Time for You Care: Helping to solve the bed blocking crisis

Bellrock Technology took Time for You (TfY) Care from initial engagement to a production solution in less than 7 days. Delivering an AI powered application to allow them to streamline and monitor their network of carers and ensure their customers are receiving the correct level of service.

Azure

SQL Server Database

Health

Python

Company overview

Bed blocking is a serious issue across the UK, with thousands of people trapped in hospital because they cannot be cared for in their own home.  In addition, Age UK estimate that over 1.4 million elderly people who required help with basic tasks such as getting out of bed, washing, dressing and meal preparation cannot get access to these services.

The challenge

Time for You (TfY) Care is an innovative care provider who recognises that the main barrier to solving the bed blocking crisis is the lack of available people willing to be carers.  The most significant reason for this is the low rate of pay.

To change this TfY Care is paying carers 20% more than the industry norm but charging the end customer no more.

How do they do this? By ensuring that they run a highly efficient business which uses technology and data to great effect.

“When you are caring for hundreds of people, all in different locations we really need a constant awareness of everything that is happening and in real-time” stated Melissa Singh, CEO of Time for Your Care, “this is a massive administrative overhead on the business.”

The solution

Using Lumen, Bellrock Technology rapidly developed connections to all TfY Care’s sources of information, developed analysis to interpret the business impact and presented them to the control hub in real-time, substantially reducing the resources required to manage this work.

“The ease and speed at which Lumen turned our ideas into a working solution was amazing” said Melissa “Now we are working with Lumen, we are not only more effective and efficient, but we have even stronger control over our quality of service.”

“Now we have seen what Lumen can do, we are already expanding its application to help transform other areas of the business” added, Katie Hardman, TfY Care Operations Manager.

The Model

The model is written in Python and using the data from TfY Care system looks to check and validate this. The model will highlight where the data suggests there is a discrepancy with the location data and the data from the carers.

The Application

The application was designed to present the results and any discrepancies in a clear and accessible fashion for the TfY management team, with the application being put up on a monitor within the head office. The application shows a live feed of each carer and confirms when their location and timing matches that of the schedule and highlights in red any discrepancies, where the information does not match. This allows the management the information needed to easily identify areas requiring action.

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