Surrey health and social Care Analytics Linked Ecosystem (SCALE): Visualising patterns of need and care
This project will develop a joint approach to visualising datasets that describe health need and service provision, to improve how data can inform decision making.
This project will develop novel analytics to visualise and increase understanding of antimicrobial prescribing and support antimicrobial stewardship initiatives.
This project will bring together analysts, managers and clinicians across a whole health economy to build a sustainable, self-supporting network of analytical capacity.
Building an analytical framework around the Electronic Frailty Index to transform care for people living with frailty
This project will establish a whole-system analytical framework to identify all frail patients in Midlothian, and will provide support to general practices to analyse the data and measure improvement.
Developing a community of practice around capacity planning for the Kent and Medway sustainability and transformation partnership
This project will develop new ways to support population health modelling and better service design within Kent and Medway STP.
Linking health and local government data at household level to understand social determinants of health
This project will create an innovative, household-level linked dataset between NHS and local government in order to improve the use of information in the health care system and local government in Islington to assess patterns in the social determinants of health.
Modelling elective pathways across the Devon health economy to better inform strategic STP decision-making
This project will use innovative statistical techniques to develop high-level models of the elective care system to predict and inform the impact of proposed changes on patient flow, outcomes and cost.
This project will deliver a tailored research design and statistical training programme to train staff within the Royal Derby Hospital to increase their ability to analyse electronic data.
This project aims to improve understanding of the variation in routes-to-diagnosis (for example screen-detected, GP referral, emergency presentation) of cancer in Northern Ireland, in order to increase earlier diagnoses and treatment effectiveness.
This project aims to kick-start the use of the ‘R’ statistical and graphics programming language in the NHS in order to improve data analysis and develop shared solutions.