Care journey intelligence
Is expected care completed, already planned, or truly missing?
- Referral and specialist follow-through
- Post-discharge care-plan completion
- Preventive and chronic-care monitoring
- Recoverable care and revenue leakage
Patient intelligence for risk-bearing care.
Know whether care is on track. Recognize when the patient is changing.
Act before either leads to an avoidable outcome. reCare.ai is a patient-intelligence platform for ACOs, MSOs, medical groups, and complex-care organizations. It connects longitudinal clinical and operational signals to understand both the care plan and the patient—what should happen, what is already in motion, and what is meaningfully changing.
Patient journeySpecialty referral
Needs follow-up✓
Referral orderedCompleted Sep 18
Observed→
Specialist visitScheduled next week
Planned!
Post-visit labsExpected within 14 days
No plan foundJourney is not fully reconciled
Upcoming specialist care is on track, but the downstream lab plan is incomplete.
What reCare.ai does
One patient context. Two kinds of exceptions.
Care-plan exceptions: reCare.ai reconciles expected care with completed and planned events so teams can see whether the journey is on track or whether a real gap is emerging.
Patient-change exceptions: reCare.ai also looks across longitudinal utilization, engagement, symptoms, behavior, and other available signals to recognize when the patient’s own pattern is changing in a way that may indicate rising risk.
Two lenses on the same patient
Understand the care plan. Understand the patient.
Patient risk intelligence
Is something meaningfully changing for this patient?
- Changes in utilization or acute-care activity
- Symptoms, engagement, and behavioral shifts
- Patient-specific deviation from recent baseline
- Signals associated with rising readmission risk
What reCare.ai can do today
Built to operate on real healthcare workflows.
✓
Ingest clinical and operational events from existing systems
✓
Normalize events into longitudinal patient context
✓
Compare expected care against completed and planned care
✓
Detect missing steps and meaningful patient-level changes
✓
Trigger approved outreach and coordination workflows
✓
Track whether the expected next step actually occurred
✓
Preserve the evidence behind each surfaced exception
Integration patterns
FHIRAPIsWebhooksEvent feedsScheduling dataReferral dataClaims & data files
Start with a focused, measurable workflow. Connect the data needed to support it, prove value, then expand the longitudinal patient context over time.
How it works
From fragmented signals to a closed care loop.
Build the patient picture
Bring clinical, scheduling, referral, utilization, engagement, symptom, and other relevant signals into one current patient view.
Reconcile the care plan
Compare expected care with what is completed, scheduled, or planned. Surface only the true gap or incomplete plan.
Detect meaningful change
Compare new signals with the patient’s own baseline and current plan to identify changes that may signal rising risk.
Act and close the loop
Push the next action into the care plan or work queue teams already use, then capture the outcome.
What the intelligence layer produces
See the journey, the exception, and the evidence together.
This illustrative view uses synthetic patient data. It shows the kind of patient-level context reCare.ai can assemble for a defined workflow; it is not presented as a finalized production UI.
Day 0
Hospital discharge
CompleteTransition plan documented
Day 2
Medication review
ReconciledCompleted with patient
Day 3
PCP follow-up
On trackScheduled for Day 7
Day 4
New symptom report
ChangePatient-reported change from recent baseline
Day 5
Engagement pattern changes
SignalTwo expected check-ins not completed
Today
Care-team review requested
ReviewPatient-change evidence attached
Fits your operating model
Put the intelligence back where your team already works.
reCare.ai pushes the next action and supporting context back into the care plan or action queue your team already uses, whether that’s in the EHR or another workflow system. No separate inbox. No new operating pattern.
Surface the exception
Detect the care-plan gap or meaningful patient change, and keep the evidence attached.
Add the right context
Show what’s completed, scheduled, planned, or changing, so the next person knows what matters.
Push the action into the workflow
Push the next action and supporting context into the care plan, work queue, task, notification, outreach flow, or API.
Close the loop
Capture the action and outcome, so reCare.ai knows what happened, what changed, and what remains open.
Operational impact
Change how teams manage the work between encounters.
Without reCare.aiWith reCare.ai
Static lists and fragmented systemsA patient context that updates as relevant events arrive
Manual review to find missing follow-upExpected care reconciled against completed and planned events
Population risk scores without current contextPatient-level change interpreted against recent history and the current care plan
Handoffs that are hard to verifyClosed-loop workflows that capture what happened next
Fewer missed care opportunities
See when expected care has no completed or planned event before the opportunity disappears.
Earlier risk visibility
Recognize meaningful changes in utilization, symptoms, engagement, or other patient-level signals before they become an avoidable outcome.
More informed follow-up
Start outreach with the patient’s history, expected care, current plan, recent changes, and supporting evidence already in context.
Better closed-loop execution
Track whether the intended next step was scheduled, completed, or still needs intervention.
Who we serve
For teams accountable beyond the encounter.
01
Risk-Bearing Providers
ACOs, MSOs, IPAs, value-based medical groups, and teams accountable for cost, quality, or shared savings.
Explore →02Senior & Complex Care
Organizations managing high-need populations where meaningful change often happens between traditional encounters.
Explore →03Care Transitions
Teams responsible for ensuring the expected care journey actually continues after a discharge or handoff.
Explore →Built for healthcare
Automation with boundaries.
Human-in-the-loopEscalate decisions requiring clinical judgment or policy-defined review.
Healthcare data handlingProcess PHI according to customer agreements and applicable healthcare privacy requirements.
Traceable workflowsPreserve the context, action, and outcome behind patient-level workflow decisions.
Insights
Thinking beyond the encounter.
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Read article →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.