Quality improvement Improving quality in health care is about making it safe, effective, patient-centred, timely, efficient and equitable
We think of quality improvement as a systematic approach that uses specific techniques to improve quality in health and health care.
Our recent work and content on this topic is listed below.
This guide focuses on one important element of the quality agenda: quality improvement. It looks in particular at what are known as organisational or industrial approaches to quality improvement.
A multidisciplinary analytics action learning set to improve GP appointment systems using discrete event simulation
This project will build analytical capacity in discrete event simulation (DES) in the GP setting, involving a case study site in the West Midlands, an applied skills development programme for analysts...
This project will use analytics from PathAnalyse to support senior staff to understand current processes, and identify scenarios that negatively impact patient experience and resource efficiency.
The Informatics Skills Framework will support the analytical workforce, identify skills gaps and improve capability, enabling analytics staff to provide analytical support, advice and guidance to clin...
Improving the analytical capabilities to support the North Cumbria Population Health Management approach
This project will develop and deliver a comprehensive training and support programme on how to access and use population health intelligence.
This project will use the programming language R to analyse prescription data to provide clinicians with adherence estimates and visualisation of medication histories at the point of care.
From data to decisions: embedding a Real-world Intervention Causal Evaluation (RICE) tool in the decision-making process
This project will develop a Real-world Intervention Causal Evaluation (RICE) tool, which will semi automate the process of intervention evaluation and significantly enhance analytical capability.
Developing the foundations of applied analytics: using a collaborative approach to model ‘black days’
This project will implement a standard process for data-mining (CRISP-DM) and develop collaboration between senior decision-makers and analytical teams.
This project will develop and test analytical strategies to inform the design of quality improvement projects led by paediatric trainees.
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Q is an initiative connecting people with improvement expertise across the UK.Find out more