ProvidEHR
Population health

The clinical counterpart to a personal prevention layer.

Public health sets the priorities. Primary care handles medical accountability. A personal companion like InVivo helps people generate useful daily evidence and follow low-cost prevention plans. ProvidEHR is the governed record and population-health layer that receives it — turning behaviour into care without becoming a diagnosis engine.

Public healthsets the priorities
Primary careholds accountability
InVivogenerates the evidence
ProvidEHRrecord + cohorts

InVivo is the personal prevention layer; ProvidEHR is the governed clinical record and population-health counterpart it reports into.

Personal loop · Between visits · InVivo

Daily evidence, small actions

Risk forms every day, but the system sees people once a year. A personal prevention layer like InVivo helps people capture meals, sleep, readings and labs, follow low-cost plans, and prepare for care — without diagnosing or prescribing.

Clinical loop · Primary care · ProvidEHR

A scoped packet, not a data dump

What changed, what was measured, what's missing, what was tried, adherence and burden, and questions for review — composed into a concise, source-cited packet that lands in the governed clinical record for clinician attestation.

Population loop · Health systems · cohorts

Consented, aggregate-safe learning

Which low-cost interventions people actually complete, which groups aren't engaging, which plans improve markers without adding burden — reported as small-cell-suppressed, consented cohort learning, never individual surveillance.

Twin fidelity tiersConsent-scoped sharingSmall-cell suppressionClinician packetsAssignable prevention tracksOutcomes over engagement
Prevention intelligence

The best models for prevention — governed, on one record.

Not a chatbot and not a single model: a governed, multimodal early-signal engine. The strongest published models for wellness, prevention and population health surface early, source-cited risk on the patient twin — anchored on the AHA PREVENT protocol, with a sharp focus on the earliest signals of heart disease — and the prevention loops act on it under attestation, consent and audit.

Anchor

PREVENT risk engine

AHA PREVENT 10- and 30-year risk for ASCVD, heart failure and total CVD — cardiovascular-kidney-metabolic aware, the backbone of the 2026 CKM guideline.

Heart disease

AI-ECG early warning

Asymptomatic low ejection fraction and atrial fibrillation read from a single- or 12-lead ECG, before symptoms — the earliest structural signal.

Heart disease

Oculomics

Cardiovascular risk and major adverse cardiac events predicted from a retinal photo — non-invasive, suited to population-scale screening.

Between visits

Wearable PPG signals

Phone-camera and wearable photoplethysmography from InVivo → continuous AF screening, blood-pressure estimation and cardiovascular profiling.

Between visits

Cardiac nudge → clinician review

An on-device ECG finding from InVivo (QTc, ST-T, wide-QRS) arrives as a source-cited, consent-scoped packet in the cardiology review inbox — ProvidEHR decides whether to surface or escalate. Decision support from a single-lead wearable, never an autonomous alarm.

Between visits

Voice biomarkers

A 30-second voice capture surfaces a coronary-risk signal and tracks heart-failure congestion — earlier and more sensitively than daily weights.

Heart disease

Integrated genomic risk

A coronary polygenic risk score fused with PREVENT reclassifies younger and intermediate-risk patients the clinical score alone would miss.

Population health

Multimodal population model

A foundation model fuses every signal with the record and social determinants for cohort risk stratification and the next best action across the panel.

The flywheel

Closed-loop calibration

Every prediction is linked to what actually happened. Each model's calibration and discrimination are measured on your own population — per subgroup — drift is detected, and a governed recalibration is applied, so a risk shown to a clinician means what it says, here.

Care reflexes

Prevention K-lines

When a care pathway repeatedly improves outcomes for a given risk signature — proven on your own population through the intervention ledger, not prediction alone — it is promoted under governance into a certified reflex: the next matching patient surfaces the validated plan instantly. Procedural memory for prevention. A clinician still accepts every time; stale reflexes are retired.

The moat

Governed by design

Every model output is source-cited, confidence- and subgroup-gated, consent-scoped and clinician-attested before it touches the record. Decision support, never autonomous diagnosis.

Research-grounded and rolling out under clinical governance. Each model is a swappable, intended-use-labelled provider behind one signal interface — best-of-breed today, upgraded as the science moves. And because every prediction is linked back to the outcome and recalibrated on your population, the platform gets measurably better over time — and can prove it. Models inform clinicians; they never act autonomously.

Anecdote falsification

Patient-led experiments become governed prevention evidence.

InVivo Experiments turns wellness folklore into pre-specified, randomized, safety-screened n-of-1 trials. ProvidEHR turns those patient-led experiments into governed prevention evidence: consented, source-grounded, federated, and linked to clinical outcomes — without centralizing raw personal data.

01

Consented

Each claim is a distinct, withdrawable opt-in. Because experiment data can touch care, linking results to the clinical record is a separate consent beyond general research uploads.

02

Source-grounded

Every reading carries time, source, method, confidence, and consent scope; baseline labs or validated scores anchor the endpoint — auditable evidence, not self-reported anecdote.

03

Federated

Phones compute each person's effect locally and contribute only secure-aggregated summaries — never raw readings — with small-cell suppression before anything is reported.

04

Governed verdict

An inverse-variance cohort estimate is judged against a pre-specified minimum worthwhile effect, with adverse-event stop rules and a strict supported / not-supported / subgroup / inconclusive vocabulary — never 'proved'.

05

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.

ProvidEHR can say which patient-led experiments helped, which did not, and when burden or risk outweighed benefit — preserving privacy throughout. Experiments that change prescribed therapy are clinician-directed, never self-started. That boundary — wellness and clinician discussion — is part of the evidence.