Patient with a long-term condition
A flare reviewed early
Day 104
Weekly PRO shows a sharp rise.
Day 105
Patient at top of worklist with reason.
Day 105
Care manager calls and documents outreach.
Illustrative · synthetic data
Therapeutic area · Long-term conditions
Chronic disease between scheduled visits
Long-term conditions are lived every day. Clarrio.ai keeps the record running between appointments. Align clinical, treatment and behavioral information on one shared longitudinal timeline, where available and appropriate to the program.
What Clarrio.ai captures
- Condition-specific PROs
- Home devices and wearables
- Medication and adherence
- Lifestyle and environment
- Clinical records
The challenge
Chronic conditions change slowly, then suddenly
Long-term conditions are lived every day but reviewed periodically. Gradual decline is easy to miss, and sudden deteriorations often occur between appointments. Care teams managing large panels need to know who to contact first and why, but home data, adherence and symptoms sit in separate places or are not captured at all.
Toggle the chart to compare what a visit-based record shows with what the continuous record shows for the same synthetic patient.
Symptom burden (0–10) over 120 days
Observations2
Events in periodNot visible
Events with no nearby visit3 of 3
Illustrative · synthetic data
Large panels
Limited time
Care managers cannot review every patient, every week.
Silent decline
Gradual change
Slow deterioration rarely prompts a call until it becomes acute.
Fragmented data
Many sources
Home devices, PROs and records are seldom seen together.
Product workflow
How the record is built, step by step
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
- Condition-specific PROs
- Home devices & wearables
- Medication & adherence
- Lifestyle & environment
- EHR records
Clarrio.ai workflow
Outputs
- Outreach worklist
- Patient trajectory
- Population insight
Stakeholder outputs
Role-specific views of the longitudinal record
Each role receives a different view of the same longitudinal record. Values are synthetic.
Care manager
Outreach worklist
Who to contact first, with the reason shown next to each name.
Clarrio.ai / Outreach worklistSynthetic
- Patient K-412FlareSymptom burden up 3 points this week
- Patient K-087DecliningGradual rise over 4 weeks
- Patient K-233No dataNo check-in in 15 days
Clinician
Trajectory in workflow
A between-appointment summary alongside the patient's record.
Clarrio.ai / Trajectory in workflowSynthetic
- Since last visit2 flaresDays 40 and 104
- Adherence82%Self-reported
- ActivityBelow baselineLast 3 weeks
Executive
Population trends
Condition-level trends inform staffing and service design.
Clarrio.ai / Population trendsSynthetic
- Patients monitored2,150Active in last 14 days
- Flares this quarter318Self-reported
- Outreach volume46Per care manager
Worked examples
Two illustrative scenarios
Health-system leadership
Planning a service
Quarter 1
Population dashboard established.
Quarter 2
Flare patterns inform clinic capacity.
Illustrative · synthetic data
FAQ
Chronic disease questions
Evidence interpretation
A long-term record needs both continuity and a workable review process
Multiple conditions and changing services can complicate comparisons. Specify which reports are relevant, who reviews them and how source interruptions are handled. Program participation, clinical outcomes and utilization must be evaluated separately.
Benefits in practice
From chronic disease observations to a useful review
Pharma & biotech
Start with the evidence question a decision-maker actually needs answered
Routine records can describe encounters and prescriptions while leaving daily function, symptom burden and experience under-observed. Adding remote data can fill selected gaps, but a large dataset is not automatically decision-ready. Population selection, questionnaire suitability, exposure timing and missing observations can all change the interpretation of a longitudinal analysis.
01
Specify the evidence objective
Define the population, observation window, outcome concept and intended decision before selecting sources.
02
Collect and reconcile
Combine appropriately scoped Patient App reports with available clinical and device data in the Platform; keep reported experience separate from recorded events.
03
Review before analysis
Use source-aware review to inspect context and quality. Agree variable definitions, analysis methods and limitations with the study team.
For the professional team
Clinical development, medical affairs and HEOR teams can work from a common record while asking different questions. Clinical operations needs coverage by site and timepoint; an evidence analyst needs definitions and provenance; medical affairs needs an account of the population and study limitations. Those outputs should not be treated as interchangeable.
For patients, members and caregivers
Participants have a structured way to contribute the experience that encounters may miss. Questions should be meaningful, proportionate and appropriate to the population. Explain the study purpose, who reviews submissions and whether reporting receives an individual response; a research diary is not an emergency service.
For payers and program funders
A payer-facing evidence package should connect patient experience to a defined decision question and relevant population. Include baseline characteristics, follow-up, missingness and the analysis method. Patient-reported experience can complement other evidence, but it does not alone establish comparative effectiveness, economic value or a coverage recommendation.
- Population definition
- Eligibility, enrollment dates and relevant baseline characteristics
- Longitudinal variables
- Source, units, assessment window and missing-data conventions
- Evidence limitations
- Selection, confounding and generalisability to the decision population
Workflow illustration · not a customer result or live record
What to evaluate before making a claim
Assess suitability against the research question: provenance, completeness, accuracy and relevance. Predefine the analysis rather than choosing a favorable pattern after viewing the results. Publication and payer use require appropriate scientific review.
Explore evidence and evaluationPayers & health economics
Distinguish richer patient context from evidence of value
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
Define the appraisal question
Specify the relevant covered population, decision, comparator where needed and evaluation horizon.
02
Assess data suitability
Review provenance, participation, measurement windows and missingness before examining results.
03
Build the evidence account
Combine appropriately governed patient experience with relevant clinical or utilization evidence; document assumptions and limits for expert appraisal.
For the professional team
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.
For patients, members and caregivers
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.
For payers and program funders
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.
- Decision context
- Population, appraisal question and evaluation horizon
- Suitability account
- Provenance, completeness, accuracy and relevance
- Interpretation boundary
- What the analysis can support and what remains uncertain
Workflow illustration · not a customer result or live record
What to evaluate before making a claim
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
Give the person contributing data a meaningful place in the workflow
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
Explain the purpose
Agree what the care or research program needs to learn and what participation involves.
02
Capture lived experience
Use appropriate reports alongside available observations; distinguish the patient's own answers from caregiver observations.
03
Bring context to review
Discuss a dated interval with the responsible professional, including what is missing and what matters to the person.
For the professional team
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.
For patients, members and caregivers
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.
For payers and program funders
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.
- Personal context
- The person's own priorities and dated reports
- Reporting perspective
- Patient answer or appropriately identified caregiver observation
- Review arrangement
- Who reviews reports, when and through which contact pathway
Workflow illustration · not a customer result or live record
What to evaluate before making a claim
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
Related deployment workflows
Health systems & hospitals
Connect 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 solutionPharma & biotech
Investigate disease trajectories, treatment exposure and patient experiences in real-world settings. Clarrio.ai aligns clinical, treatment and behavioral observations to support defined research questions.
See solutionRequest a demo
Explore disease, treatment and behavior together
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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