InVivo turns personal tracking into measurable population-healthspan value.
The population-health opportunity is a consented loop: source-grounded events, modality-focused UX, source-fidelity SleepInsight recovery evidence, preventable transition models, governed low-cost interventions, CarePlan packets, Triager handoffs, measured outcomes, economic endpoints, and honest safety boundaries.
metabolic, cardio, recovery, inflammation, function
every declared intervention has a measurable protocol
packets, handoff, compliance, outcome review
sleep/wake, acoustic, recovery, uplift, metabolic response
iOS Twin readiness plus Android domain parity
minimum cohort cell before aggregate display
Source-grounded health events
Every signal can carry time, source, method, confidence, privacy class, consent scope, and source receipt metadata so population models are built from auditable evidence instead of unstructured wellness notes.
Preventable transition models
InVivo models transitions that can be prevented or delayed: worsening metabolic recovery, cardiovascular marker momentum, SleepInsight recovery debt, persistent inflammation context, and functional decline.
Governed intervention loops
The native model layer implements measurable protocols with eligibility, required inputs, preferred inputs, burden, cost, measurement windows, prohibited-use withholding, and aggregate-safe reporting.
CarePlan follow-up evidence
Standards-backed CarePlans now become consent-scoped Clinician Packets: included, withheld, stale and missing evidence; source receipts; Triager handoff context; observed effects; and reviewable signals for how a plan may need clinician review.
SleepInsight recovery evidence
Sleep becomes a source-grounded nightly recovery event: source fidelity, sanity validation, user corrections, breathing-load boundaries, HRV/resting-heart-rate context, and derived-feature cohort eligibility.
Cohort learning with consent
Individuals get personal feedback while consented cohorts can reveal which low-cost actions work, where data is missing, and which groups need better measurement before stronger claims are made.
Cost and utilization endpoints
Population value is measured through avoided duplicated labs, completed follow-up, lower user burden, clinician minutes saved, low-cost intervention adherence, and healthier daily function.
Privacy-preserving boundaries
Population reporting is aggregate-safe, small-cell suppressed, consent-scoped, and explicit about what remains personal, what can be shared, and what is never diagnosis or medication advice.
Model preventable transitions, not abstract wellness.
The current implementation focuses on five healthspan model families and ties every declared intervention to measurable assignment, adherence, outcome, and reporting contracts.
Metabolic deterioration
Transition: Stable metabolic pattern -> poor glucose recovery or higher-risk lab band
post-meal walking, earlier dinner, DPP-style prevention packet
glucose recovery, lab anchors, adherence, cost per improved risk state
Cardiovascular momentum
Transition: Stable marker pattern -> unmanaged BP, lipid, glucose, or recovery momentum
home BP plan, lipid packet, follow-up preparation
duplicate tests avoided, clinician minutes saved, marker drift prevented
Recovery capacity
Transition: Stable recovery -> SleepInsight recovery debt, lower adherence, or fewer functional days
sleep regularity, strain budget, meal cutoff, wind-down plan
source-fidelity sleep timing, HRV/resting HR, correction rate, healthy functional days
Inflammation context
Transition: Weak context -> persistent abnormal marker pattern needing clinician discussion
repeat-lab packet, symptom timing, recovery-load review
unnecessary worry/testing avoided while preserving escalation
Function and frailty prevention
Transition: Stable function -> mobility decline, lower strength reserve, or falls context
strength habit, protein adequacy, walking consistency, mobility check
functional days preserved and avoidable decline reduced
Eleven protocols make the portfolio assignable and reportable.
Post-meal walking keeps the deepest glucose-specific outcome scoring; the full suite adds structured eligibility, SleepInsight recovery endpoints, CarePlan activity assignment, consent-scoped Clinician Packets, stale or withheld evidence, Triager handoffs, prohibited-use withholding, follow-up assessment, and small-cell-suppressed cohort reports across all five model families.
Eligibility
Check source coverage, protocol-specific required inputs, missing preferred inputs, readiness, and prohibited medical-use triggers before assigning a pilot.
CarePlan assignment
Select a declared protocol or standardized CarePlan activity with an action label, measurement window, required source context, and safety boundary.
Compliance evidence
Capture completion, burden, source count, SleepInsight correction labels, Clinician Packet readiness, stale or withheld evidence, and safety handoffs rather than assuming a recommendation was followed.
Outcome window
Measure response using predefined endpoints such as glucose recovery, BP coverage, SleepInsight sleep regularity, packet follow-up, functional days, duplicate testing avoided, or CarePlan goal movement.
Aggregate learning
Report only cohort-safe counts, adherence, missingness, response distribution, burden, economic endpoints, and plan-modification hypotheses with small-cell suppression.
Post-meal walk
meal adherence and 30/60/120-minute glucose response
Earlier dinner
overnight recovery, morning glucose or ketone context
DPP-style prevention
packet review, activity minutes, weight/waist or lab follow-up
Home BP tracking
reading consistency, source provenance, follow-up readiness
Lipid clinician packet
clinician review, duplicated tests avoided, source-document utility
Sleep regularity
source-fidelity sleep timing, HRV/resting HR, correction rate, recovery debt, functional-day reports
Strain budget
accepted suggestions, correction rate, next-day recovery
Repeat-lab context
repeat-lab completion, escalation preserved, duplicated explanation avoided
Recovery-load review
symptom resolution, recovery movement, lab-anchor timing
Strength habit
session adherence, walking consistency, soreness, functional-day report
Mobility check
mobility-check completion, walking trend, escalation completion
Patient-led experiments become governed prevention evidence.
InVivo Experiments turns wellness folklore into pre-specified, randomized, safety-screened n-of-1 trials. ProvidEHR consents, source-grounds, and federates the results — so a claim collapses or refines on evidence, without centralizing raw personal data.
Pre-specified
Hypothesis, population, exclusions, endpoints, and minimum worthwhile effect are fixed before the first day of data.
Federated, not centralized
Phones compute personal effects and contribute only secure-aggregated summaries — federated analytics first, learning second.
Stricter verdicts
Supported, falsified, not-supported-in-cohort, subgroup signal, inconclusive, or stop — never the word 'proved'.
Clinically linkable
Promoted to clinical-grade only with a pre-registered protocol, CONSORT-style reporting, external validation, and clinician review.
ProvidEHR turns patient-led experiments into governed prevention evidence: consented, source-grounded, federated, and linked to clinical outcomes.
Consented
Each claim is a distinct, withdrawable opt-in under research consent — and because experiment data can touch care, clinical linkage is a separate consent beyond general uploads.
Source-grounded
Every reading carries time, source, method, confidence, and consent scope; baseline labs or validated scores anchor the endpoint, so the evidence is auditable, not self-reported anecdote.
Federated
Phones compute each person's effect locally and contribute only secure-aggregated sufficient statistics — never raw readings — with small-cell suppression before anything is reported.
Governed verdict
An inverse-variance cohort estimate is judged against a pre-specified minimum worthwhile effect, with adverse-event stop rules and the stricter supported / not-supported / subgroup / inconclusive vocabulary.
Linked to outcomes
Promotion to clinical-grade requires pre-registration, CONSORT-style reporting, external validation, and clinician review — then the verdict can inform CarePlans and is tracked against real care outcomes.
Who it serves
Health systems and research partners get consented, source-grounded prevention evidence instead of influencer claims — with explicit missingness and subgroup calibration.
What stays private
Raw observations never leave the phone. Only masked summaries are aggregated, and small cells are suppressed, so no individual experiment is exposed.
Where it stops
Experiments that change prescribed therapy are clinician-directed, never self-started. The boundary — wellness and clinician discussion — is part of the evidence.
ProvidEHR can say which patient-led experiments helped, which did not, and when burden or risk outweighed benefit — preserving privacy throughout. That is governed evidence, not wellness content.
See the falsification engineThe product boundary is part of the value.
InVivo can support population-health learning without turning the app into a diagnosis, prescribing, or surveillance system.
CarePlan follow-through
Identify which standardized plans produce measurable follow-through, which evidence is ready for a Clinician Packet, which tasks need handoff, and where escalation is preserved.
Source-grounded plans
Run consented observational pilots with explicit missingness, device tier, standards evidence, subgroup calibration, and outcome-window capture.
Aggregate value
Evaluate CarePlan packet readiness, compliance, burden, avoided duplicate testing, functional days, and privacy-safe cohort summaries.
Personal utility first
Keep insight useful while packaging source receipts, medicine context, and clinician questions when care review is needed.