Improvement Analytics Unit (IAU) In a unique partnership between NHS England and the Health Foundation, we evaluate complex initiatives in health and social care in order to support learning and improvement.

The Improvement Analytics Unit (IAU) is a unique partnership between NHS England and the Health Foundation. We evaluate complex initiatives in health and social care in order to support learning and improvement.

Our unique access to NHS data combined with our ability to work closely with decision-makers, allows us to deliver independent, rigorous evaluations of complex change to better inform policy and care. We share our ideas, capabilities, and experience. And we collaborate with others to encourage analysis and evaluation.

By providing rapid feedback to service leaders and decision-makers at both a local and national level, we help to identify what is working well and what might need to change in the future to improve outcomes.

The Improvement Analytics Unit:

• Provides robust evaluation of complex change to support the development of strong and effective health care systems.
• Identifies whether outcomes for patients have changed following the introduction of a new initiative and why, so far as possible.
• Helps to spread the use of data analytics in the NHS for the purposes of quality improvement and evidence-based decision making.
• Strengthens the robustness of the body of evidence available to inform policy development.

The IAU’s senior sponsors are Charles Tallack, the Health Foundation’s Director of Research and Analysis and Ming Tang, National Director Data and Analytics at NHS England.

Our approach

We deliver rigorous analysis and evaluation of complex change. What we discover influences decision-makers in the development of national health and care programmes and policies. 

The team at the Improvement Analytics Unit are experts in robust evaluation. We use a range of evaluation methods, particularly focusing on counterfactual analysis  – one of the most rigorous ways to determine the real impact of interventions.

Robustly evaluating the impact of complex change often requires the use of a counterfactual control group. Counterfactual analysis relies on making a comparison between a group of patients who have experienced an intervention with a carefully matched control group who have not. We take a wide range of factors into account to help us ensure that any differences observed between the two groups are likely to be the result of the intervention.

Our current programmes

Understanding primary care 

General practices in England are currently facing major workforce pressures with falling numbers of full time General Practitioners (GPs) and rising demand for services. 

Partnering with NHSE’s Primary Care Transformation directorate and The Strategy Unit, we are working to understand changes in staff skill mix, activity, and patient characteristics to inform national policy direction.

Health equity in primary care 

Around 50% of funding allocated to general practices in England is determined by the global sum allocation formula (also known as the Carr-Hill). The formula considers several factors to determine how much funding to assign a practice, and has been criticised for not fully considering patient need or deprivation. 

We are evaluating a recent intervention by Leicester, Leicestershire and Rutland ICS, which provided additional funding for some practices to account for those higher patient need or levels of deprivation. We are looking to understand the impact, if any, of these payments on the practices and on inequalities in practice performance across the ICS. 

Evaluation technology changes with the NHS Innovation Accelerator 

Technology innovations are an important opportunity for the NHS but, in a complex landscape, it can be difficult to know what works. We have partnered with the NHS Innovation Accelerator to evaluate some of the companies that they support, enabling better understanding of their implementation and impact.

Our recent programmes 

Evaluating the Elective Hubs with the Getting It Right First Time (GIRFT) team

Surgical hubs are dedicated units within NHS trusts that aim to improve productivity, reduce cancelled operations and enable people to be discharged from hospital more quickly by ring-fencing staff and resources for planned surgery. 

Our research provides the first robust causal evidence that NHS surgical hubs increase treatment volumes and reduce the length of time patients spend in hospital. By delivering more operations in a shorter time, they could speed up efforts to tackle waiting lists.

Developing a minimum data set for care home residents 

The recent growth in research on social care services needs access to large, comprehensive, routine datasets on these services and their interaction with healthcare. As part of the Developing research resources And minimum data set for Care Homes’ Adoption (DACHA) study, we set out to develop a prototype minimum dataset to demonstrate proof of concept and proposals for implementation .

Understanding virtual wards with NHSE’s Virtual Wards Programme team 

Virtual wards treat patients in their own homes who would traditionally be cared for in hospital. They have been rapidly rolled out across England with the aim of improving patient choice and experience, as well as avoiding the risks of inpatient stays and improving hospital flow. We analysed the state of virtual wards across England to understand their variation and scale of the roll out.

Contact

For further information, or to register your interest in taking part in an evaluation, please get in touch with Geraldine Clarke, Senior Analytical Manager.