St. Croix County Health Care Campus · exacare

The problem

Manual, paper-heavy referral review process for admissions was difficult to scale with growing referral volume and increasing hospital turnaround expectations, leading to missed details and referrals.

What was deployed

Vendor

exacare

Products

exacare ai

Technique

NLP

Build or buy

Bought off the shelf

Deployment

SaaS

Data used

referral packets (clinical packets, physician orders, encounter documentation, medication information)

Scale

50-bed long-term care/transitional care building, 48-bed assisted living/memory care building, 10-bed locked dementia crisis unit

What changed

Each row is quoted from the source. Figures we could not find on the page in those words are marked — they are kept, not deleted, so you can judge them.

Difficulties and limits

• A careful, paper-based workflow had become difficult to scale as referral volume, packet length, and hospital turnaround expectations increased.
• We were getting so many referrals that sometimes, by the time we called back, the resident had already been placed somewhere else.
• With 100-page referral packets, it was hard to catch every detail as quickly as we needed to. That could mean missing an appropriate referral or moving forward without the full picture.

• The platform gives the team a stronger starting point but does not replace clinical judgment — staff still review every referral rather than relying on AI recommendations alone

Sources

• exacare.com — vendor self-report, 2026-06-11