an "AI-ready data foundation" that can aggregate the data needed for health AI at scale. This will power AI capabilities for financial and revenue cycle operations, as well as for clinical and payer solutions.
Oracle's approach builds an EHR within an AI-ready environment rather than layering AI on top of the EHR, which other vendors have done.
"If we simply layer AI onto fragmented systems, disconnected data, manual processes and technology architectures built for another era, we risk amplifying the discord rather than creating harmony," Verma stated.
Epic currently holds about 42% of the U.S. acute care hospital market, making its tools heavily integrated and widely deployed across a stable client base. But this pivot for Oracle could counter recent reductions in Oracle Health market share, giving the company a seemingly clean slate after the Cerner purchase to prove itself with embedded AI capabilities.
The overhaul has raised concerns about operational disruption versus incremental progress with a layered AI approach. But Oracle reassured customers that this transformation still means they can modernize their revenue cycles at their own pace, leveraging the native AI embedded across its solutions when needed.
Jacqueline LaPointe is an Executive Editor at Xtelligent Healthcare Media, covering revenue cycle management, healthcare payers, health policy, and health IT since 2016.