Custom product & infrastructure

Point-of-Care Protocol Decision Workflow

A lightweight clinical workflow built to guide protocol decisions at the moment of care, without requiring a heavy web app shell or platform dependency.

Clinical protocol workflow

Clinical Compass guided protocol workflow showing progressive steps and structured clinical decision branches.

Progressive disclosure

Protocol steps revealed only when relevant

JSON-backed

Clinical pathways modeled as structured branching content

Static embed

Workflow can be delivered inside other sites without an app shell

Project snapshot

Before, build, and operating change

A lightweight view of the problem, the intervention, and what changed after the system shipped.

Before / Problem

  • Protocol guidance lived more like reference material than an in-flow decision tool, so users had to interpret the next step themselves
  • Long-form content exposed too much too early, making it harder to navigate the right branch in the moment of care

Build / Fix

  • Progressive-disclosure decision flow

    The protocol was rebuilt as a step-by-step decision workflow that only reveals the next relevant branch when a user makes a choice. Instead of scanning a dense page, clinicians move through one decision at a time.

  • JSON-backed pathway model

    Branching logic, pathway labels, and decision content were modeled in JSON so the workflow could be maintained as structured content instead of rewriting front-end logic for every protocol update.

After / Outcome

Instead of interpreting dense protocol content or jumping between references, clinicians get one guided decision path at a time. The workflow is easier to embed, easier to maintain, and clearer to use in context than a heavier application or a static document.

Constraints handled

  • Needed to work as a static embeddable workflow, not a full app
  • Had to keep branching logic maintainable in structured data
  • Needed point-of-care clarity without exposing the entire protocol at once

Why it mattered

When clinicians have to interpret protocol logic from static documents or training memory, the next step becomes slower, less consistent, and harder to use in the real context of care. The job here was to turn protocol knowledge into a guided workflow that remains fast, portable, and easy to maintain.

What was broken

  • Protocol guidance lived more like reference material than an in-flow decision tool, so users had to interpret the next step themselves
  • Long-form content exposed too much too early, making it harder to navigate the right branch in the moment of care
  • The workflow needed to be embeddable in static environments, which ruled out a heavier app-style implementation
  • Content updates needed to happen in structured pathway data, not in brittle hardcoded UI branches

What was built

01

Progressive-disclosure decision flow

The protocol was rebuilt as a step-by-step decision workflow that only reveals the next relevant branch when a user makes a choice. Instead of scanning a dense page, clinicians move through one decision at a time.

02

JSON-backed pathway model

Branching logic, pathway labels, and decision content were modeled in JSON so the workflow could be maintained as structured content instead of rewriting front-end logic for every protocol update.

03

Static embed-anywhere delivery

The runtime was built with vanilla HTML, CSS, and JavaScript so the workflow could be embedded into static environments and shipped without framework overhead or application hosting complexity.

04

Low-friction protocol UX

Interaction patterns were tuned for clarity and speed: simple branching controls, persistent context, and copy written for the point-of-care moment rather than for general product marketing.

Supporting visual

Clinical Compass protocol summary screen with progressive-disclosure pathway output.

Protocol summary screen

Operating impact

Instead of interpreting dense protocol content or jumping between references, clinicians get one guided decision path at a time. The workflow is easier to embed, easier to maintain, and clearer to use in context than a heavier application or a static document.

SYSTEMS INVOLVED IN THE BUILD

The tools and system layers that made this project work — grouped by what they contributed.

Documented implementation layers

  • Progressive-disclosure protocol UI
  • JSON-backed pathway architecture
  • Vanilla HTML/CSS/JS runtime
  • Static embed delivery
  • Structured content-driven branch logic

Case study angles

What this project demonstrates

Each block names the capability first. Figures below are supporting context from the same engagement — not the headline.

  • Point-of-Care Protocol Routing

    The protocol was turned into a guided decision path so clinicians could move one step at a time instead of interpreting a dense static reference at the point of care.

    Referenced outcomes (same engagement)

    Only the next relevant protocol step is shown
    Progressive disclosureOnly the next relevant protocol step is shown
    One guided pathway instead of dense document scanning
    Single flowOne guided pathway instead of dense document scanning
  • JSON-Backed Pathway Architecture

    Branch logic and content live in structured JSON so updates happen in pathway data instead of hardcoded UI branches, keeping the workflow maintainable.

    Referenced outcomes (same engagement)

    Branching content modeled outside the UI
    JSON-backedBranching content modeled outside the UI
    Protocol changes do not require UI rewrites
    MaintainableProtocol changes do not require UI rewrites
  • Static Embed Delivery Model

    Built with vanilla HTML, CSS, and JavaScript so the workflow can be embedded anywhere without a framework runtime or app-shell dependency.

    Referenced outcomes (same engagement)

    Deployable inside lightweight environments
    Static embedDeployable inside lightweight environments
    No heavy framework dependency required
    Vanilla JSNo heavy framework dependency required

Related build types

Similar project shapes and delivery patterns — useful when you are comparing system fit, not client names.

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