Clinical Analytics Platform

Clinical questions do not arrive on a reporting schedule.

A clinical analytics platform for the people accountable for care quality — where the question gets asked and answered by the same person, and where variation surfaces before it becomes an outcome.

See What Vizier Finds in Your Data

Built for clinical leadership rather than for analysts. Starts from clinical extracts you already produce.

The problem

The people who notice something is wrong are the furthest from the data.

A clinical director develops a suspicion. Something about a cohort, a unit, a pathway — the kind of pattern that comes from seeing patients rather than reports. Acting on it requires evidence, evidence requires data, and getting data requires a request that joins a queue.

By the time the answer arrives, weeks have passed, the question has often moved on, and the answer frequently prompts a second question that requires another request. Most clinical leaders learn to ration what they ask, which means the majority of clinically-informed suspicions never get tested at all.

This is a poor use of the most valuable pattern-recognition capability in the organization. Clinical judgement about what is worth investigating is exactly what analytics cannot supply, and it is being throttled by a process bottleneck.

  • Clinical leaders have stopped asking, because the answer arrives after it is useful
  • Outcome variation between providers and units is suspected and unquantified
  • Quality measure performance is known at submission and not before
  • Every clinical question is translated by an analyst who lacks the clinical context
  • Registry and measure data is extracted for submission and never interrogated
  • The answer to a question generates two more, each requiring a new request

Capabilities

What a clinical analytics platform should surface

Vizier evaluates clinical performance continuously and raises what changed — in clinical language, to the people who can judge whether it matters.

Outcome variation

Differences in outcome between providers, units and pathways, adjusted for case mix so the comparison reflects care rather than acuity.

Cohort deterioration

A patient group whose measures are drifting, surfaced while the movement is small and before the aggregate reflects it.

Measure performance, early

Where quality measures are heading during the performance period, with the cohorts driving the movement identified.

Pathway adherence

Where practice has moved away from the intended pathway, and whether outcomes moved with it.

Investigation in clinical language

Follow-up questions asked in the terms clinicians actually use — a 30-day window, a measure exclusion, a cohort definition — and answered directly.

Evidence for the conversation

Findings that carry their evidence, because a variation conversation with a colleague needs data behind it rather than an assertion.

What a finding looks like

Raw outcome comparison between units is the fastest way to start an argument, because the unit performing worse can almost always point to sicker patients — and is often right.

Ruling out case mix first is what makes this a clinical conversation rather than a defensive one. The variation is real, it is confined to one procedure group, and there is a specific pathway step to look at.

Quality IntelligenceFinding

Outcome variation between two units survives case-mix adjustment.

Post-surgical · Two comparable units · Rolling 12 monthsHigh confidence
Adjustment result
Comparable acuity
  • The complication rate differs by 4.2 percentage points between two units.
  • Case mix index and acuity distribution are comparable across both.
  • The difference concentrates in one procedure group rather than across all activity.
  • Both units follow the same documented pathway; adherence recording differs at one step.
Recommended investigation

Compare practice at the pathway step where adherence recording differs, for the affected procedure group only.

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

The reporting gap

Why general analytics tools struggle with clinical questions

Clinical questions carry meaning that has to be understood before they can be answered, and that meaning is not in the column names.

  • A readmission has a defined window; a tool that does not know that will answer a different question.
  • Quality measures carry exclusions, and a denominator built without them is wrong rather than approximate.
  • Comparing outcomes without case-mix adjustment produces confidently misleading conclusions.
  • Clinical concepts span coding systems, and a generic tool treats each as an unrelated column.
  • The translation step — clinician to analyst to query and back — loses clinical context in both directions.

What this replaces

This replaces the clinical report request

The report request is where clinical curiosity goes to die. It is not anyone's fault: the analyst is busy, the request has to be specified precisely by someone who does not yet know what they will find, and the turnaround is long enough that the question loses urgency.

The consequence is invisible and expensive. Nobody counts the investigations that were not requested because they were not worth the wait, and those unasked questions include the ones a clinical leader's judgement was best placed to identify.

What changes is who can investigate. The bottleneck was never clinical judgement — it was access.

  • The clinical report request queue, for routine investigation
  • Analyst time spent translating clinical questions into queries and results back into clinical terms
  • Registry and measure data extracted for submission and never interrogated
  • Variation conversations conducted on impression because the evidence took too long
  • The investigations nobody requested because the wait made them not worth it

Who this is for

Clinical questions, answered by the people asking them.

Population Health / Quality

Where does outcome variation survive case-mix adjustment?

  • 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

Analytics / Data

How do we serve clinical questions without absorbing every one of them?

  • 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

COO / Operations

Where does clinical variation connect to operational performance?

  • Throughput and patient flow constraints identified by location and service line
  • Performance variability between sites made visible rather than averaged away
  • Operational deterioration flagged while it is still a trend, not a crisis

Getting your data in

Start from clinical extracts you already produce.

Most of what clinical analysis needs is already being extracted for quality submission or registry reporting.

  • Quality measure or registry extracts already produced for submission.
  • A clinical encounter extract with diagnosis, procedure and outcome coding.
  • Read-only EHR connectivity when your governance process is ready for 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

How is this different from your main platform page?

Same platform, different entry point. /platform/ is written for the CIO, CFO or analytics leader evaluating a healthcare analytics platform across the organization. This page is for clinical leadership — the people accountable for care quality who want to know whether they can investigate their own questions. The underlying product is one thing; the buying reason is genuinely different.

Does it do case-mix adjustment?

Yes, and for clinical comparison it is not optional. Comparing outcomes between units or providers without adjusting for acuity produces conclusions that are confidently wrong and, worse, damage the credibility of every subsequent comparison. Where coding depth is not sufficient to adjust reliably, Vizier says so rather than presenting an adjustment you should not defend in a clinical governance meeting.

Is this a clinical decision support tool?

No, and the distinction matters. Vizier does not make recommendations about individual patient care, does not sit in clinical workflow, and is not a regulated clinical decision support system. It analyses performance across populations for clinical leadership and quality improvement. If you need point-of-care decision support, that is a different product category with different regulatory obligations.

Can clinicians use it without training?

That is the design intent — investigation happens in clinical language rather than through a query interface. In practice most organizations do a short orientation, less because the tool is difficult and more because it is worth agreeing which questions matter and how findings will be handled in governance.

How does this handle measure exclusions?

Measure definitions including exclusions and denominators are maintained centrally and updated as specifications change, which is precisely the maintenance burden that makes rebuilding measure logic in a general BI tool expensive. If a denominator looks wrong to your team, that is worth raising — measure logic is the thing most worth checking during evaluation, and any vendor should welcome the scrutiny.

Next step

See what Vizier finds in your clinical data.

Bring a measure or registry extract you already produce. Thirty minutes, and bring the question you have been meaning to ask.

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