1771 Provision of Risk Stratification Algorithms Tool For NHS Arden and GEM CSU

Description

NHS Arden & GEM CSU seeks competitive offers for the supply, installation, support, and maintenance of Risk Stratification Algorithms within a Tool able to cover a population of 3.3 million patients.<br/><br/>The Risk Stratification Algorithms/Tool must meet the following key requirements:<br/>Have a proven evidence base and be rigorously tested using standardised statistical metrics and support repeatable results from the same data set.<br/>Be continually updated and supported to reflect changes in clinical practice and patient behaviour.<br/>The tool should have had experience of operating in the NHS and with associated NHS data flows or equivalent.<br/>Must be predicated on clinical evidence including a combination of prescription, diagnosis, and event data rather than purely historical financial spend in secondary care. Lot 1: NHS Arden & GEM CSU seeks competitive offers for the supply, installation, support, and maintenance of Risk Stratification Algorithms within a Tool able to cover a population of 3.3 million patients.<br/><br/>The Risk Stratification Algorithms/Tool must meet the following key requirements:<br/>Have a proven evidence base and be rigorously tested using standardised statistical metrics and support repeatable results from the same data set.<br/>Be continually updated and supported to reflect changes in clinical practice and patient behaviour.<br/>The tool should have had experience of operating in the NHS and with associated NHS data flows or equivalent.<br/>Must be predicated on clinical evidence including a combination of prescription, diagnosis, and event data rather than purely historical financial spend in secondary care.<br/>Be able to utilise, as a minimum, acute, and primary care data records as a basis for its stratification<br/>Use multiple years of data to support a longitudinal record which can be updated on an automated basis by AGCSU.<br/>The Risk Stratification Tool must have a range of predictive models with ability to include as a minimum:<br/>Current and predicted costs.<br/>Predicted resource utilisation.<br/>Risk of hospitalisation.<br/>The algorithms within the tool must be able to factor in sufficient historical data to enable the clinical evidence-base of the tool, including historical diagnosis of long-term conditions and support and provide disease profiling. It should capture the multidimensional nature of an individual’s health.<br/>The Risk Stratification algorithms must be able to be housed and run within the AGCSU data management environment to maintain our data controls and governance and allow it to be augmented by other data elements managed by the customer. All outputs of the tool must be programmatically readable, must output validation to measure success of the processing and use a server-based technology not a desktop to enable flexible and secure working.