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Building trust and confidence in autonomous coding with Solventum

Case study

How a Midwest health system automated outpatient coding with Solventum while maintaining accuracy

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About the health system Background and challenge Solution Implementation Change management Results and impact What's next
On this page...
About the health system
Background and challenge
Solution
Implementation
Change management
Results and impact
What's next

The health system

  • Leading non-profit health system in the upper Midwest of the United States with locations in South Dakota, Minnesota, Iowa, Nebraska and North Dakota.
  • As of 2025, it served over 43,000 inpatient stays, 1.2 million outpatient visits and 2 million clinic visits with over 300 care locations across a 5-state area.
300+ locations
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5 states
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Background and challenge

The health system faced increasing patient volumes and a need to optimize its coding operations without expanding its full-time employee (FTE) base. Coders were spending time on repetitive tasks rather than applying their expertise, especially for simpler cases like ancillary services. At the same time, the health system observed that payer reimbursement rates were not keeping pace with inflation and rising operational expenses, adding financial pressure to improve efficiency. The organization sought a solution that could streamline coding, reduce manual effort and maintain accuracy.

Technologies in scope:

Service lines in scope:

  • Radiology
  • Lab/pathology
  • Same day surgery
  • Diagnostic cardiology

Facilities involved:

  • Four prospective payment system (PPS) sites (out of 21 facilities)
  • Plan to extend the scope to critical access hospitals (CAH)

The solution: Autonomous coding with Solventum

The health system partnered with Solventum to implement Solventum Autonomous Coding in the outpatient facility space. Solventum Autonomous Coding employs leading class, expert-guided AI technology to read, process, code, and complete up-to-date, qualified visits or professional encounters, ready for the billing process without human intervention. The health system’s goal was to leverage technology to bridge the gap between growing volumes and limited staffing resources. The health system also aimed to improve coder workflow and satisfaction, ensuring that staff could focus on higher-value tasks. Importantly, the organization wanted to avoid outsourcing coding, preserving internal expertise and maintaining control over quality.

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Implementation process

Technology transition

Experienced a seamless switch from the legacy natural language processing (NLP) to the Solventum™ Catalyst™ AI engine, achieving improved autosuggestion quality with no support tickets post-launch.

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Phased rollout

Avoided a big bang approach by conducting weekly testing and review meetings. Built trust by starting small and expanding as confidence grew with consistently accurate coding on claims.

Account categories: Solventum Autonomous Coding is flexible and allows for automation at the account level (e.g. diagnostic ultrasound, CT/PET, etc.). The health system embraced this and chose to go live with screening mammograms to start, followed by CTs and MRIs, employing a small group of super users for testing. Other account categories followed.

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Prospective audit strategy

Started with 100% audit of qualified charts, then increased automation up to 80% for diagnostic radiology including MRIs, CT/PET and screening mammography. For ultrasounds, the health system set quality assurance (QA) at 75% initially, then increased automation up to 80%. It also incorporated the “AI coder” into quarterly reviews for auditing like any other coder. The result of the audit was compliant coding and 80% full automation (no human review) of qualified visits.

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A circle chart showing 80 percent shaded and 80 percent automation of qualified visits inside
A circle chart showing 20% shaded and 20 percent QA inside

Change management

Super user engagement was crucial to the success of implementing autonomous coding at the health system. The organization developed a comprehensive plan to have super users test different implementation milestones and then promote the system internally to their peers. They also engaged with some early users to address their apprehensions and encouraged them to reconsider their perspectives, resulting in a constructive outcome. To build trust in the system, the health system used super users to test every piece of the IT setup, from the new AI engine to the order interface and charge interface; they were present every step of the way. Super users also performed part-time validation testing which helped reassure staff. The overall implementation ultimately needed very minimal training in the rollout. Tip sheets and a one-hour training session were sufficient for the staff to know what to expect and how to interact with the new Solventum Autonomous Coding technology.

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Results and impact

95% accuracy

For all account categories that are going through autonomous coding. 

80–90% qualified

For automation in diagnostic radiology. 

Post-publication update:

70% of volume

Since the publication of this case study, the health system has activated diagnostic cardiology with 70% of volume qualifying for autonomous coding. 

Workflow integration

Coders experienced minimal disruption; Solventum Autonomous Coding integrated smoothly into existing EHR workflows.
 

Operational efficiencies

The health system has been able to upskill coders for more complex cases. For example, in radiology, they reported having 5 to 7 coders who are being trained to code for emergency room and other areas where they see an increased volume. In addition, they haven’t needed to replace coders who are retiring or leaving.
 

Automation rates

Since its autonomous coding go-live, the health system has experienced increasing automation rates in diagnostic radiology, with visits qualifying for autonomous coding in the 80-90% range, depending on account category, and 70-80% of those going out to the billing system without any coder review across all four hospitals actively coding autonomously.

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Account
categories		% of visits
qualified		% of visits
automated
Bone density studies87%79%
MRI94%82%
Diagnostic ultrasound94%77%
CT/PET57%70%
CTA/MRA87%79%
Screening mammography85%81%

Customer report month:
December 2025

Service line:
Radiology

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Accuracy

The health system has seen 95% accuracy for all account categories that are going through autonomous coding. Some account categories have seen as high as 98% accuracy — an outstanding result.
 

Outcomes

The organization has had no increase in claim edits or denials and their discharged not final billed and discharged not final coded (DNFB/DNFC) metrics have improved as well. They anticipate benefits in more complex radiology services to follow.
 

Training

Minimal learning curve; staff trained in one-hour sessions.

“We needed a system that looked at the whole radiology report, not just at the order — this applies to any service that requires interpretation.”

Director of coding services

Non-profit health system

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Ready to build trust in Solventum autonomous coding?

See what Solventum Health Information Systems can do for your organization. Connect with our experts to learn how autonomous coding can help you scale operations, automate a higher percentage of visits, and improve efficiency and accuracy—without adding staff or increasing risk.

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