common data framework
The Common Data Framework guidance for housing related support for 2014 was developed following Sitra's consultation into the future of the Supporting People data. This version is virtually identical to the 2012/13 one.
The Common Data Framework provides a comprehensive list of data items to be collected for housing related support and other low level preventative services. The data collected provides data for commissioners, providers and service users for the following purposes:
Demonstrating the benefits of housing related support
Good quality, robust and consistent data provides valuable information about the benefits of housing related support. Capturing investment and outcomes in services helps show the difference that the investment made. Nationally consistent data enables providers, commissioners and policy makers to have a national overview of the impact of housing related support. It also enables them to see local and regional data in a national context.
Commissioning and funding strategies
Data is vital for commissioning and funding strategies. Commissioners need data to analyse need, to understand how housing related support services can meet these needs and to identify key measures of performance to be monitored. Consistency in data collection also supports commissioners to make national and local comparison of services. This is especially important for some of the client groups with which housing related support services work who move across local authority boundaries, for example, rough sleepers and victims of domestic violence.
Service performance and quality
Data is an important component of service performance and quality monitoring. It supports assessment of their services by providers and commissioners, enabling them to identify what is working and what is not. Along with service improvement tools such as the Quality Assessment Framework, it is a key element in measuring quality. Sound performance data is essential for Payment by Results contracts. Data also enables clients to understand what the service is achieving and how its quality is measured. As personalisation policies support increased client choice, a key issue will be ensuring that the data is accessible and useable for clients and their advocates who are purchasing their own services.
Making comparisons between services and learning from those comparisons can assist service improvement measures by providers and commissioners and support choice by purchasers. Robust, consistent data is essential for effective benchmarking of performance by providers and a starting point for assessing services by clients and commissioners.