For skilled nursingClinical & financial intelligence, built HIPAA-ready

Every referral, chart and claim, read against your building’s own rules.

Orenda reads the documents your facility already produces and returns a structured, cited answer — a fit score, a PDPM review, a survey-ready chart, a drafted note — with every finding quoted to the page it came from. Your team verifies in seconds. Your team decides.

AWS Bedrock under a signed BAA Audit row on every access Nothing reaches the chart without a clinician

Built around the standards and systems your building already runs on

PointClickCareFHIR R4 · US CoreMDS 3.0PDPMF-tags & CMS-2567AWS Bedrock
The problem

The hard part was never the decision. It was the reading.

The pattern repeats all month. In every case the work that eats the hours is not judgment — it is finding the one sentence on page thirty-four that settles the matter.

Friday, 4:40 pm

A sixty-page referral arrives by fax.

Someone has to read it against the acuity limits, the payer mix, the isolation beds and the diagnoses this building cannot take — before the discharge planner calls the next facility on the list.

Day 5 of the window

The ARD is closing on the MDS.

Items to verify, a comorbidity documented in a consult note nobody coded, Section GG scores to support. Reimbursement rides on what gets found before the window shuts.

Monday, 8:05 am

A surveyor is in the lobby.

Falls, psychotropics, weight loss, pressure injuries — every chart has to answer for itself. The binder says what to audit. Nobody has the hours to pull it.

Orenda does the retrieval — and shows you the sentence. The recommendation never travels without its quote, its page and its section.

The platform

Six workspaces. One resident record.

Admissions, MDS, nursing, compliance and the business office each get their own workspace — all reading the same record, so adding a tool never forks your data or your workflow.

Admissions

Admission fit, before the planner calls the next building

Drop a referral packet. Get a 0–100 fit score, an accept, review or decline recommendation, risk factors with severity, staffing impact and a qualifying-stay check — scored against your building’s criteria, not a generic rubric.

Case mix

MDS & PDPM accuracy

A PDPM register across the census and MDS review while the assessment window is still open.

Survey

Survey readiness & F-tag response

Readiness across the building, and a working surface for answering a 2567 with the evidence attached.

Clinical QA

Self-audit & chart review

The audit instruments your QA binder already specifies, run against the chart instead of a clipboard.

Business office

AR, ADR & triple check

Receivables and documentation requests tracked to the resident and the claim, reconciled before billing.

Data

Reads the chart where it already lives

Referral packets drive the admission decision. Every tool after admission reads the resident’s PointClickCare chart, synced into one record — and a result goes stale when the chart changes, not when the calendar says so.

Clinical review

The platform drafts. Your nurse decides.

SBARs, progress notes, care-plan changes and IDT notes are drafted from the chart. A nurse edits them in place and enters them into PointClickCare under their own name.

Nothing auto-posts. No draft reaches a resident’s chart without a clinician putting it there.

Edits save as they type. No forms, no extra attestations — edit, then copy.

Gaps stay visible. Anything the chart could not answer is left as a placeholder, and copy is held until it is filled.

The evidence trail

Every finding shows its source.

A reviewer confirms the quote rather than taking a summary on faith — and every answer comes back in the same shape, so a decision can be filed, compared across months and audited a year later.

A structured record, not a paragraph of prose

Each assessment returns the same fields every time. Nothing is parsed out of free text.

Fit score
0 – 100, computed by the platform from its parts
Recommendation
Accept · review · decline
Risk factors
Factor, severity, clinical note
Staffing impact
Nursing hours, therapy minutes, special needs
Payer & stay check
Payer, qualifying stay, the window it closes in
Cited evidence
Verbatim quote, page and section

The platform owns the answer

Scores, deadlines, F-tags and disclaimers are recomputed after the model responds — never taken from it.

Documents are data, not instructions

A referral packet is untrusted input, fenced off as quoted data — and nothing written in it can move a server-owned field.

Fresh when the chart changes

Each result is stamped with the record it read, so a change in the chart marks it stale the moment it lands.

How it works

From document to decision, in four steps.

1

Configure the building

Acuity ceiling, accepted payers, isolation beds, excluded diagnoses. Stored as a versioned record, so you can see which rules produced last quarter's decisions.

2

Send the document

The upload goes from the browser directly to encrypted storage. Protected health information never passes through an application server.

3

The model reads it whole

Scanned pages go through OCR first; identifiers are stripped; the output is forced into a fixed schema and checked on every run.

4

Read the citation, decide

Every finding carries its quote, page and section. A reviewer verifies the source, and the access is written to the audit log.

Security & compliance

Built for protected health information on day one.

Every architectural decision assumes real patient data, even where only synthetic data is being processed. Your IT reviewer will find the controls where they expect them.

HIPAA-ready architecture TLS 1.2+ · encrypted at rest Multi-factor sign-in Two-hour, revocable sessions Role-based access per route

PHI never touches an app server

Documents upload from the browser straight to encrypted storage through a presigned, size-limited policy. The API never holds the bytes.

Identifiers stay out of the prompt

Names, MRNs and dates of birth are stripped before anything reaches the model. Clinical tools see age, sex and admission date.

Append-only audit log

Who, when, what and from where — on every read of a resident's record, not just every write. No update, no delete.

Tenant isolation

Every row carries its facility and every query is scoped to the caller's. A role never widens the boundary.

Least-privilege roles

Nursing, MDS, business office, therapy, compliance, admissions and IT each see their own workspace — enforced on the server, per route.

One BAA for inference

Model inference runs on AWS Bedrock under a signed business associate agreement, alongside storage and the database.

Integration

Your chart, where it already lives.

Connectors for PointClickCare ship in the platform and stay dormant until your facility supplies credentials.

Recommended first

FHIR R4 / USCDI

US Core 3.1.1 and 6.1.0, from published documentation. Reaches progress, therapy and consult notes, vitals, weights, labs, orders, medications, immunisations, the care plan, coverage, encounters and the document list.

Public documentationSandbox available

Deeper surface

Partner / Marketplace REST

PointClickCare documents a partner programme covering the medication administration record, CNA and ADL charting, and the MDS item sets. We have not yet verified it against a live tenant, so we describe it as their published surface rather than something we read today.

Per-customer LOANot yet verified

By design

Residents are linked by a person

There is no bulk link and no name matching. A wrong link writes one resident’s chart into another’s record and nothing downstream would catch it — so a person confirms each one.

Questions

What administrators ask first.

Something else? Bring it to the walkthrough — we will answer it with the product open.

Does the AI write into the medical record?

No. The platform drafts; a nurse reads, edits and enters the note into PointClickCare themselves. Nothing reaches a resident's chart without a clinician putting it there, and a draft with an unfilled placeholder cannot be copied until it is completed.

Where do the scores come from — the model?

The model reads and extracts; the platform scores. The fit score, deadlines, F-tags and disclaimers are recomputed from structured fields after the model has answered, so a score can always be traced to its parts and an instruction hidden in a document cannot move it.

Do we need PointClickCare to start?

Not for admissions: the fit assessment reads the referral packet you upload. The tools that work after admission — PDPM, survey readiness, clinical QA, drafted notes — read the resident's chart, so they need the resident linked to PointClickCare.

Is our data used to train models?

Inference runs on AWS Bedrock under our BAA, and identifiers are removed before a prompt is built. Your residents' records are processed to answer your question, not collected to train anything.

How do multi-facility operators use it?

Each building keeps its own criteria, staff and data. One account can work across the buildings it has been granted, with every access recorded against the building and the authority it was made under.

Book a walkthrough

See it on your own referral.

Bring a packet — synthetic, or redacted from your building — and we run it live against your intake criteria.
Thirty minutes. No preparation needed on your side.
Multi-facility operators: we will walk the cross-building view and the per-facility criteria model.

Do not send protected health information through this form.

Orenda Intelligence — Clinical & financial intelligence for skilled nursing