Sharon Kelley, Mayo Clinic Revenue Cycle and Autonomous Coding: The AI Shift That Changed Medical Coding

For hospitals, artificial intelligence becomes consequential when it moves beyond demonstrations and starts touching claims, coding accuracy, staff workload and cash flow. Mayo Clinic reached that point during Sharon Kelley’s period leading its revenue-cycle organization, when automation became part of the institution’s strategy for handling complex administrative work at enterprise scale.

One project stands out. Kelley’s revenue-cycle team worked with CodaMetrix on automation of radiology medical coding across Mayo Clinic operations in Minnesota, Arizona and Florida. The work received recognition at Mayo Clinic’s inaugural VIBE Automation Summit, placing an often invisible back-office function—medical coding—inside the broader conversation about practical healthcare AI. (LinkedIn)

There is also an important 2026 update. Kelley is no longer Mayo Clinic’s revenue-cycle chair. She left Mayo Clinic effective January 3, 2026, and Todd Manion subsequently became chair. That distinction matters because older conference pages and profiles still identify Kelley by her former Mayo title. (beckershospitalreview.com)

BLUF: Sharon Kelley led Mayo Clinic Revenue Cycle during a period when the organization expanded its use of AI and automation, including CodaMetrix-supported radiology coding across Minnesota, Arizona and Florida. The initiative was publicly recognized by Mayo Clinic, although Mayo-specific financial savings, automation percentages and denial-rate improvements have not been publicly verified. (LinkedIn)

Sharon Kelley’s Mayo Clinic Role Was Bigger Than Medical Billing

Sharon Kelley, CPA, MBA, brought a finance-centered perspective to revenue-cycle management. HFMA materials state that she joined Mayo Clinic in 2019 as chief financial officer for Mayo Clinic Health System before moving into the enterprise revenue-cycle chair position. Her earlier experience included financial leadership roles at Gateway Health Plan and MetroHealth, as well as consulting work with Booz Allen Hamilton. (HFMA)

Duquesne University described Kelley in 2025 as chair of revenue cycle for Mayo Clinic’s worldwide operations, while Becker’s Healthcare repeatedly listed her as Mayo Clinic Revenue Cycle chair during healthcare-finance and AI discussions. (Duquesne University)

From Centralized Revenue Cycle to Autonomous Coding

Autonomous medical coding is different from simply giving a coder an AI suggestion.

In an assisted workflow, software may recommend an ICD-10, CPT or other billing code, but a human coder still reviews the encounter and makes the final decision. A more autonomous system can interpret eligible clinical documentation, generate codes and allow sufficiently qualified encounters to move through the workflow with substantially less routine manual intervention.

Human expertise does not disappear. Complex, uncertain or exception cases can still require coder review, compliance oversight, auditing and clinical-documentation work.

For Mayo Clinic, the publicly documented project centered on radiology coding.

What has been publicly verified

Item	Verified information
Revenue-cycle leader	Sharon Kelley led Mayo Clinic Revenue Cycle during the project period
Technology collaborator	CodaMetrix
Initial publicly described use	Automation of radiology medical coding
Mayo locations identified	Minnesota, Arizona and Florida
Internal recognition	Automation Project Showcase recognition at Mayo Clinic’s inaugural VIBE Automation Summit
Broader objective	Use automation to reduce repetitive work while supporting staff and patient experience
Mayo-specific automation rate	Not publicly verified in the sources reviewed
Mayo-specific coding-cost savings	Not publicly verified
Mayo-specific denial reduction	Not publicly verified
Mayo-specific revenue increase	Not publicly verified

CodaMetrix publicly described Kelley’s revenue-cycle team as working with its technology to automate radiology medical coding at Mayo locations in Minnesota, Arizona and Florida. (LinkedIn)

That is a more defensible description than claiming Mayo achieved a specific percentage of savings or claims improvement.

CodaMetrix has separately reported broad performance figures for organizations using its platform, including an average successful automation rate above 96%, a 60% reduction in coding costs, a 70% reduction in claims denials and faster time to cash. Those are vendor-reported, network-level figures and should not be represented as Sharon Kelley or Mayo Clinic results unless Mayo publishes institution-specific evidence confirming them. (CodaMetrix)

Why Radiology Became an Important Test of Healthcare AI

Radiology produces immense quantities of structured and semi-structured clinical information. Every examination can generate documentation that must ultimately connect with appropriate billing and reimbursement codes.

Manual coding has advantages because trained professionals understand exceptions, documentation nuances and compliance rules. It also creates labor requirements that rise with clinical volume.

Research involving Mayo Clinic investigators has described manual billing-code assignment as potentially expensive, time-consuming and vulnerable to human error while examining machine-learning approaches for automated coding. The researchers also stressed the need for models capable of dealing with the large and changing ICD-10 hierarchy. (Mayo Clinic)

That makes radiology a logical area for carefully governed automation: volumes can be high, documentation follows recognizable patterns, and repetitive cases may provide opportunities for straight-through processing.

But “autonomous” should never be interpreted as “uncontrolled.”

Healthcare coding affects reimbursement, compliance, clinical records and potentially quality reporting. An autonomous system therefore needs monitoring for coding accuracy, model drift, unusual documentation, payer-rule changes and cases falling outside validated conditions.

Mayo Clinic researchers discussing AI deployment more broadly have likewise emphasized operational, technical, clinical and regulatory challenges rather than treating AI implementation as a simple software installation. (Mayo Clinic)

The VIBE Recognition Showed What Mayo Wanted Automation to Do

In December 2024, Mayo Clinic hosted its inaugural VIBE Automation Summit, bringing together employees, leaders and external specialists around AI, automation and robotics.

Mayo Clinic described the objective in human terms rather than purely financial ones. Anjali Bhagra, M.D., Mayo Clinic’s medical director of Automation and Equity, Inclusion and Diversity, said:

“Patients and staff are at the heart of our automation efforts.”

Mayo said the summit highlighted technologies intended to enhance employees’ work and create more time for patient-focused activity. (LinkedIn)

CodaMetrix subsequently identified Sharon Kelley and her Revenue Cycle team among the Automation Project Showcase winners and specifically connected the recognition to radiology medical-coding automation across Mayo sites in Minnesota, Arizona and Florida. (LinkedIn)

The significance was not merely that an AI tool could assign a code. It was that coding automation had become an enterprise operational project visible alongside other Mayo automation initiatives.

Kelley’s Revenue-Cycle Timeline at Mayo

2019 — Finance leadership

HFMA presentation material states that Kelley joined Mayo Clinic in 2019 as chief financial officer for Mayo Clinic Health System. (HFMA)

2022 — Enterprise revenue-cycle leadership

Public professional histories place her move into the revenue-cycle chair position around 2022. Her remit subsequently covered Mayo Clinic’s broad revenue-cycle operation. (Becker’s Hospital Review)

2023 — A distributed revenue-cycle workforce

Kelley publicly described an approximately 2,200-person centralized revenue-cycle organization with a large remote workforce distributed across dozens of states. (Commerce Healthcare)

2024 — AI and automation become increasingly visible

Kelley appeared in healthcare-finance discussions focused on intelligent technology, including AI-assisted coding, documentation, claims submission and denial management. (Becker’s Hospital Review)

In December, Mayo’s inaugural VIBE Automation Summit recognized automation projects, with CodaMetrix identifying Kelley’s revenue-cycle team for its radiology coding work. (LinkedIn)

2025 — Kelley remained the public face of Mayo Revenue Cycle

Duquesne University introduced Kelley as chair of Mayo Clinic Revenue Cycle when she returned as a commencement speaker in 2025. (Duquesne University)

January 2026 — Leadership changed

Kelley left Mayo Clinic effective January 3, 2026. Mayo subsequently appointed Todd Manion chair of revenue cycle. (beckershospitalreview.com)

Todd Manion’s Appointment Suggests the AI Strategy Did Not End With Kelley

The leadership transition is particularly relevant to anyone searching for Sharon Kelley Mayo Clinic chair revenue cycle autonomous coding today.

Becker’s reported that Kelley was succeeded by Todd Manion, whose previous Mayo responsibilities included coding, revenue integrity, outpatient clinical documentation improvement and provider education.

More importantly, Manion had already been involved in Mayo’s AI strategy. Becker’s said he led the integration of AI into mid-revenue-cycle operations, including intelligent coding tools and predictive analytics aimed at compliance, coding accuracy and billing timeliness. (beckershospitalreview.com)

That makes the 2026 transition notable.

Kelley’s departure represented a leadership change, but the available evidence points toward continuity rather than abandonment of coding automation. Mayo placed a leader with direct AI-and-coding experience into the revenue-cycle chair position.

For health systems watching Mayo, that may be the more important signal: autonomous coding was not simply attached to one executive or one pilot.

What the Public Record Still Does Not Tell Us

The available evidence establishes that the radiology coding automation project existed and was important enough to receive internal recognition. It does not establish every performance claim that could easily be attached to it.

There are several questions for which authoritative Mayo-specific public numbers remain unavailable in the sources reviewed:

• What percentage of Mayo radiology encounters ultimately became fully autonomous?
• How many charts moved directly to billing without coder intervention?
• What was Mayo’s before-and-after coding cost?
• How much did coder productivity change?
• Did denials decline specifically because of autonomous coding?
• How much faster did claims reach billing?
• What percentage of AI-generated codes required correction?
• How did accuracy compare with Mayo’s human-coder baseline?

Those distinctions matter for E-E-A-T.

CodaMetrix’s aggregate customer results can demonstrate the potential of its technology, but they cannot automatically be substituted for Mayo Clinic’s own results. (CodaMetrix)

A credible account should therefore describe Mayo’s documented deployment without turning vendor-wide statistics into institution-specific facts.

FAQs

Was Sharon Kelley the chair of Mayo Clinic Revenue Cycle?

Sharon Kelley was chair of Mayo Clinic Revenue Cycle and previously served as chief financial officer for Mayo Clinic Health System. She is no longer the chair. Kelley left Mayo Clinic effective January 3, 2026, and Todd Manion subsequently succeeded her as revenue-cycle chair. (HFMA)

What was Sharon Kelley’s connection to autonomous coding?

Sharon Kelley led Mayo Clinic’s revenue-cycle organization while her team participated in an autonomous medical-coding initiative with CodaMetrix. Public documentation specifically identifies radiology coding automation across Mayo operations in Minnesota, Arizona and Florida. The project received recognition during Mayo Clinic’s inaugural VIBE Automation Summit. (LinkedIn)

What is autonomous medical coding?

Autonomous medical coding is the use of AI-driven systems to analyze clinical documentation and generate billing codes with reduced routine human intervention. In appropriate straight-through workflows, qualified encounters may proceed without a coder manually coding every chart, while exceptions and uncertain cases remain candidates for human review, quality auditing and compliance oversight.

Did Mayo Clinic replace its medical coders with AI?

There is no reliable public evidence that Mayo Clinic eliminated its medical-coding workforce because of autonomous coding. Mayo continues to describe medical coders as important to billing accuracy, integrity and quality, and its careers material identifies coding roles across clinical outpatient, hospital outpatient and inpatient services. (jobs.mayoclinic.org)

How successful was Mayo Clinic’s autonomous coding project?

The project was successful enough to receive automation recognition at Mayo Clinic’s VIBE summit, but Mayo-specific percentages for automation, cost reduction, denial reduction or revenue improvement were not identified in the authoritative public material reviewed. CodaMetrix publishes broader customer-network performance figures, but those figures should not be presented as Mayo-specific outcomes. (LinkedIn)

Who leads Mayo Clinic Revenue Cycle after Sharon Kelley?

Todd Manion succeeded Sharon Kelley as Mayo Clinic’s revenue-cycle chair in January 2026. Before the appointment, Manion led areas including coding, revenue integrity and clinical documentation improvement and was credited with integrating intelligent coding tools and predictive analytics into Mayo’s mid-revenue-cycle operations. (beckershospitalreview.com)

The Bigger Signal From the Sharon Kelley Era

Sharon Kelley’s connection to autonomous coding is important because it illustrates how healthcare AI can move from technical experimentation into a core financial operation.

During her Mayo Clinic revenue-cycle tenure, the challenge was not simply generating codes faster. Mayo was managing a large centralized revenue-cycle workforce, complex clinical operations and multiple geographic sites. Automation had to work within that environment while preserving coding quality, compliance and human oversight.

The documented radiology initiative with CodaMetrix showed one practical route forward: automate repeatable work, scale successful workflows across locations and allow skilled professionals to concentrate on exceptions, auditing, documentation integrity and higher-value decisions.

Kelley’s departure in January 2026 closes one chapter, but Mayo Clinic’s appointment of Todd Manion—a leader already connected with intelligent coding and predictive analytics—suggests the underlying transformation remains active. (beckershospitalreview.com)

For healthcare executives, that continuity may be the most consequential lesson. Autonomous coding is moving from an isolated AI experiment toward an operating model in which machines process suitable routine work while people increasingly govern quality, exceptions, compliance and clinical complexity.

Editorial Disclaimer

This article distinguishes verified Mayo Clinic information from technology-vendor claims and avoids attributing CodaMetrix-wide performance statistics directly to Mayo Clinic. Public professional titles can become outdated; Sharon Kelley should be described as former Chair of Mayo Clinic Revenue Cycle for current 2026 publication. No unpublished financial, employment, coding-accuracy or personal information has been estimated or inferred.

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