Therapeutic area · Healthy aging and prevention
Longevity programs are judged on change over months. Clarrio.ai turns assessments, biomarkers and everyday data into one longitudinal record for members, clinicians and program leaders. Align clinical, treatment and behavioral information on one shared longitudinal timeline, where available and appropriate to the program.
What Clarrio.ai captures
Longitudinal health intelligence
Align clinical observations, medication or intervention history, and daily-life context without losing source meaning. Available data and review boundaries depend on the program.
One person / one shared timeline
Illustrative research data · Synthetic demonstration
Health and disease trajectories
Resting heart rate
Treatments and interventions
Exposure · dose · reported experience
Behavior and daily life
Average sleep
Week 4 / Disease64 bpm · Connected observation
Week 4 / TreatmentPlan adjustment · Recovery days added
Week 4 / Behavior7.1 h · Routine resumed
Separate measures and independently scaled channels; values appear in their own units. Temporal alignment does not establish causality.
The evidence gap
Longevity and preventive health clinics run comprehensive assessments: labs, body composition, cardiometabolic tests, fitness. Between those assessments, members wear devices and follow protocols, but that data rarely returns to the clinic in a usable form.
Without a continuous record, clinics struggle to show members their progress, to adjust protocols with evidence, or to report program outcomes to leadership and partners.
Cardiometabolic
Lipids, glucose and blood pressure measured a few times a year.
Sleep & recovery
Wearable data stays in consumer apps.
Function
Strength, VO2 max and mobility tested occasionally.
Wellbeing
Stress and mood are rarely tracked systematically.
The challenge
A metabolic or healthy-aging program is judged on change over months, yet most of the evidence arrives as two or three lab draws a year. Training blocks, travel, illness and diet changes happen in between and leave no trace in the record. The result is a program that can report where a member ended up, but not what moved them there.
Toggle the chart to compare what a visit-based record shows with what the continuous record shows for the same synthetic patient.
Fasting glucose (mg/dL) over 120 days
Observations2
Events in periodNot visible
Events with no nearby visit3 of 3
Illustrative · synthetic data
Between draws
Response is invisible
Labs confirm a result; they rarely explain which protocol change produced it.
Per member
Averages hide responders
Program-level averages blend members who respond strongly with those who do not respond at all.
Renewal
Value is hard to show
Without a visible trajectory, members and leadership see cost, not progress.
How Clarrio.ai addresses the gap
Seven health domains
Cardiometabolic, sleep, activity, biomarkers, lifestyle, wellbeing and environmental context.
Member app
Device connection, check-ins and personal progress views.
Clinic dashboards
Baseline versus follow-up, domain profiles and engagement.
Research-ready data
Program datasets for internal review or partnerships.
Data captured
Select a layer. Exact sources depend on deployment configuration and data permissions.
Captured from patients or caregivers in the Patient App.
Product workflow
Select a step to see what happens. Sources are captured through the Patient App and integrations, harmonized on the Platform and summarized by Intelligence.
Sources
Clarrio.ai workflow
Outputs
Stakeholder outputs
Each role receives a different view of the same longitudinal record. Values are synthetic.
Member
Members see which routines coincided with better readings in their own data, framed as associations rather than advice.
Physician
Before the review, the physician reads a dated summary of the period since the last draw instead of reconstructing it from memory.
Clinic lead
Leadership sees engagement and trajectory across the member base, the basis for program reporting.
Worked examples
Member, metabolic program
Week 0
Baseline panel; protocol set.
Weeks 2–6
CGM shows evening spikes after late training sessions.
Week 7
Coach sees the pattern in the pre-call summary and moves training earlier.
Week 16
Second panel; the record shows when the change began.
Illustrative · synthetic data
Clinic leadership
Month 1
Cohort defined: members enrolled this quarter.
Month 3
Dashboard shows completeness and trajectories.
Month 6
Export supports an internal program review.
Illustrative · synthetic data
FAQ
Research & operational outputs
Member longitudinal dashboard
All domains on one timeline.
Health domain profiles
Where each member stands, and how it is moving.
Baseline vs follow-up
Structured comparison between assessments.
Program analytics
Engagement and trajectories across the member base.
Longevity clinics
Evidence of member progress and program value.
Physicians & coaches
Between-assessment context for protocol decisions.
Members
A visible, personal record of change.
Pharmaceutical & biotech
Research partnerships on healthy aging cohorts, with consent.
Program evaluation
These are the KPIs we agree with customers before deployment, measured against their own baseline. Data coverage, patient experience and clinical outcomes answer different questions. Higher engagement alone does not demonstrate better health or lower utilization.
Explore benefits and evidence| Lever | How it is measured |
|---|---|
| Member retention | Members renewing relative to eligible |
| Engagement | Members syncing data in last 14 days |
| Clinician time | Minutes spent compiling pre-review data |
| Program reporting | Hours to produce outcome reports |
Illustrative use case
Longevity clinic, illustrative
Month 0
Baseline assessment and device connection.
Months 1–6
Weekly data sync; monthly wellbeing check-ins.
Month 6
Mid-point review with domain profiles.
Month 12
Follow-up assessment compared against baseline.
Illustrative · synthetic data
Clarrio.ai has joined Mayo Clinic Platform's Solutions Studio, supporting its mission to advance interoperable, data-driven healthcare innovation. This does not imply endorsement or clinical validation.
See Clarrio for Longevity Clinics
See Clarrio for Longevity ClinicsEvidence interpretation
Keep laboratory intervals distinct from device sampling. A member-reported routine change can explain the review question without establishing its cause. Payer-facing evaluation needs a defined preventive service and outcomes beyond participation.
Benefits in practice
Longevity clinics
An annual assessment and a wearable dashboard answer different questions. The assessment describes a scheduled measurement; a device records selected aspects of everyday life. Neither alone explains whether a member could sustain a routine, why observations stopped or what they want to discuss. Combining them is useful only when the dates, measurement methods and member context remain distinguishable.
01
Choose a specific interval and member goal rather than collecting every available signal.
02
Use the Patient App for member context, the Platform for available source coverage and Intelligence for source-aware review.
03
Compare like-for-like observation windows, inspect gaps and bring unresolved questions to the physician or coach.
Physicians and coaches gain a structured basis for preparation: which period changed, which source supports the observation and which question remains open. Leadership can separately review onboarding, connection support and review workload. A more detailed chart does not establish that the program improved health or extended life.
Members can explain travel, routines and personal priorities alongside their observations. The benefit is continuity of the conversation, not another unexplained score. A useful member journey also makes room for people without a wearable and makes clear when the team will review what they share.
For an employer or payer considering a preventive program, participation and data coverage are starting points, not evidence of prevention or savings. Define the eligible population, program services and evaluation period before comparing results. A self-pay clinic membership does not imply an insurance coverage benefit.
Workflow illustration · not a customer result or live record
Track whether intended records are available, whether reviews are completed and whether members find the reporting burden acceptable. Analyze renewals separately from health outcomes; neither should be attributed to a software workflow without a suitable evaluation.
Explore evidence and evaluationPayers & health economics
Claims and encounter datasets can describe recorded utilization without fully capturing function, experience or the practical burden of a program. Patient reports add a different perspective, but they can be incomplete or drawn from a population unlike the members covered by a payer. The task is to establish whether those observations are suitable for a specific appraisal question, not to turn engagement into a savings claim.
01
Specify the relevant covered population, decision, comparator where needed and evaluation horizon.
02
Review provenance, participation, measurement windows and missingness before examining results.
03
Combine appropriately governed patient experience with relevant clinical or utilization evidence; document assumptions and limits for expert appraisal.
HEOR and population-health teams can examine how reported experience varies across the observation period and which groups are represented. A useful output explains the denominator behind a measure and the observations excluded from analysis. Governance must also define the permitted purpose of any linkage to payer-held data.
The member perspective should remain visible in a program evaluation: burden, everyday function, access and what participants consider meaningful. Reporting should not become an unexplained condition of receiving services. Explain the collection purpose and permitted uses in a way members can understand.
Decision support means an inspectable evidence package, not an automatic reimbursement verdict. Include the target population, relevant baseline differences, data sources, follow-up and limitations. Cost and utilization conclusions need appropriate data and analysis; neither can be inferred from app activity or observation coverage.
Workflow illustration · not a customer result or live record
Separate program participation, patient-reported experience, clinical outcomes and economic endpoints. Define each before collection, use an appropriate comparison where the question requires one and examine whether findings transfer to the covered population.
Explore evidence and evaluationPatients, members & caregivers
A person can complete many questions without understanding why they are being asked or who will read the answers. Device observations may look precise while missing personal context. A useful longitudinal journey starts with the person's priorities and makes the reporting purpose, burden and review arrangements understandable.
01
Agree what the care or research program needs to learn and what participation involves.
02
Use appropriate reports alongside available observations; distinguish the patient's own answers from caregiver observations.
03
Discuss a dated interval with the responsible professional, including what is missing and what matters to the person.
Teams gain context for a more specific conversation, but should not assume that a missed report means a person disengaged. Accessibility, fatigue, language and connectivity may affect reporting. Define support and review arrangements before introducing new questions.
Patients and members can keep a dated account of experiences they might otherwise forget. Caregivers can contribute observations when appropriately scoped, without replacing the person's own perspective. Personal patterns invite discussion; they are not instructions or proof that a particular routine produced an outcome.
A program's apparent reach can hide who could not participate. Payers and commissioners should examine access, reporting burden and representativeness alongside outcome evidence. Patient experience is an important perspective in appraisal, not a shortcut to an economic conclusion.
Workflow illustration · not a customer result or live record
Ask whether reporting is understandable, manageable and meaningful. Examine completion alongside accessibility and support needs. A high completion rate alone does not show that people feel heard or that a program has improved their health.
Explore evidence and evaluationRelated solutions
Understand how health status, interventions and lifestyle behaviors evolve together over time. Clarrio.ai aligns those dimensions on a shared longitudinal member timeline.
See solutionConnect clinical information with longitudinal treatment and patient-generated data for research and appropriate healthcare workflows. A shared timeline preserves source context for professional review.
See solutionRequest a demo
Explore how clinical, treatment and behavioral information align around your program and the research or review questions your team needs to answer.
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