Prospective, Concurrent, and Retrospective Risk Adjustment: A 2026 Guide for MA Plans, ACOs, PACE Programs, and Providers

Risk adjustment is often discussed as a Medicare Advantage problem. In actuality, it affects every organization whose reimbursement, shared savings, or quality performance depends on accurately reflecting the complexity of their patient population.

Medicare Advantage risk adjustment, ACO risk adjustment, PACE programs, and value-based provider arrangements all operate under a framework where documented patient complexity directly shapes financial outcomes. The mechanisms differ across programs, but the core challenge is the same: incomplete or insufficiently specific documentation creates RAF score gaps that compound quietly across plan years, shared savings calculations, and quality ratings – often without triggering any operational alert.

This guide explains how the three primary risk adjustment coding approaches work, how prospective and retrospective HEDIS abstraction fits alongside them, and why the organizations performing best in 2026 are using all three in combination.

The scope of risk-adjusted reimbursement in U.S. healthcare has expanded significantly. As of January 2026, 14.3 million Medicare beneficiaries receive care coordinated by ACOs – a 4.4% increase from 2025 [1]. In Performance Year 2024, Shared Savings Program ACOs earned $4.1 billion in shared savings and reduced Medicare spending by $2.5 billion [1]. ACO risk adjustment directly affects how benchmark expenditures are calculated – meaning the accuracy of risk scores shapes whether an ACO generates shared savings or faces shared losses.

For PACE organizations, the stakes are just as high. PACE participants are typically dually eligible for Medicare and Medicaid and qualify for nursing home level of care – among the most medically complex populations in the U.S. healthcare system. The comprehensiveness of HCC risk adjustment coding for PACE participants directly determines capitation rates and the resources available to deliver the coordinated, interdisciplinary care the model depends on.

For value-based providers, risk adjustment accuracy is increasingly tied to quality bonuses, alternative payment model performance, and the clinical documentation infrastructure that supports every downstream revenue function.

Understanding how each approach functions – and where it belongs in a program design – is the foundation of effective risk adjustment services in USA.

Prospective risk adjustment uses existing claims and clinical data to identify members with likely undercaptured chronic conditions before the encounter takes place. It gives care teams and coders advance visibility into documentation gaps – which conditions should be addressed, which haven't been recaptured in the current plan year, and which members are approaching a care gap that carries both clinical and coding implications.

Example: A prospective review flags a diabetic member with a history of peripheral neuropathy who hasn't had the condition recaptured in the current year. The provider is alerted before the annual wellness visit, addresses the condition during the encounter, and documents it with the specificity V28 requires. The HCC is captured. The RAF score reflects the patient's actual complexity.

Concurrent risk adjustment works in real time during or immediately after the clinical encounter – validating that conditions are documented to the level of specificity required for HCC mapping, and flagging gaps for provider clarification before the claim is processed. It prevents the documentation shortfalls that prospective identification surfaced from becoming permanent coding gaps.

Retrospective risk adjustment works through completed charts after claims are processed, identifying diagnoses that were missed, unsupported, or undercoded. It is a necessary recovery mechanism – but its limitation is that it can only work with what the clinical record contains. If documentation lacks V28-required specificity, retrospective review has nothing to build on.

The most effective programs use all three in sequence: prospective analysis identifies the opportunity, concurrent workflows capture it in real time, and retrospective review closes what remains.

HEDIS abstraction sits alongside risk adjustment as the quality performance counterpart to financial accuracy. HEDIS measures – reported across nearly 50 domains of clinical quality and patient experience – directly influence Star Ratings for Medicare Advantage plans, quality scores for ACOs, and value-based performance metrics for providers. As of the 2025 NCQA Health Plan Ratings, approximately 235 million people are enrolled in health plans that report HEDIS data [2].

Prospective HEDIS abstraction identifies open care gaps across a patient population before the measurement year closes – diabetes screenings not yet completed, cardiovascular follow-ups outstanding, behavioral health measures not yet captured. Addressing these proactively improves quality performance and reduces the care gaps that both NCQA and CMS flag in Star Ratings calculations.

Example: A prospective HEDIS review for an MA plan identifies members with diabetes who are missing an eye exam for the current measurement year. Outreach is triggered. The exam is completed, documented, and captured in the measure – before the abstraction window closes.

Retrospective HEDIS abstraction reviews completed medical records to extract clinical data that wasn't captured during the measurement period – from EHRs, specialist notes, hospital records, and care management documentation. It closes gaps that weren't addressed proactively and ensures that care delivered is accurately reflected in quality reporting.

Used together, prospective and retrospective HEDIS abstraction produce higher, more defensible quality scores – and reduce the cycle-after-cycle care gap recurrence that drags Star Ratings down over time.

High-performing risk adjustment and HEDIS programs require two things that few organizations can build internally at scale: certified clinical expertise and technology that surfaces what chart review alone would miss.

3Gen's RiskGen-i uses AI to scan structured and unstructured clinical notes – flagging potentially missed or unsupported conditions for coder review, aligned to V28 requirements, and surfacing prospective RAF opportunities across a full member population before the documentation window closes. For organizations that prefer or require a coder-led model, RiskGen-Core delivers structured concurrent and retrospective review through certified HCC coding specialists – without the AI layer, but with the same clinical rigor and multi-level QA.

Both platforms support MA plans, ACOs, and PACE organizations. Both are designed to integrate into existing workflows without disrupting daily operations. And both are built around the V28 documentation requirements and RADV defensibility standards that define what effective risk adjustment looks like in 2026.

Whether your program is at the stage of building a prospective identification process, strengthening concurrent documentation workflows, or improving retrospective accuracy – the right starting point is understanding where your current structure is leaving revenue and quality performance on the table.

For a deeper look at how the RADV audit environment is shaping program strategy specifically for MA plans, see how CMS Is Ramping Up Audits of Medicare Advantage Plans.

3Gen Consulting partners with MA plans, ACOs, PACE organizations, and value-based providers across the U.S. to build structured, compliant, and technology-enabled risk adjustment and HEDIS programs – powered by RiskGen-i and RiskGen-Core. Schedule a Risk & HEDIS Program Review.