Under V28 and an expanded RADV audit environment, recovery-based workflows can quietly cost you accuracy, revenue, and audit defensibility. Check the signs that sound familiar to pressure-test where your program still depends on after-the-fact cleanup instead of prospective execution.
Gaps and suspected conditions are identified mainly from claims feeds that lag the encounter by weeks or months. By the time a code shows up as missing, the visit where you could have captured it is long closed.
Strategy is built on a stale and incomplete view. Teams spend the back half of the year reconstructing risk instead of capturing it correctly the first time.
They deploy cutting-edge AI to build the risk picture before and during the visit using multiple sources, including the EHR, HIE data, labs, imaging, and notes. The patient’s full burden of illness is visible when the clinician can still act on it, not rediscovered after the fact.
Retrospective chart review and year-end chart chases remain the main way you capture and defend risk, with teams of coders combing through records long after the encounter.
The process is expensive, hard to scale, and structurally late. Corrections arrive after the clinical decision has already been made, adding administrative burden without improving the visit or strengthening the original documentation.
They move the work upstream. Pre-visit review surfaces suspected conditions with supporting evidence before the encounter, reducing chart-chase volume and year-end cleanup.
You have a prospective initiative, but it runs in a separate portal, spreadsheet, or pre-visit packet that sits next to the EHR rather than inside it.
Adoption stays low and insights go unseen. The program exists on paper, but it rarely changes what happens in the exam room. Clinicians experience it as one more interruption to be ignored.
They embed risk insights directly into the EHR at the point of care, with simple documentation workflows and minimal context-switching. The right action becomes the easiest action.
Acceptance rates are low and suggestions are often dismissed. Physicians cannot see where a recommendation came from, so payer-supplied prompts are treated as noise rather than useful clinical signal.
A complete risk picture is only valuable if clinicians trust and act on it. Low engagement means suspected conditions remain unaddressed, documentation gaps persist, and the investment fails to translate into captured, defensible risk.
They use clinical AI solutions which support every suggestion with clear evidence, answering “where is this coming from?” in the moment. Evidence-linked insights earn trust, improve acceptance, and support stronger documentation.
Diagnosis review and coding remain post-encounter activities. The clinician walks in without the full picture, and coders take care of reconciliation after the fact.
Rather than getting it right the first time, organizations scramble to correct it later. They miss the opportunity to capture accurate, contemporaneous documentation at the point of care, increasing cleanup work and weakening audit readiness.
They put the complete, evidence-backed picture in front of the clinician before the encounter, so documentation can be captured in real time, in the workflow, and with the supporting evidence attached.
V28 has made accurate, specific, well-supported documentation more important, while CMS’s expanded RADV audit activity has raised the stakes for every diagnosis submitted for payment. In this environment, late capture is not just inefficient. It creates operational drag, revenue risk, and documentation exposure.
The strongest organizations are moving from recovery to execution. They assemble a complete risk picture before the visit, deliver it inside the provider workflow, and support every recommendation with traceable clinical evidence. That is how risk adjustment becomes more accurate, more defensible, and less burdensome for clinicians.
See where your program stands. Leading risk-bearing organizations are already making the shift from retrospective recovery to prospective execution, with AI doing the heavy lifting. If you’re curious what that could look like for your program, book a strategy call and we’ll map your current workflow against a prospective model to pinpoint where risk, revenue, and audit exposure are leaking today.
Rated #1 Best in KLAS for clinician digital workflows
Rated #1 Best in KLAS for clinician digital workflows
Rated #1 Best in KLAS for clinician digital workflows
Rated #1 Best in KLAS for clinician digital workflows