Case study · Behavioral health

From billing spreadsheets to a connected view of five treatment centers.

How a five-center behavioral health network went from a billing census retyped by hand every week to daily boards read straight from Kipu, and what is still being built.

It started as a billing problem: one person, more than a day a week, carrying attendance into a census by hand. Fixing it meant connecting the data underneath, and that changed what leadership could see every morning.

5Centers, four of them outpatient, across two states
4Separate Kipu instances, now read every morning by API
1Person who had held the whole census together
637Entries in the first real run, with zero conflicts

We were asked about the census. The census was not the only thing.

The weekly loop, beforeAs described by the client
Red is work done by hand. Management put the denial rate at about 15%, with no view of rework. That figure is management-reported, not measured by us.

Found along the way, and what each became

  • 1The attendance logs had no medical record number, only namesDoneOne added column
  • 2Nobody had looked at all the centers in one file on the same dayRunningA daily board for all five
  • 3Leadership's questions waited on the census being rebuilt by handRunningBoards every morning
  • 4The center websites had 51 location pages that nothing linked toAudit doneFixes not yet verified
  • 5Ad reporting stopped at clicks and form fills, not admissionsIn buildSource tracked to admission

What happened, in order.

  1. AuditWith the operations lead and every center's files
  2. Root causeAttendance logs had no record number
  3. Census engineDrafted and checked five ways
  4. Parallel weekRun beside the manual census, signed off
  5. EMR by APIEvery center read each morning, read-only
  6. Daily boardsCensus, executive and clinical views
Done and runningIn progress

One engine between the systems that never talked.

It reads, drafts and checks. It never writes back to the EMR, and a person approves every line. Where it runs and who can access the data is agreed in writing with the client.

Running todayPlanned or in build

What changed, for each person who uses it.

WhoBeforeNow
Operations leadRetyped every center's logs into the census, more than a day a week, then cleared the biller's flags.Reviews a drafted census and a short list of flags. Approves every line. Corrections become rules.
Center leadershipSaw their census against target only after the week's census was built by hand.Sees their center against its break-even census every morning.
Network leadershipQuestions became requests. Discrepancies were found in a two-day meeting.Daily boards for all five centers, plus an executive view with estimated value of care and a month-end projection.
Marketing and admissionsReporting stopped at clicks and form fills.In build
For the next center, every inquiry carries its source, so cost per admission can be counted by channel.

Where it started: the billing census.

The checks came from sitting with the operations lead and asking what actually goes wrong, then writing one for each answer. The finding that mattered most was not an error. It was a missing column.

BeforeSample data

DateMRNNameHoursLOC
3/8noneJ. Hale3.0IOP
3/8noneM. Ortiz2.0IOP
3/9noneJ. Hale3.0IOP
3/10noneA. Chen5.0PHP

AfterMRN added

DateMRNNameHoursLOC
3/84417J. Hale3.0IOP
3/82298M. Ortiz2.0IOP
3/94417J. Hale3.0IOP
3/108022A. Chen5.0PHP

Every identity mismatch traced back to that template. Not to carelessness. One added column closed that class of error at the source, at no cost. Names and numbers above are sample labels, not real clients.

Reads27day tabs of attendance, one facility-month
Drafts943client-days, in the biller's own format
Checks5billing checks on every line, matched by record number
Hands over~10 seca short list for a person, before claims are built

Scope: about ten seconds to read and check one facility-month once the exports are in place. It excludes pulling the exports and reviewing the flags. The hand figure it replaced was the operations lead's whole weekly census work across sites, so the two are not the same scope.

Proven in a parallel week

The operations lead ran a full week of the engine against the manual census and signed off with three notes. All three shipped the same day. Reviewed corrections since are logged as rules the engine checks, where they apply.

In the pilot it also recognised a week that had not been entered yet as work in progress, rather than flagging hundreds of errors. A tool that cries wolf on incomplete data gets switched off in week two.

The five checks, with the arithmetic, are in the billing census checks guide.

The line it does not cross

  • It does not bill, and it does not approve. A person approves every line.
  • Clinical judgment stays with the directors. A client repeatedly under threshold is an engagement conversation, not a billing correction.
  • When in doubt, hold rather than bill. A documented day can be billed late. A wrongly billed day becomes a clawback.

What leadership opens every morning.

Recreated with invented numbers. The real boards follow the same layout, are built from aggregates and carry no patient names.

Daily census

Against break-even, today

Sample
186Enrolled, network
101%Network vs break-even

Census against break-even, by site

Fairmont112%
Northgate104%
Lakeview100%
Cedar Park88%

Executive view

Month to date, aggregates only

Sample
$412KEstimated value of care
$596KProjected by month end
Jun Sep Proj.

Estimated value of care is not collected revenue. The board says so on its face.

Clinical outcomes

From discharge records

Sample
46%Completed treatment (n=212)
31 daysMedian length of stay

Completed treatment, by site

Fairmont52% n61
Northgate47% n58
Lakeview44% n50
Cedar Park38% n43

Every number, with where it comes from.

  • Verified637 entries in the first real run, zero conflictsFrom the engine's own run on real client data.
  • Verified943 client-days, 27 day tabs, about ten secondsOne facility-month, once exports are in place. Excludes pulling exports and reviewing flags.
  • VerifiedParallel week signed off, three notes, shipped the same dayRun by the operations lead against the manual census.
  • VerifiedFour Kipu instances read every morning by API, boards for five centersRead-only. Nothing is written back to the EMR.
  • Management-reportedAbout 15% denial rate, more than a day a week of retypingAs described by the client. Not measured by us.
  • Technical finding51 unlinked location pages, 7 near-duplicates, 11 open thank-you pagesFrom the audit of four center websites. Not measured traffic loss.
  • Not claimedDollars recovered, denials reduced, traffic or admissions gainedNeeds a full billing cycle with rework tracking, and real search and inquiry data.

Where each piece stands.

WorkstreamStatusLimitation
Billing census automationRunning at 3 of 4 outpatient sitesThe fourth site is moving onto the shared census template first.
Daily dashboardsRunning for five centers, from Kipu each morningEstimated value of care is not collected revenue.
Website, next centerIn buildNot launched. No traffic to report.
SEOAudit done for four sitesFixes not yet verified as implemented.
Admissions measurementBuilt tested on invented dataNo real admissions measured yet.
Financial impactNot claimedNeeds a full billing cycle after go-live, with rework tracked.

As of October 1, 2026.

What remains unresolved.

The fourth outpatient siteWhat would answer itThe site running on the shared census template.
Rework and denial trackingWhat would answer itA full billing cycle after go-live, with rework tracked. Any honest dollar figure depends on this.
Does linking the 51 location pages move search traffic?What would answer itSearch data before and after the fixes are verified as live.
Does the new center's website bring inquiries that become admissions?What would answer itLaunch, then each inquiry's source carried through to admission.
The admissions engine on real inquiriesWhat would answer itReal inquiry and admission records, instead of invented data.
Boards connected to collected revenueWhat would answer itCollected revenue matched to the census, not just estimated value of care.

When any of these has a real answer, this page will say so, with the date. Want to try the billing side yourself? The one-page checklist runs the five billing checks on one facility and one month. No email, no gate.

Two to twelve locations, and the numbers still joined by hand?

Start with a free 20-minute call. Nothing to prepare, no data to send.