What was this study about?
Using statistical techniques, it is possible to build models that predict how likely a patient is to experience a particular outcome or condition. These risk models (or prognostic models) can be used to ‘risk adjust’ outcomes by taking into account severity of illness of patients to make fairer comparisons between health care providers.
At the time of this study, and since the validation of the APACHE II method in the UK which led to the establishment of ICNARC, a number of new methods had been developed outside of the UK to risk adjust hospital mortality in adult intensive care.
The aim of this study was to identify the best risk adjustment method to use for hospital mortality in adult intensive care in the UK by:
- assessing and comparing the current methods
- optimising the performance of the current methods (‘recalibrating’ the models) and comparing the methods following recalibration
- developing and assessing a new method, and comparing it with the current methods
This study used data from the Case Mix Programme.
What did the study find?
Risk prediction models developed in another country require validation and recalibration before being used to provide risk-adjusted outcomes within a new country setting. Regular reassessment is beneficial to ensure performance is maintained.
The new model (ICNARC model) demonstrated performed better in a UK setting than existing risk prediction models, even following recalibration of these models.
Who led the study?
Professor Kathy Rowan, ICNARC
The study was funded by the Medical Research Council (Project: G9813469)