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LOTI works on homelessness data tool


Mark Say Managing Editor

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Homeless person sleeping on bench
Image source: Hudson

The London Office for Technology and Innovation (LOTI) is working on the development of a data tool to support efforts to sharply reduce the number of homeless people in the capital.

It said the project is aimed at helping strategic decision makers understand the pathways into and out of rough sleeping.

The project has been outlined in a blogpost by LOTI programme manager Jay Saggar, who said it has used outcomes defined by the mayor of London’s Life off the Streets programme and a user journey mapping exercise involving rough sleeping leads and practitioners from London boroughs.

Bloomberg Associates have been leading the curation of the minimum dataset, and initially the tool will include data from the Combined Homelessness and Information Network (CHAIN), boroughs’ Homelessness Case Level Collection (H-CLIC) returns and from hostel providers stored in the In-Form case management system.

A draft version of the minimum dataset include demographic and personal details, information on past contact with institutions such as housing offices and the armed forces, assessments of current needs, engagement on rough sleeping and temporary accommodation.

Individual records will be linked by the outputs but anonymised and aggregated for the strategic use cases. LOTI is also working with information governance leads from London’s boroughs and hostel providers to ensure the data is shared responsibly and legally.

Four pilots planned

Saggar said that LOTI expects to deliver a minimum viable product in July for pilots in four boroughs – Camden, Lambeth, Hillingdon and Westminster – and that if these prove successful it will aim to onboard the remaining boroughs through the rest of the year.

“Our intention is to create a tool that ingests and presents data in a way that enables strategic decision makers working on tackling rough sleeping in London to have deeper insights into the pathways into rough sleeping and effectiveness of various interventions,” he said, adding that once the initial product is live LOTI hopes to add more datasets.

“There is also an opportunity to build a data science capability that can perform more sophisticated analysis,” he said.

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