Patients slip through the gaps between events. Vivantal reads the whole record and surfaces what no single chart shows — open loops, contradictions, and silent declines, before they become harm.
The most dangerous thing in a record is often the thing that's missing — the follow-up that never came. No standard view flags an absence. Vivantal does.
An abnormal potassium nobody acknowledged. A suspicious mammogram with no biopsy. A referral placed and forgotten. Each looks fine alone. Together, they're a pattern of preventable harm.
Equal findings, unequal action. Follow-up happens less often for some patients than others — by race, insurance, or language — and it usually goes entirely unmeasured.
Every lens reads the same longitudinal record and surfaces a different category of risk.
Walks the timeline and finds follow-ups that were never closed — unacknowledged abnormal results, incomplete referrals, imaging recommendations that went nowhere, and medications started without their required monitoring.
Measures how often an actionable finding actually gets closed for each patient subgroup — race, insurance, language, sex, age — and uses a significance test to separate a real disparity from noise.
Reads each record for internal contradictions fragmented care produces — dangerous drug interactions, a medication continued against a contraindicating lab, duplicated work-ups.
Trends each repeatedly-measured value over time and flags patients whose trajectory is sliding toward a dangerous bound — the slow decline invisible in any single result.
80 synthetic patients, realistic gaps, every lens live. No install, no account.
Vivantal speaks to two teams that rarely share a tool — patient safety and health equity — because both questions live in the same record.
Run a unit's or panel's records through Vivantal to find every open loop, ranked by severity and how long it's been open — so the riskiest patients surface first for outreach.
Audit closure rates across race, insurance, language, sex, and age. See, with a significance test, whether a subgroup's findings are acted on less often than the best-served group's.
Use the ranked roster as an actionable outreach list, or use the cohort-level statistics to study where and for whom care processes break down — all from de-identified data, in the browser.
Take a real-looking record: years of visits, labs, imaging, and referrals. Most of it is fine. Vivantal pulls out only the loops left open — and links each to the exact event so a clinician can confirm it in seconds.
| unacknowledged_result | A high calcium of 12.9 was resulted and never acknowledged — possible hypercalcemia left unworked. |
| imaging_followup_open | A mammogram read "BIRADS 4 — biopsy recommended." No biopsy is on file. |
| missing_med_monitoring | Amiodarone was started; it requires TSH monitoring, and no TSH has been drawn since. |
| referral_incomplete | A cardiology referral was placed 596 days ago and is still open — the patient may never have been seen. |
No model, no black box. Every finding comes from a named rule or an explicit statistic you can check by hand.
Use the synthetic demo cohort, build a patient by hand, or load your own already-de-identified records. Everything stays in your browser.
Vivantal assembles each patient's events into one longitudinal record — labs, imaging, referrals, medications, vitals.
Four deterministic engines scan the record for open loops, contradictions, subgroup disparities, and deterioration trends.
Each finding links to the exact event behind it, so a clinician can verify it in seconds and export a worklist.
| unacknowledged_result | An abnormal or critical lab result with no documented acknowledgement in the record. |
| imaging_followup_open | An imaging study whose report recommends follow-up that never occurred. |
| referral_incomplete | A referral placed but never completed, ranked by how long it's been open. |
| missing_med_monitoring | A medication started without the lab monitoring it requires (e.g. warfarin without INR). |
| closure rate | For each subgroup, the share of actionable findings that actually got closed. |
| two-proportion z-test | Compares each group to the best-performing one; surfaces gaps unlikely to be chance. |
| four-fifths rule | Flags any group closing at under 80% of the reference rate — a standard disparity threshold. |
| min-N guard | Cohorts too small for a reliable signal are reported honestly as "not enough data," never as false headlines. |
Open loops surfaced from each record — abnormal results never acknowledged, referrals never completed, medications started without their required monitoring. Sorted so the patients most likely to have fallen through the cracks rise to the top.
Equal findings should get equal action. This audit measures, for each subgroup, how often an actionable finding gets closed — then compares each group to the best-performing one. A gap that survives a significance test is a disparity worth investigating, not noise.
Fragmented care produces conflicts no single clinician sees: interacting medications, a drug continued against a lab that contraindicates it, duplicated work-ups. This lens reads each record and surfaces those contradictions for a pharmacist or clinician to resolve.
A value that moves from normal toward danger across several visits is invisible in any single result. This lens trends each repeated measurement and flags the patients whose trajectory is heading the wrong way — before it becomes a crisis.
Add events one at a time — a lab, a referral, an imaging study, a medication. Each becomes a row. When the record is built, analyze it directly or export it to load into the cohort tools.
Pick a type, fill the fields, add it to the record.
Protecting patient data isn't a policy we promise — it's an architecture we can't violate. Here's exactly how, in plain terms, and the rules we hold ourselves to.
Protected health information is never compromised. Vivantal does not receive, store, or transmit identifiable patient data — ever. There is no server in our analysis pipeline to send data to. Everything runs in your browser, on your machine. You can't leak what you never receive, and we never receive it.
The entire engine is JavaScript running inside your browser tab. Records you load are processed locally and never sent anywhere. Disconnect from the internet entirely and Vivantal still works.
Vivantal is designed for data that's already de-identified. A separate, open converter — which runs on your machine, never ours — removes the 18 HIPAA Safe Harbor identifiers before any record reaches the app.
No analytics, no trackers, no third-party scripts, and nothing stored about you or your data between sessions. Close the tab and nothing persists.
Because Vivantal is deterministic and open, anyone can verify these claims: open your browser's network tab and watch zero data leave the page. Nothing hidden in a model or a server you can't inspect.
Vivantal started from a simple conviction: the most preventable harm in healthcare hides in the gaps between events, and you can make those gaps visible without a black box.
Vivantal today is a working, validated prototype on synthetic data. The path forward is real: validating the open-loop rules with clinicians, testing the method on de-identified institutional data under review, and adding lenses onto the same spine. The goal is a tool quality and equity teams reach for, then trust.
Signed in. Your settings and audit history live on this device.
Tune the engine to how your practice works. Changes apply immediately to the next analysis. These are preferences, not patient data — nothing here is PHI.
Override the high/low bound for a specific test — for example, flag HbA1c high at 7.0 instead of the lab's default.
Wipe your account, settings, and audit history from this browser. Use this on a shared or public computer when you're done. This can't be undone — you'll need your recovery phrase to get back in elsewhere.
A timestamped record of every audit you've run — counts only, never patient data. This is the evidence a clinic shows its insurer or regulator to prove gaps are being actively monitored.
Invite your staff so everyone processes records against the same clinical thresholds. Membership and shared settings are non-PHI; patient data still never leaves each person's own machine.
Seats on this plan: 5. In a hosted deployment, invites email a sign-up link; here they're added directly for demonstration.
Produce a branded, timestamped PDF summarizing your audit activity — the document a clinic hands to HHS or its malpractice insurer. Built entirely in your browser from metadata only.