OR62 President's Medal

Talk:

NHSquicker: Shaping Demand for Urgent Care through Real-Time Data and Digital Nudges

Our work aims to investigate if indirect suggestions (nudges) can support patients in need of urgent care to make more informed decisions about available healthcare choices. Our nudge is digital in nature and is delivered through the NHSquicker app. The app informs patients of alternative facilities for care that are located at a catchment-level (e.g., hospitals with A&E departments, urgent care centres [UCC] and minor injury units [MIU] that are part of the urgent care network). By combining the current wait time with travel time, the app directs users towards facilities where they may be seen quicker, so that patients can choose the appropriate type of treatment facility for their condition.

Thus, beneficially, only those with more serious needs present at the A&E, thereby reducing overall demand on the A&E facilities by redirecting less serious cases to the more appropriate facilities of MIUs/UCCs. A&E waiting times are thereby reduced. It also helps to shape demand across the urgent care network by encouraging patients to choose an appropriate destination and optimal time of visit. NHSquicker is currently live in all of Devon and Cornwall and covers parts of Somerset and Bristol. It receives real-time data from 27 centres for urgent care, including nine emergency departments

candidates:

Each candidate will give a short presentation of their applications where the judges will deliberate the winners.

Professor Nav Mustafee, 
Centre for Simulation, Analytics and Modelling (CSAM) University of Exeter Business School

Emeritus Professor John H Powell, 
Centre for Simulation, Analytics and Modelling (CSAM) University of Exeter Business School

Circuit Optimisation with Copperleaf C55 at National Grid Electricity Transmission

NGET Electricity Transmission (NGET) is the owner of the high-voltage electricity network in England and Wales. This presentation will focus on the development of a new Intelligent Bundling capability to maximise value and minimise circuit outage requirements across the network.

Copperleaf and NGET worked together to combine the power of the C55 Mixed-Integer Linear Programming (MILP) optimisation platform, Copperleaf’s consulting and software development expertise, with the engineering knowledge and prototypes that have been nurtured within NGET over many years.

The solution supports more than 60,000 assets, up to 8 different intervention types on each asset and more than 400 multi-year outage and resource constraints. To our knowledge no one else has ever solved such a problem before and organizations in the electrical transmission industry have been attempting to solve this problem since before the year 2000. A patent application for our multi-step technique is in progress. It recently won the Copperleaf 2020 Innovation Award, voted on by all Copperleaf clients globally.

Having gone live in September 2019 the new capability is already delivering significant benefit including data architecture improvements, planning efficiencies of 50%, reduction in outage costs of £6m / year, and new strategic workforce planning capabilities.

Creating new population movement insight to shape the UK Government’s response to the Coronavirus pandemic

When the UK locked down during the Coronavirus pandemic, the Government needed to rapidly understand the impact its actions were having on population mobility given this is a key driver of Coronavirus spread. It was critical to go beyond traditional modal specific data to get to an aggregate view. From first looking at Mobile Telecoms data on the day the UK went into lockdown, the Department for Transport’s Analytics Unit paused project delivery and within 2 days created a daily insights team supporting decision makers across government, including the Civil Contingencies Secretariat, devolved administrations and the NHS.

Working closely with O2, we built an agile daily insights team, streamlining our processes to meet timelines of minutes to hours. Over lockdown, the team continued to develop insights by linking this new data to existing sources and identifying connectivity between hot-spot areas, and deriving for the first time an estimate of Active travel, and a national cycling series now published weekly. The insights generated have supported Departmental and Wider Government Decision making throughout Lockdown and Restart and represent a step change in capability ensuring decision making is evidenced based and effectively monitored.