Revenue Intelligence
Know where revenue is deteriorating before someone builds the report.
Most revenue cycle reporting tells you what your denial rate was last month. It does not tell you that it moved, which payer moved it, what that is worth, or what to do on Monday — and getting those answers currently means an analyst, a queue, and a week.
Works with the remittance and AR files your billing team already produces. No EHR integration required to start.
The problem
You found out in the month-end pack. The trend started six weeks ago.
The reports exist. Denial rate by payer, AR ageing, charge capture variance, days to payment — your team can produce all of it, and probably does, on a monthly cycle into a deck nobody reads until the number is already bad.
By the time a denial trend is visible in a monthly summary, roughly two claim cycles have gone out under the same broken condition. The prior authorisation requirement changed, or a payer quietly re-scoped a policy, or one service line started coding differently after a staffing change. The aggregate rate moves a point and a half. Nobody can say which of those three things caused it without a week of analyst time.
So the question gets asked, it goes into a queue, and the answer arrives after the quarter closes. The revenue is not unrecoverable — but the window where recovering it was cheap has passed.
- Denial rate is discussed monthly and investigated quarterly
- Nobody can attribute a rate change to a specific payer, code or service line without pulling a custom report
- The AR ageing report shows a total, not which concentration inside it is actually at risk
- Underbilling is invisible, because nothing generates an alert for revenue you never claimed
- Your best analyst spends more time producing recurring reports than investigating anything
Capabilities
What Vizier surfaces in revenue cycle data
Vizier evaluates your revenue data continuously and raises the things that changed, ranked by what they are worth — rather than waiting to be asked.
Denial deterioration
Denial rate movement caught as it develops, attributed to the specific reason codes, payers and service lines driving it — not just reported as a higher aggregate.
Payer behaviour shifts
When one payer starts adjudicating differently — slower payment, new documentation demands, changed policy scope — it separates from the rest of your payer mix and gets flagged.
Underbilling and coding drift
Evaluation and management distributions that have moved away from your own historical pattern or peer norms, including the revenue sitting in encounters that were never billed at the level the documentation supports.
AR concentration and ageing risk
Not the total AR number, but where inside it the risk actually sits: which payer, which bucket, which cohort is ageing past the point where recovery rates fall off.
Charge capture gaps
Encounters and procedures where an expected charge is missing relative to how similar activity is normally captured in your own data.
Quantified exposure and priority
Each finding carries an estimate of what it is worth where the evidence supports one, so the biggest number gets attention first instead of the loudest meeting.
What a finding looks like
Nobody asked for this. It arrived because the number moved and the movement was worth someone's attention.
Every figure in it already existed somewhere in your billing data. The difference is that the change was noticed while it was still developing, the cause was narrowed to two payers and two service lines, the consequence was priced, and there is a specific thing to go and look at.
When you want more, you keep asking — in plain language, in the same place.
Denial rate crossed 12% this month, concentrated in five reason codes.
- Up from 8.6% across the prior six months, with the shift beginning in week 3.
- Five reason codes account for 71% of the increase, all prior-authorization related.
- Two payers drive the change; the remaining payer mix is unchanged.
- Orthopedics and cardiology are affected; other service lines are stable.
Review prior-authorization workflow changes in orthopedics and cardiology since the start of the quarter, beginning with the two payers involved.
The reporting gap
Why the reports you already have miss this
This is not a criticism of your reporting team. It is a structural limit of how reporting works.
A dashboard answers a question somebody thought to ask, on a refresh schedule somebody set, at a level of aggregation somebody chose in advance. All three of those decisions were made before the thing that is now going wrong started going wrong.
- Static reports show the level, not the change — a rate can drift for weeks inside a normal-looking tile.
- Aggregation hides concentration. A stable overall denial rate can contain one payer deteriorating badly and another improving.
- Investigation is manual. Finding the cause means drilling down by hand, or briefing an analyst and waiting.
- Domains are fragmented. A coding change shows up in one report, its denial consequence in another, and the AR impact in a third.
- Nothing prompts. If no one opens the report, or opens it and does not look at the right cut, the trend continues.
What this replaces
This replaces the investigation, not just the report
The reporting is not the expensive part. The expensive part is what happens after a number moves: someone notices, someone asks, someone briefs an analyst, the analyst builds a cut, the cut raises another question, and two weeks later there is an answer to a question that was urgent when it was asked.
That cycle runs every time. It runs for denial rate, then again for AR, then again for coding distribution, and it runs whether or not the finding turns out to be material — because the only way to know is to do the work.
Vizier removes the detection step and most of the first investigation. The finding arrives with the payer, the service line, the codes and the exposure already isolated. Your analysts get involved when something genuinely needs them, not to establish whether it does.
- Recurring monthly denial, AR and coding reports built by hand and reviewed after the fact
- The ad-hoc request queue — 'can you pull denials by payer for orthopedics since April'
- Analyst time spent establishing whether a number moved materially, before any real analysis begins
- External consulting engaged for revenue cycle root-cause work the internal team has no capacity for
- The spreadsheet somebody maintains privately because the official report does not answer their question
- Waiting for month-end to find out something started going wrong in week three
Who this is for
One set of findings. Three reasons to act on them.
CFO / Finance
How much revenue is leaking, and how much of it can we still recover this quarter?
- Revenue leakage surfaced with the exposure quantified
- Reimbursement and payer performance movement, early
- Financial impact ranked so the biggest number gets attention first
Revenue Cycle
What changed in denials, and which payer or workflow caused it?
- Denial deterioration attributed to specific codes, payers and service lines
- AR ageing and payer behaviour shifts detected as they emerge
- Root-cause investigation you can keep pulling on in plain language
Analytics / Data
How do we answer revenue questions without another custom report request?
- 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 with the billing data you already export.
Revenue cycle is usually the easiest place to start, because the files already exist and already leave your building on a schedule.
- A monthly 835 remittance file — enough on its own to surface denial concentration and payer behaviour.
- An AR ageing export from your practice management or billing system.
- A charge and coding extract, for underbilling and capture analysis.
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.
FAQ
Questions buyers ask
Do you need a direct EHR connection to do revenue cycle analytics?
No. Revenue cycle is the domain where the starting data is most likely to already exist as a file. A remittance file and an AR ageing export are enough to surface denial concentration, payer behaviour changes and ageing risk. Direct connectivity to your EHR or billing system makes it continuous rather than periodic, which is worth doing — but it is a later step, not a prerequisite.
How is this different from the denial reporting in our billing system?
Your billing system reports denials that happened. It is accurate and it is necessary. What it does not do is tell you that the pattern changed, isolate which payer and which codes caused the change, price the consequence, and tell you where to look. That gap is the entire reason a director ends up asking an analyst for a custom pull every time a number moves.
Will it work with our payer mix and specialty?
Findings come from your own data and your own history, so the baseline is your payer mix and your specialty rather than a generic benchmark. Peer benchmarking is available where a meaningful comparison group exists, but the primary comparison is always your organization against itself over time.
How much does it cost to recover the revenue it finds?
That depends entirely on what the finding is. Prior-authorization workflow problems are usually process fixes rather than spend. Underbilling generally needs documentation and coding attention. Vizier quantifies the exposure so you can judge whether the recovery is worth the effort — it does not claim every finding is free money.
Can our team ask follow-up questions, or is it just alerts?
You can keep asking. Every finding is a starting point for conversational investigation in plain language — narrowing to a payer, a date range, a location or a cohort — without writing a query or opening a ticket.
Who typically uses this day to day?
Revenue cycle directors and managers use it most often. CFOs and finance leads tend to look at the quantified exposure and prioritization. Analytics teams use it to absorb the recurring ad-hoc requests that were previously landing in their queue.
Related reading
See what Vizier finds in your revenue data.
Bring a remittance file or an AR export — nothing to build first. Thirty minutes is enough to know whether this is useful to you.
Start with the data you already have. Connect your EHR when you’re ready.