Zone Pulse

UX Research
Product Design
UX / UI Design
Information Architecture

A SaaS healthcare analytics dashboard for hospital administrators, and department heads to make data-driven decisions with real-time insights into patient flow, staff allocation, and compliance metrics. This project addresses operational inefficiencies in hospitals caused by fragmented visibility, leading to delays and compliance risks.

Background

The COO has five tabs open: bed census, ER queue, staffing, OR schedule, and incidents. “If these numbers lived on a single screen”, she tells me, “we’d stop guessing and start preparing.”
That became the brief: make the hospital’s moving pieces visible in one place and use predictions to buy teams time. Compliance officers are concerned that important safety or quality issues, such as rising infection rates or missed protocol steps, go unnoticed until an audit uncovers them. By that time, it is potentially too late, with the risk of regulatory penalties or patient harm.

Role & Deliverables

This case study delves into user research, information architecture, interaction design, and the integration of AI features. Collaborating closely with a product manager and developers, I synthesised clinical insights with technical feasibility, prioritising the accessibility and intuitiveness of complex healthcare data. Notable innovations included the development of predictive analytics to facilitate proactive management.

Primary Goal

How can we design Zone Pulse to enable Swedish healthcare leaders to foresee bottlenecks, improve bed allocation, and minimize patient waiting times?

The pivotal design decision in the process: predictive analysis with recommendations

"When I embedded micro-recommendations directly everything clicked."

Interviews & Drafting Personas

Stakeholder Interviews

Hospital Director: “We scramble when occupancy spikes, but data arrives too late.

ICU Head: “I need real-time alerts before we hit critical load.”

Compliance Officer: “Reporting is reactive—by then, it’s a crisis.” The primary goal of SwiftLogistics is to enhance operational efficiency, reduce costs, and improve decision-making in warehouse logistics.

Competitive Analysis
‍‍
Benchmarked Epic Systems, Tableau Healthcare

Key Findings
Centralised dashboards with predictive alerts are rare in Swedish systems


Personas

Eva, Hospital Director:I want a daily capacity snapshot so I can reassign resources before peak times.

Johan, ICU Head: I need instant alerts when ICU occupancy crosses safe thresholds.

Lena, Compliance Manager:: I want exportable compliance reports that auto-update with the latest data


Core Features
- Real-time bed and ICU usage with trend sparklines
- Project tomorrow’s capacity based on current trends
- Compare unit performance and staffing ratios side by side
- Critical Alert clarifications


Unique statments by users

When occupancy is trending upward, I want an alert so I can open surge capacity.”“Before shift change, I want to simulate tomorrow’s census to adjust staffing.”“Each quarter, I want a one-click compliance report to submit to regulators.”

General User Flow

Login → Dashboard (Capacity card highlights red)

Open Alerts Panel → “ICU occupancy +15% above threshold”

Click ‘Simulate’ → Model opening 5 surge beds

Review Simulation → Adjust staff schedule

What should the Dashboard have

- Capacity Snapshot
- Alerts & Insights
- Department Drill-Down
- What‑If Simulator
- Reports

Wireframes & Low-Fidelity Prototypes without AI based suggestions

Initial screens and wireframes for ZonePulse were rapidly iterated in Figma to validate design structure and user flows before finalizing visuals.

Provides an intuitive overview of bottlenecks.

Dashboard Overview (Wireframe) Top navigation bar with filters (date range, department), main grid of KPI cards, and AI insight banner below. Annotated hotspots for sparklines and alerts.

Alerts Panel (Wireframe) Sidebar listing alerts with colour blocks (Gray placeholder for each), export icon, and "Simulate" button.

Capacity Simulation
Horizontal slider control with numeric input, dynamic bar chart showing projected bed occupancy, and "Apply" and "Reset" buttons at bottom.

User Scenario using AI

Surge Response: Johan, the ICU Head, receives a red alert at 2 PM indicating ICU occupancy will exceed safe thresholds by 4 PM. He opens the Alerts Panel, runs a what-if simulation to add 5 surge beds, then adjusts staff rosters and confirms the plan via the dashboard.

Pre-Shift Planning: Each morning, Eva, the hospital director, uses the What-If Simulator to forecast department loads for the next shift. Seeing a projected spike in emergency admissions, she reallocates two nurses from general surgery, ensuring balanced staffing before the first patient arrives.

Compliance Audit Prep: A week before the quarterly review, Lena, the Compliance Manager, launches the Report Generator to export the latest compliance dashboard. She reviews flagged items, annotates sections with action notes, and shares the PDF with regulatory stakeholders—all within minutes.

Final UI Screens utilising AI-Based Suggestions

Conclusion

In this project we addressed fragmented clinician analytics for the Nordics under GDPR-aligned controls. In simulated (AI-generated) validation, task success rate rose and time-to-insight fell 71%

"Whats next: Nordic specialty benchmarks, alert subscriptions, and connections to speed up decisions at the point of care."