Developing a Register for Home Adaptations

Millions of pounds are spent every year on adapting the homes of disabled tenants. But in many cases their landlord, a housing association or local authority, has no systematic way of recording what adaptations have been made or how accessible the home is.

The result is that when an existing tenant moves out, the property may not be identified as being suitable for someone else with a disability. In many cases this means that existing adaptations are ripped out as part of the voids process and a disabled person misses out on the chance to move somewhere more suitable for them.

We worked with Leeds Beckett University and a group of Stakeholders to develop a system that landlords could adopt to record adaptations and the accessibility of their stock. The Property Register is set out over 11 screens and captures key information about a property and its location.

Adaptations Register Property Screen Screenshot

Property Information

Key features of a property are categorised and recorded so that its potential suitability for people with different abilities can be assessed.

It includes information about the garden, parking, access, heating, bedrooms, bathrooms, kitchen and location. See screenshots below for details of what information is recorded.

Matching People and Properties

Based on the information entered into the Property Register each property is ranked on the Essential, Desirable and Moderate features for the following different levels of disability:

  • Can walk independently
  • Uses a one-handed aid (e.g. a walking stick)
  • Uses a two-handed aid (e.g. a zimmer frame)
  • Needs help to walk
  • Independent wheelchair user
  • Assisted wheelchair user
  • Unable to leave bed

After selecting the appropriate level of disability, the system will sort the properties in the chosen locality by those which have the most Essential, Desirable and Moderate features. The user can also click on the property to see more details to inform the choice.

This prototype can be either used by social landlords as is, or they can use the learning to incorporate an adapted property register into their own asset management system.

Machine Learning

The original aim of this project was to gather data on adaptations held in existing Property Registers and use that to develop a machine learning algorithm that could better match people and properties and help to predict when adaptations may be required. Unfortunately, we couldn’t find landlords with sufficiently robust data to allow for machine learning.

The project was revised to develop a system to begin capturing this data for further analysis in the future.