What is this course about?
Transitions are the highest-risk moment in a care episode and the point where patients most often fall out of the system. This course covers referral loop closure, transition summaries the receiving clinician can actually use, post-discharge follow-up sequences, social determinants and resource navigation, and interoperability across organizations that do not share an EHR.
Who is this course for?
- Care coordination and case management staff
- Population health teams
- Transitions of care programs
- Clinical operations leaders
What do I need before starting?
- Care coordination or case management experience
- Familiarity with your referral workflow
What will I be able to do afterwards?
- Quantify where patients are lost in transitions
- Close referral loops and detect the ones that stall
- Produce transition summaries the receiving clinician can use
- Design post-discharge follow-up that reduces readmission
- Coordinate across organizations that do not share an EHR
What does each module cover?
Where are patients actually lost?
45 minMeasuring loop closure and the transition points where patients disappear.
Objectives
- Measure referral loop closure rates
- Identify the highest-loss transition points
- Quantify the clinical consequence
Topics
Activity. Measure loop closure for one referral type and identify where patients are lost.
How do you close a referral loop?
50 minTracking a referral through to a completed visit and a report back.
Objectives
- Track referrals through to completion
- Detect stalls at each stage
- Escalate before the patient is lost
Topics
Activity. Build referral tracking with stall escalation for one specialty.
What makes a transition summary usable?
50 minSummaries the receiving clinician reads, rather than a document dump.
Objectives
- Produce summaries a receiving clinician can use
- Include what the receiver actually needs
- Avoid the information dump that gets ignored
Topics
Activity. Produce transition summaries and have receiving clinicians rate their usability.
How do you design post-discharge follow-up?
45 minFollow-up sequences timed and targeted to reduce readmission measurably.
Objectives
- Design follow-up timing and content
- Target patients by readmission risk
- Measure the readmission effect
Topics
Activity. Design a follow-up sequence with a measurable readmission comparison.
How do you handle social determinants?
45 minResource navigation for the barriers that actually prevent follow-through.
Objectives
- Identify social barriers to follow-through
- Match patients to available resources
- Track whether the connection was made
Topics
Activity. Build resource matching for your service area and verify the resources exist.
How do you coordinate across organizations?
45 minInteroperability with organizations that do not share your EHR.
Objectives
- Exchange information across organizational boundaries
- Handle organizations without modern interfaces
- Meet privacy requirements in exchange
Topics
Activity. Map information exchange with a referral partner outside your EHR.
How do you measure the program?
40 minLoop closure and readmission as outcome measures rather than activity counts.
Objectives
- Define outcome measures for coordination
- Distinguish activity from outcome
- Report honestly including null results
Topics
Activity. Design the measurement plan with a comparison condition.
Building the loop-closure agent
50 minThe lab module: an agent that escalates stalled referrals before patients are lost.
Objectives
- Build the loop-closure agent
- Implement stage-level stall escalation
- Measure closure rate improvement
Topics
Activity. Deploy the agent and measure loop closure against baseline.
What is the capstone project?
Referral loop-closure agent with measured improvement
Build a care coordination workflow with referral tracking and stall escalation, usable transition summaries rated by receiving clinicians, risk-targeted follow-up, verified resource matching, cross-organization exchange, and measured loop closure against baseline.
Deliverable: A deployed agent with before-and-after loop closure and readmission figures.
How are learners assessed?
- Loop closure measured against a real pre-deployment baseline
- Transition summaries rated for usability by actual receiving clinicians
- Resource matching verified — every resource must actually exist and accept referrals
What ships with the course?
Facilitator guide
Session-by-session running order, discussion prompts, and the questions that reliably derail a room.
Learner workbook
Exercises, checklists, and the templates each module's activity produces.
Hands-on lab environment
A sandboxed ibl.ai deployment so exercises run against real agents, not screenshots.
Assessment bank
Scenario questions and rubric criteria mapped to each stated learning outcome.
Source bibliography
Every primary regulation and standard cited on this page, linked and dated.
Which AI agents does this course use?
The hands-on modules run against agents already deployable on the ibl.ai platform for healthcare.
Where does the course material come from?
Every module is grounded in primary sources — the regulation, standard, or research itself, not a summary of it. Each was resolved at authoring time.
- Centers for Medicare and Medicaid Services
CMS
Transitions of care requirements and readmission programs.
- HL7 FHIR
HL7
The interoperability standard for cross-organization exchange.
- Agency for Healthcare Research and Quality
AHRQ
Transitions of care evidence and measurement methodology.
- HealthIT.gov
ASTP/ONC
Information blocking rules and exchange requirements.
Delivery notes
Binding guidance for anyone preparing and delivering this course.
- Module 1's loop closure measurement is usually a shock. Organizations assume closure rates far above reality, and the measurement is what motivates the rest of the course.
- Module 5's resource verification matters. Referring a patient to a resource that no longer exists or does not accept their insurance is worse than not referring.
- Module 3's usability rating must come from receiving clinicians, not the sending organization. Senders consistently overestimate how usable their summaries are.
- Module 6 should acknowledge that many referral partners have no modern interface. Fax remains real and the workflow must handle it.
- Coordinate with MED-5 — post-discharge patient education and coordination follow-up are the same touchpoint and should not be two separate contacts.
Why run AI training on a platform you own?
You own the course, not a licence to it
Course content, learner data, and the platform run inside your perimeter — you own all the code and the data.
Model-agnostic delivery
Run the course's AI components on any LLM — Claude, GPT, Llama, Gemini, Command — and switch anytime.
No per-seat training licences
Usage-based or self-hosted, so cost tracks actual use rather than headcount.
Deploy anywhere
Cloud, private VPC, on-premise, or fully air-gapped — including for cohorts that cannot use public AI tools.
Frequently asked questions
What does the Care Coordination Agents: Referrals and Transitions course cover?
Transitions are the highest-risk moment in a care episode and the point where patients most often fall out of the system. This course covers referral loop closure, transition summaries the receiving clinician can actually use, post-discharge follow-up sequences, social determinants and resource navigation, and interoperability across organizations that do not share an EHR. It runs 5 hours across 8 modules across 8 modules, at intermediate level, and closes with a capstone: Referral loop-closure agent with measured improvement.
Who should take Care Coordination Agents: Referrals and Transitions?
It is written for Care coordination and case management staff, Population health teams, Transitions of care programs, Clinical operations leaders. Prerequisites: Care coordination or case management experience; Familiarity with your referral workflow.
Can we run this course on our own infrastructure?
Yes. ibl.ai is model-agnostic and deploy-anywhere — cloud, private VPC, on-premise, or fully air-gapped — and you own all the code and the data. Cohort data, submissions, and any material learners upload stay inside your perimeter, which matters for healthcare teams that cannot send work to a public AI tool.
How do we get access to Care Coordination Agents: Referrals and Transitions?
Request access and we will set it up for your cohort — hosted by ibl.ai, or running against your own deployment. Tell us the group size and timing you need, and whether it should run inside your own perimeter.
How much does AI training for healthcare cost on ibl.ai?
There is no per-seat pricing — you pay for usage or self-host and pay only for the infrastructure, so a 5,000-person rollout does not cost 5,000 licences. 1.6M+ users across 400+ organizations run the platform this way, including NVIDIA, MIT, and Syracuse University.