Why Arara
Placement decisions you can defend
The hard part of a placement is rarely finding facilities. It is knowing which of them can actually take this patient — and being able to say why you chose the one you did.
The evidence standard
Three answers, not two
Most systems store a capability as a checkbox. A checkbox has no way to say “we have no record”, so missing data silently becomes no — and a facility that could have taken the patient disappears from the list before anyone sees it.
The facilities a source does not cover skew towards exactly the specialists a hard placement needs. A two-state model is therefore most wrong about the cases where being wrong costs the most.
Confirmed
Counts as metNot certified
Can excludeNot verified
Never excludesAn illustration of the three states as the product renders them.
The standard
What we refuse to do
Three decisions that would each make the product look better in a demo and worse in a hospital.
Guess at identity
Federal and state records are linked on a published identifier. We measured name-and-address matching on this data at roughly one error in seven among its most confident answers — and a wrong link attaches another facility's ventilator beds to this one. Where the identifier is missing, a person decides.
Turn silence into a no
Facilities a source does not cover skew towards exactly the specialists a hard placement needs. Reading “no data” as “no program” would be most wrong about the facilities that matter most.
Hide what a filter removed
When a requirement excludes facilities, the count and the reason are shown. A filter whose effect is invisible is a filter that will quietly hide the right facility, and nobody will ever know it happened.
Afterwards
The reasoning outlives the decision
A placement gets questioned weeks later — by a family, a reviewer, a readmission committee. The useful answer is not “the system recommended it”.
- What the case required is recorded at intake, with each capability marked required or preferred.
- What each facility showed is kept with its source and observation date, not re-derived later from data that has since changed.
- What the filters removed, and why, stays visible rather than being silently dropped from the list.
- Who looked and when is audited, including every view of a patient identifier.
Next step
See it against your own state's data
We will tell you plainly where coverage is thin before you spend a meeting on it.