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Case Manager

Coordinating referrals and service connections

Enhances✓ Available Now

What You Do Today

Connect clients to housing programs, mental health services, job training, legal aid, childcare, food assistance — navigating a fragmented system that's hard even for professionals.

AI That Applies

AI maintains a real-time resource directory with current availability, eligibility requirements, and wait times. Matches client needs to available services automatically.

Technologies

How It Works

For coordinating referrals and service connections, the system draws on the relevant operational data and applies the appropriate analytical models. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context.

What Changes

You know which services have current openings and eligibility matches before making calls. Less time on hold, more accurate referrals.

What Stays

Navigating waitlists, advocating for your client's priority, and building relationships with service providers. The system is imperfect — you bridge the gaps.

What To Do Next

This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.

1

Establish Your Baseline

Know where you are before you move

Before adopting AI tools for coordinating referrals and service connections, understand your current state.

Map your current process: Document how coordinating referrals and service connections works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: Navigating waitlists, advocating for your client's priority, and building relationships with service providers. These are the boundaries AI won't cross.
Assess your data readiness: AI tools for this area need data to work. Check whether your organization has the historical data, integrations, and data quality to support resource directories (Aunt Bertha/findhelp, 211) tools.

Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.

2

Define Your Measures

What to track and how to calculate it

Time per cycle

How to calculate

Measure how long coordinating referrals and service connections takes end-to-end today, then after AI adoption.

Why it matters

The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.

Quality of output

How to calculate

Track error rates, rework frequency, or stakeholder satisfaction scores before and after.

Why it matters

Speed without quality is just faster mistakes. Measure both.

When to check: Check after 30 days of consistent use, then quarterly.
The commitment: Give new tools at least 30 days before judging. The first week is always awkward.
What NOT to measure: Don't measure AI adoption rate as a KPI. Adoption follows value — if the tool helps, people use it.
3

Start These Conversations

Who to talk to and what to ask

your department medical director

What's the biggest bottleneck in coordinating referrals and service connections today — and would AI address the bottleneck or just speed up something that's already fast enough?

They set clinical practice guidelines that AI tools must align with

your health informatics lead

How do we currently measure service quality, and would AI-assisted responses change that measurement?

They manage the EHR integrations and clinical decision support configuration

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.