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HCC and Risk Adjustment Analytics

Accurate Risk Capture,
in Both Directions

Risk adjustment analytics that surface genuinely supported conditions for clinician evaluation, assess whether documentation actually supports what was submitted, and identify codes that should be removed as readily as codes that should be added.
Most risk adjustment programmes are measured on score lift, which quietly makes them programmes for finding more codes. CaliberFocus builds them the other way round. We start from the population and the evidence, present suspected conditions to clinicians with the data behind them rather than as a prompt, assess whether existing documentation would survive a review, and report unsupported submissions for correction. The score that results is the one the record supports.
If your risk adjustment programme cannot produce a list of codes that should be deleted, it is not measuring accuracy. It is measuring revenue.
The Challenge

The incentive points one way. The enforcement points the other.

Risk adjustment rewards documenting the conditions a patient genuinely has. The difficulty is that every commercial incentive pushes one way only, while enforcement attention has moved toward unsupported diagnoses and the analytics that generated them.
A programme measured on score improvement will produce score improvement. Whether that improvement is defensible is a separate question, and it is the one that matters when charts are reviewed. 

Recapture is an operational problem

Most of the apparent gap is patients with no qualifying encounter, or an encounter where the condition was never addressed.

A problem list is not evidence

Problem lists carry resolved conditions, duplicates, historical diagnoses and entries copied forward without current assessment.

A claim code is not the same as support

A submitted diagnosis without documentation evidencing evaluation or management is a liability rather than revenue.

Suspecting tools that prompt rather than inform

Bare code prompts invite rubber stamping or wholesale rejection. Neither produces accuracy.

No view of what the plan actually accepted

Submitted, accepted and acknowledged are three different populations.

Provider reporting that reads as policing

Clinician-level coding performance framed as a compliance scorecard destroys the engagement the programme depends on.
Under audit, a small error rate on a large population is not a small number.
Chart-review samples can be extrapolated. That arithmetic turns a modest documentation weakness into material financial exposure. We build for the sample, not for the score.
Our Approach

Start by auditing what you already submitted

Almost every engagement in this space begins by looking for what is missing. We begin by examining what is already there. That establishes credibility with clinicians and surfaces existing exposure before new opportunities are pursued.

Step 1

Establish population and attribution

Define which patients are in scope, under which arrangement, attributed to which providers, for which period.

Step 2

Build the condition picture

Assemble claims, problem lists, encounters, medications, labs, imaging and specialist correspondence.

Step 3

Audit what was already submitted

Test whether existing diagnoses are supported by current-period documentation.

Step 4

Identify recapture by cause

No qualifying encounter, encounter without assessment, or assessed and documented but not coded.

Step 5

Surface suspected conditions with evidence

Present the underlying clinical information and no code pre-selected.

Step 6

Deliver into the pre-visit workflow

Put the information into the workflow the care team already uses before the encounter.

Step 7

Support documentation quality

Help clinicians document what they assessed to the specificity the record supports.

Step 8

Reconcile the chain

Compare documented, coded, submitted, accepted and payer-acknowledged states.

Step 9

Retain evidence and monitor accuracy

Keep the logic, evidence and lineage required to explain the programme years later.
Capabilities

Evidence first, code last

The technical work here is not condition detection. The defensible work is assembling the evidence, assessing whether documentation supports it, and delivering it in a form a clinician will engage with.

Build the Picture

Population and Attribution Management

Patients in scope, arrangements, providers and periods reconciled against the payer view.

Multi-Source Condition History

Claims, problem lists, encounters, medications, labs, imaging, specialist correspondence and external data.

Patient Identity as a Prerequisite

Unresolved matches enter stewardship rather than becoming confirmed clinical history.

Submission Chain Reconciliation

Documented, coded, submitted, accepted and payer-acknowledged compared as distinct states.

Find the Opportunity, Both Directions

Recapture Identification

Persistent conditions classified by the reason they have not been addressed.

Evidence-Based Suspecting

Objective clinical data attached to every candidate condition.

Documentation Sufficiency Assessment

Whether existing documentation evidences evaluation, assessment and management.

Deletion and Correction Identification

Unsupported diagnoses identified and returned for correction as a standard output.

Deliver and Defend

Pre-Visit Workflow Delivery

Opportunities delivered into the pre-visit and encounter workflow.

Provider-Level Insight

Clinician-level patterns presented as education and adjusted for patient complexity.

Audit Evidence and Model Versioning

Supporting documentation, model version, logic version and lineage retained together.
What CaliberFocus does, and does not do?
We are not paid on score movement and we will not accept an engagement structured that way. We do not pre-populate diagnoses, we do not present codes without evidence, and we do not conclude that a patient has a condition. Analytics can surface a clinical question. Only the clinician can answer it, and only the record can support it.  
The Opportunity

Three opportunity types, and only one is about new conditions

Programmes tend to be sold on suspecting, which is the most interesting category and usually the smallest. The larger and safer opportunity is generally in conditions the organization already knows about, and in submissions it has already made.

Recapture

A persistent condition documented previously and not addressed this period. Lowest risk, highest volume.

Specificity

A condition documented less specifically than the record supports. Accuracy improvement with no new clinical assertion required.

Suspecting

A condition suggested by objective data and never documented. Genuine clinical value and highest scrutiny.

Correction and deletion

A submitted diagnosis the documentation does not support. Reduces exposure and is treated as an opportunity, not an embarrassment
Evidence tiers, and the one we never surface

Strong evidence

Objective results, condition-specific medication or specialist diagnosis, surfaced with source values and dates visible.

Moderate evidence

Indirect indicators, historical claims or related procedures, surfaced as a question with reasoning shown and clearly labelled as inference.

Weak evidence — Not surfaced

Statistical or population-level likelihood with no patient-specific clinical evidence. We do not put probability in front of a physician as if it were a finding.

What Sufficient Documentation Looks Like
A code is not support. Documentation sufficient to survive review generally shows that the condition was actually evaluated and managed in the period: an assessment, a status, and a plan or rationale for continuing current management.
Signal, question, action, and what we never do
A suspected condition is a question, not a diagnosis. Each signal is handled the same way: surface the evidence, frame the clinical question, route it for review, and stop.
Signal The Clinical Question Action What We Never Do
Prior-period condition not documented this period Is the condition still present and clinically relevant? Present history for provider review Carry the diagnosis forward automatically
Problem-list entry with limited current documentation Is it still active, and was it assessed or managed? Route for clinical review Treat problem-list presence as current-period support
Medication specific to a condition Does the record support evaluating that condition? Surface medication and context Infer the diagnosis from the prescription
Laboratory or diagnostic result Has the clinical significance been evaluated and documented? Bring result and context into review Convert an abnormal result directly into a diagnosis
Specialist documentation not reflected elsewhere Is it current, supported and relevant here? Make the documentation available Assume it propagates to every encounter
Documentation supporting greater specificity Does the record support a more precise representation? Route for documentation or coding review Code beyond what the record supports
Coded condition with weak or conflicting support Can the diagnosis be substantiated? Prioritize for validation and correction Protect a code because removing it reduces capture
Every opportunity gets a disposition

Confirmed and documented

Already supported

Needs clarification

Not supported

Resolved or historical
Duplicate

Deferred

Stratification and Insight

Stratify for care first. The coding follows.

Risk stratification built purely for coding produces a list of patients worth a documentation visit. Risk stratification built for care produces a list of patients who need attention, most of whom also carry undocumented complexity.

Care management

Patients whose complexity or trajectory warrants proactive management.

Visit planning

Patients with unaddressed chronic conditions and no scheduled encounter.

Documentation completeness

Patients where the record does not reflect known complexity, addressed during the encounter.
Provider-Level Insight Without Destroying Provider Engagement
Clinician-level coding reporting should be presented as education, adjusted for patient complexity, and designed with clinical leadership.

Adjust for the panel

Unadjusted comparison across physicians with different patient complexity is noise with a name attached.

Route through clinical leadership

Physician documentation feedback comes through clinical leadership, not finance.

Never link compensation to capture

Compensating clinicians on documented risk score creates the wrong incentive.
Data

Submitted, Accepted and Acknowledged Are Three Different Numbers

Organizations routinely manage risk adjustment against what they believe they submitted. The payer is working from what it accepted and acknowledged. The gap between those positions is invisible without deliberate reconciliation.

Documented but not coded

The note evidences evaluation and management, but the coder or logic cannot act on it.

Coded but not submitted

Present on the encounter, absent from the file actually transmitted.

Submitted but not accepted

Rejected for format, eligibility or timing and never resubmitted.

Accepted but not acknowledged

The payer accepted the record but the condition does not appear in its view of the member.
Built on the Governed Platform, Not Beside It
This work consumes the same certified data products as the rest of the organization. If the provider dashboard, coder worklist and finance report disagree about a patient’s risk profile, that is one unresolved data problem.
Trust

Design the programme for the sample, not for the score

The governing question for every design decision is what happens when a reviewer pulls twenty charts. A programme comfortable with that scenario is built differently from one optimized for score.

Programme integrity

Documentation standards

Audit readiness

Access and oversight

The uncomfortable test.
Ask whoever runs your risk adjustment programme today for the list of codes they have recommended deleting in the last twelve months. If there is no list, the programme has only ever been pointed in one direction.
Outcomes

Accuracy measures, deliberately not score

Score is an output. Reporting a programme on it creates exactly the incentive the programme should not have. These are the measures we report.
Category What We Measure Why It Matters
Documentation Sufficiency Share of submitted conditions with documentation that survives internal review, on a rolling sample The measure that determines exposure
Two-Directional Activity Conditions added and codes identified for deletion, reported together every period A programme with no deletions is not looking
Recapture Completeness Persistent conditions addressed in the period, and reason for each that was not The largest and lowest-risk part of the opportunity
Suspecting Quality Clinician confirmation rate and rejection rate on surfaced conditions, by evidence tier Very high confirmation may suggest rubber stamping; rejection is a healthy signal
Audit Position Internal review pass rate, time to assemble an audit response, extrapolation exposure estimate The scenario the whole programme should be designed for
Expect the first year to be uncomfortable.
The first year may produce a lower net position than a capture-focused programme because unsupported submissions are coming off at the same time as supported conditions go on. Initial review may also identify exposure that needs correction. Those realities should be agreed with compliance and finance before the work starts.

Improve risk capture with confidence

We will take a defined patient sample, assess whether the documentation supports what was submitted, identify the persistent conditions that were missed, and give you both lists with the evidence attached. That exercise takes weeks, it tells you your real position rather than your reported one, and it is the only honest basis for deciding what the programme should look like.

Start with the clinical workflow, not the ambient AI platform.

Bring us a specialty or clinical setting where clinicians are spending too much time creating notes. We will assess where ambient documentation fits, what must remain clinician controlled, how it should integrate with your EHR, and how to measure whether it is actually reducing burden.

One conversation with people who have run these deployments, and a written readiness view you can use with or without us.

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