Patient Journey Analytics for Hospital Network
A hospital group had no visibility into patient flow bottlenecks, causing 4-hour average A&E wait times and bed management crises.
Team
6 data engineers + 2 healthcare analysts
Timeline
14 weeks end-to-end
Client
Hospital Group (8 hospitals)
Outcomes Delivered
48%
A&E Wait Time Reduction
22%
Bed Utilisation Improvement
$1.9M
Annual Operational Savings
How we delivered it
Integrated data from 6 source systems (EMR, bed management, staff scheduling, A&E triage, pharmacy, and lab) into a unified patient journey data model.
Built a real-time A&E operations dashboard showing current wait times, patient queue by acuity, and predicted breach times for 4-hour targets.
Developed a bed management module with predictive discharge modelling that identifies patients likely to be discharged in the next 4 hours.
Created a staff allocation tool that recommends nurse-to-patient ratio adjustments based on predicted ward occupancy.
Ran a 6-week pilot in 2 hospitals before full network rollout, validating the 48% A&E wait time reduction before scaling.
What we built
Built a patient journey analytics platform integrating EMR, bed management, and staff scheduling data into a real-time operations dashboard.
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