Quality Intelligence

Compliance risk builds continuously. Most organizations check for it periodically.

Audits sample. Internal reviews run quarterly. Submissions happen once a year. In the gaps between those cadences, a documentation pattern can drift for months without anyone holding the evidence that it has.

See What Vizier Finds in Your Data

Works from coding and documentation extracts you already produce. Surfaces the pattern, not a compliance opinion.

The problem

The audit finds a pattern that has been running for eight months.

Compliance functions are almost always under-resourced relative to what they are asked to cover, and they cope by sampling. A sample tells you whether the sampled records were compliant. It cannot tell you that one provider's coding distribution moved in March, or that documentation for a specific service line has been drifting since a template change.

Those are exactly the patterns that produce audit findings, repayment exposure and, occasionally, something considerably worse. They are also visible in data the organization already holds — coding distributions, documentation completeness, measure denominators — months before anyone samples the affected records.

The difficulty is that continuous monitoring across every provider, service line and measure is not achievable by hand. So it does not happen, and the organization runs on periodic assurance while the risk accumulates between checks.

  • Compliance monitoring is sample-based, and the sample size is set by available capacity
  • Coding distribution shifts are noticed at year-end or by an external auditor
  • Documentation drift after a template or workflow change goes undetected
  • Measure denominators move and nobody reconciles what that did to performance
  • Exposure is discussed qualitatively because quantifying it takes an analyst
  • The compliance team learns about an operational change after it has affected the record

Capabilities

What Vizier surfaces in compliance data

Vizier evaluates coding and documentation patterns continuously against your own history, and raises movement worth a compliance conversation — evidence for a human to judge, not a compliance determination.

Coding distribution shift

Where a provider, service line or site has moved away from its own historical pattern, and whether documented complexity moved with it.

Documentation drift

Completeness and consistency changing after a template, staffing or workflow change — usually the point where the cause is still identifiable.

Measure and denominator movement

Where regulatory measure populations have shifted, and what that has done to reported performance.

Outlier concentration

Where variation from the norm concentrates, so limited review capacity is spent on records that actually warrant it.

Exposure, quantified

The scale of a pattern in records and value where the evidence supports it, so remediation can be sized before it is escalated.

Change against a known date

Whether a shift coincides with something identifiable — a template change, a staffing change, a policy update — which is usually the difference between a finding and a fix.

What a finding looks like

Vizier is not making a compliance determination here, and it should not. It has found a pattern, tested it against documented complexity, isolated it to three providers, and tied it to a specific date.

What that pattern means — and whether it is a documentation problem, a training gap or something else — is a judgement for your compliance team. The point is that they get to make it in month five rather than after an audit.

Quality IntelligenceFinding

One provider group's coding distribution shifted after a template change, without documented complexity moving with it.

Three providers · One service line · Since a template change 5 months agoHigh confidence
Affected population
1,840 encounters
  • The distribution moved toward higher-level codes beginning the week of a documentation template change.
  • Documented problem complexity for the same encounters is statistically unchanged.
  • The shift is confined to three providers; the rest of the service line is stable.
  • The other service lines using the same template show no comparable shift.
Recommended investigation

Review the template change against the three providers' documentation workflow, and sample encounters from the period after the change.

Illustrative finding on modeled healthcare data. Your findings come from your own data.

The reporting gap

Why sampling finds this late

Sampling is a sound method for estimating a rate. It is a poor method for detecting a change, and detecting change is what compliance monitoring actually needs.

  • A sample sized to estimate a rate is rarely large enough to detect a shift in a subgroup.
  • Periodic review means a pattern can run for a full cycle before anyone looks.
  • Sampling is random by design, so it does not concentrate where risk concentrates.
  • Coding, documentation and measure data sit in separate reports and are rarely read together.
  • Nothing prompts. If no one schedules the review, the pattern continues.

What this replaces

This replaces sampling as the primary detection method

Sampling and audit remain necessary — for assurance, for regulatory expectations, and because some questions genuinely require reading the record. Nothing here suggests stopping.

What changes is what they are for. Today sampling is doing double duty as both assurance and detection, and it is poorly suited to the second job. Continuous pattern analysis handles detection, and your audit capacity gets pointed at records that already look worth reviewing.

That is a better use of a scarce, expensive and highly skilled resource.

  • Random sampling as the primary way of noticing that something changed
  • Analyst work cutting coding distributions by provider and service line on request
  • Year-end reconciliation of measure denominators against reported performance
  • External audit as the mechanism that first surfaces an internal pattern
  • Remediation scoped after the fact, because the exposure was never quantified early

Who this is for

One pattern. Three functions that need it early.

Population Health / Quality

Where has documentation or coding moved, and does it need review?

  • Care gaps and rising-risk cohorts prioritized by impact
  • Measure performance variation against peer benchmarks
  • Programs ranked by what the evidence says will actually move outcomes

CFO / Finance

What is our exposure, and how large is remediation if this is confirmed?

  • Revenue leakage surfaced with the exposure quantified
  • Reimbursement and payer performance movement, early
  • Financial impact ranked so the biggest number gets attention first

Analytics / Data

How do we monitor every provider and measure without sampling?

  • Consistent definitions so two leaders asking the same question get the same answer
  • Self-service investigation that does not generate another ticket queue
  • Governance, access control and audit logging that survive review

Getting your data in

Start from coding and documentation extracts.

Compliance analytics generally works from data already extracted for billing and quality submission, which means no new collection is required to begin.

  • A coding extract with provider, service line and encounter-level detail.
  • Quality measure extracts already produced for submission.
  • Documentation completeness data where your EHR exposes it.

01

Upload

CSV, Excel, or an export you already produce. Drop it in and Vizier reads it. This is where most organizations start, and it is enough to see real findings against your own numbers.

02

Scheduled

A recurring feed over secure transfer, on whatever cadence your team already runs. No one re-uploads anything by hand, and nothing about your source systems has to change.

03

Connected

Direct read-only connectivity to your EHR or source systems via FHIR R4, HL7 v2, or vendor APIs. Vizier reads; it never writes back.

Connect your EHR when you’re ready. See supported systems.

Security and governance

The page your CIO will ask for

Security questions get answered before a demo, not after procurement stalls.

HIPAA compliant

PHI handled under HIPAA Security Rule safeguards.

BAA included

Executed within one business day, on every plan.

Encrypted throughout

AES-256 at rest, TLS 1.3 in transit.

Read-only access

Vizier reads from source systems. It never writes back.

Role-based access control

Scoped permissions with SSO available.

Audit logging

Every query logged with account, timestamp and result size.

Tenant isolation

Your data is segregated from every other customer's.

SOC 2 Type II audit underway

Not yet certified. Report available under NDA on completion.

Full security and HIPAA detail · Request a BAA

FAQ

Questions buyers ask

Does Vizier decide whether something is non-compliant?

No, and this is a boundary we hold deliberately. Vizier surfaces patterns and the evidence behind them — a distribution moved, complexity did not, it is confined to three providers, it started on a specific date. Whether that constitutes a compliance problem is a determination requiring professional judgement, clinical context and often a review of the actual records. A product that claimed to make that call from coding data alone would be both wrong and dangerous.

Is this the same as a coding audit tool?

No. Coding audit tools review records against coding rules, generally at the record level, and that is genuinely useful work. Vizier operates at the pattern level — detecting that something changed, where, and when — and does not replace record-level review. The two are complementary in the accurate sense: one finds where to look, the other looks.

Will this create a discoverable record of problems we knew about?

A fair question, and one your counsel should weigh rather than us. What we would say is that the patterns Vizier surfaces already exist in your data whether or not anyone looks at them, and that most compliance leaders would rather find a five-month pattern in month five. How you document and act on findings is a matter for your compliance programme, and Vizier's audit logging supports whatever process you decide on.

Can it cover MIPS and quality measure compliance?

It surfaces measure performance and denominator movement in time to influence the result, which is the compliance-adjacent question most organizations care about. It is not a submission tool and does not replace your registry or submission vendor.

How much data do you need to detect a pattern?

Enough history to establish what normal looks like for that provider or service line — typically several months. Vizier will say when the evidence is too thin to support a conclusion rather than flagging noise, which matters here more than almost anywhere: a false positive in compliance costs review capacity and credibility.

Next step

See the pattern before the auditor does.

Bring a coding extract with a few months of history. Thirty minutes, and you will know whether anything has moved.

Start with the data you already have. Connect your EHR when you’re ready.