Modular Analytics Platform

Retrospective risk adjustment looks backward. It reviews charts for the plan year that has already happened and finds conditions that were documented but never coded, so the diagnosis can be submitted before the deadline closes.

Prospective risk adjustment looks forward. It predicts which members carry undocumented conditions before the visit, then routes that member to an assessment or puts the suspected condition in front of the clinician at the point of care so the diagnosis gets documented correctly the first time.

Most plans need both, and the two share the same underlying data. Running them on separate systems is where the fragmentation and the double vendor spend usually starts.

Five things, in rough order of how often they get skipped in an evaluation.

First, data agnosticism. The platform has to ingest claims, labs, EMR, assessment, pharmacy, and encounter data in any format from any source, structured and unstructured, or it will only see the part of the member that came through claims.

Second, one system across lines of business. Medicare Advantage, Managed Medicaid, and ACA on separate platforms means a dual-eligible member's history is split across tools and the suspecting logic sees half the picture.

Third, compliance built in rather than bolted on: MAO-004 reconciliation, RADV audit support, and ACA EDGE submission checks out of the box.

Fourth, adaptive models. Risk models change. V28 removed a large number of diagnosis codes from payment eligibility. A platform that needs a rebuild every time CMS revises the model will always be a cycle behind.

Fifth, an audit trail transparent enough to satisfy internal teams, CMS regulators, and provider partners at the same time.

MAP ingests structured and unstructured data from any source and turns it into real-time insight that supports both strategies from the same data foundation.

On the retrospective side it runs AI-powered suspecting and gap closure to identify undocumented HCCs, chart chase optimization that prioritizes retrieval lists by expected ROI and submission deadline, and an NLP-driven clinical insight engine that extracts risk conditions from unstructured chart data.

On the prospective side it runs member and provider stratification, Annual Wellness Visit effectiveness tracking, condition progression modeling that predicts chronic condition trajectory, and encounter integrity modeling that flags at-risk encounters before submission.

Claims, labs, EMR, assessments, pharmacy, and encounter data, in any format from any source, both structured and unstructured.

Data agnosticism is a practical requirement rather than a feature line. The conditions that drive RAF accuracy are disproportionately described in unstructured text, so a platform limited to structured feeds systematically under-detects exactly the members who matter most.

Yes, and it is included rather than sold as a module. MAP covers MAO-004 reconciliation, RADV audit support, and ACA EDGE server submission checks out of the box.

Reporting is built to be transparent and auditable for three different audiences at once: internal teams, CMS regulators, and provider partners.

Yes. MAP supports revenue forecasting, financial risk modeling, and scenario analysis, so risk adjustment performance connects to the plan's financial planning rather than sitting in an operational silo.

For finance and actuarial teams the practical use is in-year: model the RAF impact of an intervention before committing the outreach budget to it.