AI-Enhanced Clinical Deterioration Dashboard

Predictive Risk Visualization Concept for ICU Settings

Context

This is a research-driven product concept exploring how predictive modeling and explainable alerts could improve ICU workflows. The work is based on academic literature, public clinical studies, and industry examples. No hospital deployment was conducted.

Problem

ICU environments generate excessive static alarms. Research shows:

  • 50+ alarms per shift in some units
  • High false-positive rates
  • Alert fatigue among nurses
  • Limited explanation behind triggers

Clinical staff often react to alarms rather than proactively managing risk.

Opportunity

  • Shift from reactive alarm systems to prioritized, explainable risk visibility.
  • Move from threshold-based alerting to probability-based forecasting.

Concept Solution: AI Clinical Risk Dashboard

A real-time clinical risk dashboard that continuously calculates patient deterioration probability, explains contributing clinical factors, visualizes short-term risk trends, and forecasts ICU capacity pressure.

Key Features

  • Real-Time Risk Probability
  • Ranked Contributing Factors
  • 24h Risk Trendline
  • Predictive Occupancy View

Research Foundation

Grounded in literature across:

  • Alarm fatigue studies in ICU settings
  • Systematic reviews of Early Warning Systems
  • Research on ML-based false alarm reduction
  • Explainable AI methods in healthcare

Selected References

Design Decisions

  • Probability over static score categories
  • Contributor tags prioritized over generic alerts
  • Trend visualization for context
  • Dark-mode UI for night shift use

Expected Impact

  • Reduced cognitive overload
  • Improved trust in predictive alerts
  • Faster risk prioritization
  • Better ICU capacity planning

* These outcomes are projected from literature, not measured in deployment.

Strategic Relevance

Demonstrates ability to translate academic AI research into practical clinical UX. Focuses on explainability, workflow integration, and decision clarity.

↓ Live Interactive Dashboard Below ↓

AI-Powered Clinical Deterioration Early Warning

3
High Risk Escalation Required
Anna Kowalski

Anna Kowalski

68 | Room 312

Admitt: Pneumonia

Risk Score
82
8 hours Now

Key Contributors

  • Elevated lactate level: 2.9 mmol/L (high)
  • Sustained tachycardia: 124 bpm
  • Falling oxygen saturation: 90% 87%

Patient Risk Scores

All Units
Patient Age Room Risk Score Change
Helen M.
Sepsis
52 yrs
Room 202
76 4
High 4
John L.
Post-Op
59 yrs
Room 121
68 5
5
Mark R.
COPD
47 yrs
Room 318
45 3
3
Sarah P.
CHF
64 yrs
Room 214
36 4
4
Lucas I.
Obs
53 yrs
Room 415
30 0
Stable

Ward Risk Levels

Ward A
Ward B
Ward D
Ward C
  • Surgery 4 patients High
  • Cardiology 2 patients Moderate
  • Internal Medicine Moderate
  • SpO₂ 87% Low

ICU Demand Forecast

Currently 6
08:41 AM Sarah P: was escalated by physician.
08:32 AM Adjustment in lactate levels detected for Anna K.
08:17 AM Mark R: was acknowledged by nurse Alice S.

ICU Demand Forecast

Currently: 6 (of 20)
In 18 hours: Expected 14 (of 20)
Department
Surgery
High 4
Cardiology
Moderate - 5
Internal Medicine
Moderate - 1
Neurology
0
View All

ICU Resource Forecasting

Staff On Duty
3:3 avg: patients per attend.
Available Ventilators
7 of 12 in use
Available Beds
6 of 20 occupied

Audit Log

Sarah P. was escalated to physician.
Adjustment in lactate levels detected.
Helen M. risk score increased from 75.6%