Manage by exception
Focus staff on true care-plan exceptions and meaningful patient changes rather than reconstructing every journey manually.
Risk-bearing providers
Protect value across care that happens beyond the encounter.
For ACOs, MSOs, IPAs, value-based medical groups, and other organizations accountable for total cost, quality, or shared savings.
Population viewManage by exception
Care journey reconciledon trackFuture care scheduledwatchingExpected care has no planfollow upMeaningful patient changereview
Why it matters
The visit may be over. Your accountability is not.
Referrals still need to close, follow-up still needs to happen, transitions still need to hold, and changes in a patient’s condition can drive avoidable utilization. reCare.ai gives risk-bearing teams one way to understand both whether expected care is on track and whether the patient is meaningfully changing.
What this changes
Act before avoidable outcomes
Find missing or threatened care and recognize rising-risk patient changes while outreach, navigation, coordination, or review can still affect the outcome.
Connect action to economics
Track closed-loop activity around workflows tied to quality, utilization, care capture, or shared-savings performance.
Starter workflows
Three concrete places to start.
Referral closure
- Observe
- Referral order, scheduling, specialist encounter, and documented downstream plan.
- Detect
- Referral or downstream care with no completed or planned reconciling event.
- Act
- Patient outreach, scheduling, navigation, or staff escalation.
- Measure
- Referral completion, time to close, and downstream follow-through.
Post-discharge transition
- Observe
- Discharge event, prescribed follow-up, scheduled visits, medication activity, utilization, engagement, symptoms, and other transition evidence.
- Detect
- Missing or delayed expected follow-up, plus patient-level changes that may indicate rising readmission or acute-care risk.
- Act
- Outreach, navigation, scheduling, coordination, or escalation with the relevant patient context attached.
- Measure
- Follow-up completion, unresolved exceptions, time to intervention, and—where available—subsequent acute-care utilization.
Preventive & chronic-care follow-through
- Observe
- Expected monitoring, orders, future appointments, results, and relevant care-plan dependencies.
- Detect
- Expected action with neither completion nor a credible future plan.
- Act
- Outreach, scheduling, or care-team workflow.
- Measure
- Closure rate and outstanding actionable exceptions.
How reCare.ai works here
Turn accountability between encounters into an operating workflow
Choose a measurable journey
Start with a care process that has clear expected steps and an identifiable clinical or economic outcome.
Reconcile the population
Determine which patients are on track, which already have future care planned, and which have a true exception.
Work the exception
Use approved automation and human workflows to recover missing or incomplete care.
Measure closure
Track whether the intended next step was planned, completed, or still requires action.
Measurement
Every deployment starts with a measurable hypothesis.
Exception precision
How often a surfaced journey actually requires intervention.
Manual review burden
How many patient journeys staff must investigate manually before and after deployment.
Closure rate
Whether intended care is ultimately scheduled, completed, or otherwise reconciled.
Time to intervention
How quickly an unresolved journey is identified and acted on.
Workflow resolution
What happened after outreach, coordination, or escalation.
Economic outcome
Where measurable, the effect on utilization, care capture, quality, or shared-savings performance.
Early deployments are designed to validate these measures against each organization’s existing workflow and baseline. reCare.ai does not assume an ROI result before that baseline is established.
FAQ
Common questions about this workflow.
Where should an ACO or risk-bearing group start?
Start with one measurable journey such as referral closure, post-discharge follow-up, or preventive/chronic-care follow-through where expected steps and outcomes can be observed.
What does reCare.ai measure in an early deployment?
Typical measures include exception precision, manual review burden, closure rate, time to intervention, workflow resolution, and—where measurable—economic or quality impact.
Move from signals to action
See whether care is on track, and when the patient is changing.
Bring us a high-value workflow, a care-plan problem, or a population where earlier visibility into patient change could prevent an avoidable outcome. We’ll show you how the intelligence layer fits.