Accuracy, Trust, and the Future of Coding at Scale
Medical coding is no longer a downstream function with a single destination. Coded data now flows across reimbursement, analytics, quality reporting, and research. As that reuse accelerates, accuracy stops being a local concern. It becomes an industry-wide dependency.
When coding outputs are reused across systems and stakeholders, inconsistency compounds risk. Errors don’t just affect a single claim or chart; they ripple downstream. That reality is forcing organizations to rethink what “good” looks like in modern coding operations, and how to sustain trust as scale and complexity increase.
That’s why recent recognition of Datavant as the Best in KLAS winner for outsourced coding matters; not as an award headline, but as a signal. It reflects what customers are actually prioritizing right now: coding operations that deliver consistent, reliable outputs they can confidently use downstream, not just work that gets done faster.
Trust at scale is the new bar
“As coded data gets reused across reimbursement, analytics, and reporting, accuracy stops being a local issue. At scale, consistency is what creates trust and it has to be intentionally designed into the operation” says Datavant’s SVP of Coding Solutions, Brian Donahue.
Historically, coding accuracy was often evaluated internally: did it meet guidelines, did it pass audit, did it support reimbursement? Those questions still matter, but they’re no longer sufficient. As coded data becomes more interconnected, consistency and reliability across reuse cases are what define trust.
That shift raises the bar for coding partners. Accuracy can’t be episodic. It has to be repeatable, transparent, and defensible, especially as volumes grow and complexity increases. The organizations that are succeeding are the ones grounding their operations in quality first, not treating it as a downstream check.
Technology is changing the workflow, but not replacing judgment
Technology is undeniably reshaping how coding work gets done. Its impact goes beyond efficiency alone. When applied thoughtfully, it supports consistency in guideline interpretation, improves visibility into quality and performance, and helps create more resilient operations as scale increases.
AI-enabled tools are increasingly embedded in coding workflows to standardize processes, surface risk, and support more informed decision-making, capabilities that matter more as coded data is reused across reimbursement, analytics, and reporting.
“Technology only works when it’s embedded into real workflows and aligned with how coders actually operate day to day” says Datavant Product Manager, Kelly Canter.
But technology alone doesn’t create trust.
What we see working in practice is augmentation, not automation-first thinking. Technology strengthens the system, while experienced coders provide the judgment that ensures accuracy, compliance, and nuance aren’t lost. Automation can accelerate work; augmentation reinforces reliability, especially in complex, real-world scenarios where context matters.
The most effective coding models don’t ask whether to use technology. They focus on how to align tools with people and processes to support consistent outcomes at scale.
As scale increases, the human coder matters more, not less
There’s a persistent misconception that as technology scales, human expertise becomes less important. In practice, the opposite is true.
As volumes increase and workflows become more complex, experienced medical coders play a critical role in maintaining quality. They become stewards of accuracy, ensuring guidelines are applied consistently, edge cases are handled appropriately, and automation works as intended rather than creating blind spots.
We see this clearly in real-world transformations, where combining technology-enabled workflows with experienced, engaged coding teams leads to measurable improvements in accuracy, turnaround time, and confidence in downstream use. Technology enables scale, but coders shape outcomes.
See how this approach works in practice. Read how Southwest General Health Center partnered with Datavant to improve accuracy, consistency, and confidence in downstream use.
What the recognition really reflects
Best in KLAS recognition is driven by customer feedback, which makes it a useful signal; not because it validates a single solution, but because it reflects where the market is heading. Customers are rewarding partners who combine operational discipline, transparency, and human expertise with technology to deliver results they can trust at scale.
For Datavant, that recognition reinforces a clear point of view about the future of coding. Success isn’t defined by volume or tools alone. It’s defined by the ability to scale accurately using technology to strengthen consistency and visibility, while keeping experienced coders accountable for quality and judgement.
As coding continues to evolve, the organizations that succeed will be the ones that treat trust as an operating principle, not a byproduct. At scale, accuracy isn’t optional and neither is the human expertise required to sustain it.
Interested in how trust is built into coding operations at scale? Learn more about Datavant’s approach to outsourced coding.
