We provide operational managers with reliable and intuitive analysis and tools that help them plan capacity needs, track resource use and provide evidence to effect change.

We process and analyse information to enable management teams, regulators and governments to make better, evidence-based, decisions. Our approach to working with you and your data is built around three pillars of understanding: the data, the real-world context, and the outcome required. Outputs are built around compelling narratives with their foundations set in the data, and range from bespoke solutions to tried and tested tools we have developed to support operational planning.

Plan and make decisions based on robust data analysis and modelling. We help you navigate uncertainty and limited resources by developing a deep understanding of your context and opportunities for productivity. Our insights will support you make key decisions, even the toughest ones.

What We Do

01

Demand forecasting

Understand the drivers behind the observed demand to capture both unmet demand and invest wisely in the future.

02

Capacity modelling

Project the impact of changes in demand on capacity for effective future planning.

03

Bed planning and modelling

Follow patients through their journey in high time-definition for effective resource planning.

04

Workforce projections

Take stock of current workforce and build scenarios to foresee and plan for changes.

05

Theatre optimisation tools

Make the most of theatre resources by understanding how utilisation, scheduling and throughput can be optimised using data.

06

Cancer pathway management tools

Map cancer patients across the pathway to identify potential breaches well ahead of time and implement effective solutions.

07

Working with systems to plan and reconfigure services

Plan services around a clear understanding of needs and the market.

Read more about our related work and articles:

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A Data-driven Approach to Planning Radiotherapy Workforce Requirements

Edge Health partnered with Dearden HR to develop a data-driven approach for planning radiotherapy workforce requirements for the West London Surrey & Sussex Radiotherapy Operational Delivery Network, combining demand modelling, workforce analysis, and innovative strategies to address future staffing needs.

SPaedIT: Bridging the Gap in Paediatric Health Data Post-Pandemic

Edge Health partnered with the Getting It Right First Time (GIRFT) programme to develop SPaedIT, a comprehensive analytical tool that addresses the data gap in paediatric care, offering insights across eight key surgical specialties and empowering NHS providers to make informed decisions about children’s healthcare services.

Optimizing diagnosis pathways for ADHD clinics in Canada

Edge Health conducted an independent review of an ADHD diagnostic pathway for a Canadian community healthcare provider, identifying opportunities for a 13% efficiency improvement through data analysis and collaborative engagement with practice staff, potentially saving 25 hours of clinician time per 100 new diagnoses.

A Proactive Solution to Bed Configurations: Using Simulation to Challenge Narratives

Edge Health developed an interactive simulation tool for a large specialist Trust, enabling proactive bed configuration planning and challenging existing narratives on bed requirements through data-driven insights.

Improving theatre productivity with machine learning – “Space Finder”

Space Finder is our artificial intelligence solution to help operating lists run more efficiently.

System-wide Cancer Pathway Management – CanCollaborate, a tool to monitor and risk-assess PTLs

Edge Health developed CanCollaborate, a system-wide tool that allows Trusts and Cancer Alliances to monitor and risk-assess cancer patient tracking lists across multiple hospitals, enabling proactive management of complex pathways, reducing administrative time, and improving patient outcomes by facilitating joint working and early interventions.

Forecasting demand for services in secondary care

Edge Health developed a 10-year national and system-level forecast of demand for secondary care in Ophthalmology, Cardiology, and Musculoskeletal services, using machine learning techniques to create publicly available dashboards that help stakeholders understand future volumes and plan effective care delivery.

Elevating Performance and Driving Clinical Excellence: the Discharge Pathways Model Analytical Tool

Edge Health developed the Discharge Pathways Model Analytical Tool for NHSEI, a comprehensive platform that enables NHS systems to benchmark performance, identify best practices, and model scenarios for improved patient flow between secondary and community care, addressing critical questions and supporting effective planning.

“How many beds?”: Enhancing planning with bed requirement simulations