Case studies
Six programs, six levels of care, one platform.
What changes when intake, clinical, billing and workforce stop being four systems — shown for a detox unit, a residential program, PHP, IOP, an outpatient group, and an office-based MAT clinic.
Composite scenarios. Modelled on the workflows this product was designed against, with our clinical and revenue-cycle partners. Named engagements will replace them as they publish.
to 5 minutes
Residential treatment
Forty beds, one records request, and three days nobody had
A commercial payer asked for six months of charts on four patients. The program had the care documented and still nearly lost the argument on paperwork.
Detox & withdrawal management
A detox unit that stopped losing bed-days to its own whiteboard
Sixteen beds, a paper census, and a per-diem claim rebuilt by hand every month. The gap between beds occupied and days billed turned out to be the whole problem.
Partial hospitalization
A PHP program where attendance and billing finally agreed
Group-heavy days, per-diem billing, and three separate records of who was actually in the room. The disagreements between them were costing more than the no-shows.
Intensive outpatient
An IOP program that stopped delivering care outside its authorizations
Sixty clients, two tracks, and an authorization spreadsheet reviewed on Mondays. The sessions delivered on Wednesday after a visit limit ran out were never coming back.
Outpatient practice
Nine clinicians, six vendors, and the invoice nobody had added up
An EHR, a scheduling tool, a billing service, a forms product, an LMS and a payroll system. Consolidation was worth more than any single feature on the list.
MAT / OTP
A MAT program that stopped running its medication list in two places
Controlled prescribing in one system, the clinical record in another, and a reconciliation problem that only showed up when someone asked for the whole picture.
How these are built
What is in each one, and what never will be.
Every study below follows the same structure: the situation as it stood, what changed, and three measures with a before and an after. Where a number is modelled rather than observed, it says so.
Always
What we show
- Level of care, program size and payer mix
- The specific workflow that was failing
- A baseline and the same measure after
- What did not improve, and why
Never
What we won't do
- Quotes we drafted for someone to approve
- Percentages without the counts underneath
- A best month presented as a typical one
- Any patient-level information
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