ShippedHealthcare AIRemote Monitoring
// build study

VitalLoop

An AI remote patient monitoring platform that triages home vitals into a prioritized care queue, drafts patient outreach, and tracks billable RPM minutes.

Client:Chronic-care management group (NDA)
Duration9 weeks
ScopeMVP product design and front-end build of the Care Queue triage board and single-patient detail experience, backed by a deterioration-risk scoring model and an outreach-drafting engine.

// The Care Queue board — 486 patients monitored, 1,204 readings ingested today, a worst-first queue by risk tier, and 8,940 billable RPM minutes.

// the numbers

Figures from the engagement, shared under NDA.

We publish them unchanged and can’t break them down any further here. The reference build you can open runs entirely on sample data.

486Patients monitored
1,204Readings today
23Open alerts
8,940Billable RPM minutes
01In brief

If you read one part of this page, read these 4 lines.

  • Catches early decompensation from home readings before it becomes an admission
  • Ranks the whole panel into one worst-first care queue for the nurse
  • Every alert is explainable — a weighted breakdown, not a black-box score
  • Drafts patient outreach and tracks every billable RPM minute in one place
02Overview

What it does — and which part of it we built.

VitalLoop gives a chronic-care team an always-on view of patients they only used to see at appointments.

Patients take blood pressure, glucose, weight, SpO₂ and heart-rate readings at home on connected devices; VitalLoop ingests every reading, triages abnormal trends into a worst-first care queue, and explains each risk score with the weighted drivers behind it. BuildspaceLabs designed and built the MVP front end — a population Care Queue for triage and a per-patient detail view with 30-day vitals sparklines, a weighted AI risk assessment and a drafted outreach message — turning a stream of device data into a workflow a nurse can act on in minutes, while every qualifying RPM minute is logged toward billing.

03The screens

Every screen here is from the reference build, not the client’s system.

The captions say what you are looking at. Every name and record on them is sample data.

04Outcomes

What the engagement left the client with.

  • Delivered a production-quality MVP of the Care Queue and patient detail view in a 9-week engagement
  • Consolidated reading ingestion, triage, outreach and RPM billing into a single care-team workflow
  • Gave nurses a worst-first queue with explainable risk drivers instead of an undifferentiated inbox
  • Established a reusable clinical design system (risk pills, vitals sparklines, care-action cards) for the product's next surfaces
05How it is built

The stack was picked per constraint, not per house habit.

7 technologies across 4 layers — the shape of the stack follows the problem.

AI & ML
Python · risk model
Frontend & Mobile
Next.jsReactTypeScript
Data & Infrastructure
PostgreSQL
Backend & APIs
FastAPIHL7 FHIR
Every feature in the build (6)
  • Care Queue board with live readings, open alerts, and billable RPM-minute KPIs
  • AI triage that scores every trend and ranks patients into Critical, Elevated and Stable tiers
  • Per-patient detail with 30-day blood pressure, glucose and weight sparklines
  • Explainable deterioration-risk score attributed to weighted drivers (weight, BP, adherence, missed readings)
  • AI-drafted patient outreach — a message or call script the nurse approves before it sends
  • RPM billing tracker logging every qualifying minute toward the 20-minute threshold per patient
// see for yourself

Don’t take our word for it — it is running in the frame below.

This is the same page the provenance block links to: our reference build for VitalLoop, with its own look, copy and motion. Scroll inside it, or open it full-screen.

// more from the lab

A team that ships across the board.

36products in production
8industries served
68+technologies in play

Closest to VitalLoop

// next

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