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Pre-launch draft for review. Not yet public.

Sample report

See what an AI screening can reveal.
Then validate it with an independent baseline.

These fictional self-reported results illustrate AI governance and performance questions that warrant further investigation. They do not show verified facility conditions. A paid AISureCare baseline establishes the evidence used for future comparisons.

No real organization's results appear on this site.

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Senior living example

Illustrative example

Westbrook Skilled Nursing (fictional)

Senior living version. Names and details are invented.

Overall readiness score

14 / 36

Developing Readiness

Some structure is in place, but important gaps remain. Start with low-risk improvements and document current AI use before adding larger AI tools.

Score by area

  • AI Inventory and Goals Needs Attention2 / 6
  • Staff and Shadow AI Needs Attention1 / 6
  • Workflow and Human Review Needs Attention3 / 6
  • AI Vendor and Purchase Review Needs Attention1 / 6
  • Data and Incident Safeguards Strong5 / 6
  • Impact and Ongoing Oversight Needs Attention2 / 6

Where to start

  1. AI Vendor and Purchase Review

    A new AI-enabled vendor feature was selected without a written data-handling review or performance baseline.

    Next step: Assign a purchase reviewer and document vendor questions, intended results, and approval criteria.

  2. Staff and Shadow AI

    Staff may be using unapproved AI to rewrite shift notes, with no clear guidance about what information may be entered.

    Next step: Identify current staff AI use and put interim boundaries in writing before authorizing more tools.

  3. AI Inventory and Goals

    Leadership knows about some AI features but lacks a current list of tools and the purposes they are expected to serve.

    Next step: Start an AI inventory; for the first priority tool, record its owner, purpose, and success measure.

Suggested next 90 days

  1. Next 30 days: Complete a list of AI tools, embedded features, and informal use, with an owner for each.
  2. Next 60 days: Use a purchase checklist for the next software decision and walk staff through the incident reporting steps.
  3. Next 90 days: Record starting measures for one AI-supported workflow and schedule a first review of results.

Services that fit these results

  • Safe AI Governance, to assess AI tool inventory, shadow AI, purchasing review, and staff rules
  • Proven Impact, to compare deployed AI against agreed outcome measures
  • AISureCare Complete, if leadership wants both handled together

Illustrative self-reported screening only. Westbrook Skilled Nursing is fictional. No real facility was evaluated; verified baselines and independent follow-up are separate AISureCare engagements.

Want results like these for your own facility?

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Grant-funded AI example

Illustrative example

Prairie Valley Health (fictional)

Grant-funded AI version. Names and details are invented.

Overall readiness score

24 / 36

Developing Readiness

Some pieces are in place, but measures, current workflows, or timing need work before go-live. This does not mean the project is unprepared. It means the next step is a focused baseline plan.

Score by area

  • Grant Commitments and Measures Developing4 / 6
  • Current Workflow Baseline Strong5 / 6
  • Starting Point for People and Staff Strong5 / 6
  • Existing AI and Data Readiness Needs Attention2 / 6
  • Baseline Timing and Ownership Developing4 / 6
  • Comparison and Independent Review Developing4 / 6

Where to start

  1. Existing AI and Data Readiness

    Partners already use scheduling and messaging tools with built-in AI that no one has listed, and the data agreement does not cover summary reports.

    Next step: List existing AI across partners and confirm which data can be shared in summary form before the baseline starts.

  2. Grant Commitments and Measures

    The grant promises better follow-up after hospital discharge, but only activity counts are defined.

    Next step: Turn each promised outcome into one measure, including at least one for the older adults the project serves.

  3. Comparison and Independent Review

    Follow-up measures are planned, but their timing is not tied to the funder's reporting schedule.

    Next step: Set repeat measures on the funder's reporting dates and plan an independent check of the baseline.

Suggested next 90 days

  1. Next 30 days: Confirm a data source for each measure, and list existing AI across partners.
  2. Next 60 days: Record current staff time and the current experience of the people served, in summary form.
  3. Next 90 days: Finish the baseline before go-live, and schedule repeat measures to match funder reporting.

Bottom line: Prairie Valley can describe what its grant will achieve. Before the AI goes live, it needs a clean list of existing tools, measures for the people it serves, and a comparison schedule its funder will accept.

Services that fit these results

  • Grant / RHTP Support, to check the baseline and sign findings comparing results with grant goals
  • Safe AI Governance, to list existing AI across partners and set data-sharing rules

Illustrative self-reported screening only. Prairie Valley Health is fictional. No real facility was evaluated; verified baselines and independent follow-up are separate AISureCare engagements.

Your turn

Know what your AI screening suggests.
Then decide whether to validate it on site.

Twelve self-reported questions help identify potential AI governance and measurement gaps. A separate paid baseline documents actual conditions.

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