Risk modelling for quality improvement in the critically ill: making best use of routinely available data
Record ID 32015000943
English
Authors' objectives:
When patients are critically ill, they are rarely able to choose where they are treated. We must therefore ensure that all hospitals deliver high quality critical care. One way to do this is through clinical audit. The National Advisory Group for Clinical Audit and Enquiries describes clinical audit as, "the assessment of the process (using evidence-based criteria) and/or the outcome of care (by comparison with others)." When clinical audit is undertaken by assessment of the outcome of care (by comparison with others)" it is essential that this comparison takes into account the differing types of patients treated in different hospitals. For example, if one hospital admits many more very sick or very elderly patients, then one might expect the death rate in that hospital to be higher. To do this, we use risk prediction models (also known as risk adjustment or case mix adjustment). These statistical models take information about the patient known before, or soon after, the start of their illness and make a prediction of their likely outcome based on many thousands of previous similar patients. Large amounts of information (data) are routinely collected about patients using NHS services, but often we do not make the best possible use of this data to improve patient care and outcomes. Data is held by different organisations in different databases. Joining up these different databases (data linkage) can give us a more complete picture of what has happened to a patient. The Intensive Care National Audit & Research Centre (ICNARC) is an independent charity that runs national clinical audits to monitor and improve care for critically ill patients. ICNARC co-ordinates two national clinical audits: the Case Mix Programme (CMP), a national clinical audit of adult critical care; and the National Cardiac Arrest Audit (NCAA), a national clinical audit of in-hospital cardiac arrest. Our proposed project aims to use data linkage to further develop and improve our risk prediction models underpinning these two audits, to ensure that they provide accurate and up-to-date information back to the hospitals to support quality improvement (and better patient care). The number of patients that survive to leave hospital after being admitted to an adult critical care unit has increased greatly over previous years. We therefore need to look beyond hospital mortality as an outcome of critical illness. By linking data from the CMP with death registrations we can monitor longer term survival. By linking with routine hospital data and two other national clinical audits the National Diabetes Audit and the UK Renal Registry we will develop risk models to enable us to monitor important problems that patients can experience after critical care. For cardiothoracic critical care caring largely for patients who have had heart surgery by linking data from the CMP with the National Adult Cardiac Surgery Audit we will get a more complete picture of how sick these patients were before they were admitted to critical care, helping us to improve our risk models to make fairer comparisons for these patients. Finally, it can be very difficult to record data about patients that have an in-hospital cardiac arrest as this can occur at any place and any time. By linking data from NCAA with routine hospital data, we can get a better picture of how sick these patients were before their arrest and by linking with death registrations we can monitor longer term survival, enabling us to develop risk models to make fairer comparisons for these patients.
Details
Project Status:
Completed
URL for project:
http://www.nets.nihr.ac.uk/projects/hsdr/141906
Year Published:
2015
English language abstract:
An English language summary is available
Publication Type:
Not Assigned
Country:
England, United Kingdom
MeSH Terms
- Critical Illness
- Critical Care
- Models, Organizational
- Risk Factors
Contact
Organisation Name:
NIHR Health Services and Delivery Research programme
Contact Address:
NIHR Journals Library, National Institute for Health and Care Research, Evaluation, Trials and Studies Coordinating Centre, Alpha House, University of Southampton Science Park, Southampton SO16 7NS, UK
Contact Name:
journals.library@nihr.ac.uk
Contact Email:
journals.library@nihr.ac.uk
Copyright:
Queen's Printer and Controller of HMSO
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