Building an HCC Risk Adjustment Coding Program for a Home Health Agency
Improved
HCC Capture
Updated to V28
Coding Protocol
Better aligned to complexity
RAF Accuracy
Prospective
Reviews
How Medeoan built a CMS-HCC V28 risk adjustment coding program for a Medicare Advantage-heavy home health agency using gap analysis and prospective reviews.
The Challenge
This illustrative engagement centers on a Medicare-certified home health agency that serves a high proportion of Medicare Advantage (MA) beneficiaries. The agency held several MA contracts, including shared-savings and risk-based arrangements where accurate documentation of member acuity directly influences plan reimbursement and quality benchmarks. While the clinical teams delivered strong care, the coding function had grown up around fee-for-service home health billing (PDGM), where the payment model is driven by the primary eligibility diagnosis rather than the full chronic-condition burden that risk adjustment depends on. As a result, coders reliably captured the principal diagnosis but often did not report every eligible chronic condition as a supported secondary diagnosis. Under the CMS-HCC V28 model, several conditions mapped to different hierarchical condition categories, some no longer carried the same risk weight, and others required more specific ICD-10-CM codes to map to an HCC at all. The agency's coding protocols had not yet been updated for V28, so the Risk Adjustment Factor (RAF) scores flowing to MA plans did not fully reflect the true complexity of the patient population.
Our Solution
Medeoan began with an HCC gap analysis, comparing submitted claims data against the underlying clinical documentation for a representative sample of the agency's MA patients. This surfaced two distinct issues: conditions that were clearly documented in the record but never coded as reportable secondary diagnoses, and conditions coded at a level of specificity too low to map to an HCC under V28. Framing the findings as documentation-and-coding gaps (rather than a billing problem) kept the work anchored to what the clinical record actually supported. From that baseline, our team built a V28-specific coding protocol tailored to the agency's actual chronic-condition mix — the diabetes, cardiovascular, respiratory, and renal conditions that recurred across its panel. The protocol codified how each common condition should be documented and coded to the correct ICD-10-CM specificity, how the V28 category remaps changed prior habits, and where MEAT-style documentation support was required before a diagnosis could be reported. Finally, we introduced prospective HCC reviews: a coding review step performed before claims and encounter data were submitted to the MA plans, rather than a retrospective audit after the fact. This let the agency correct specificity gaps and confirm documentation support at the point of submission, so the RAF scores communicated to payers stayed aligned with the complexity clinicians were already managing. Note that traditional fee-for-service home health is reimbursed under PDGM and is not risk-adjusted by HCCs; the HCC/RAF work here applies specifically to the agency's Medicare Advantage and risk-arrangement population.