What was this study about?
Using statistical techniques, it is possible to build models that predict how likely a patient 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 in order to make fairer comparisons between health care providers.
At the time of this study, a number of risk adjustment methods for paediatric intensive care had been developed, but none had been validated for general use in the UK.
The aim of this study was to identify the best risk adjustment method for outcomes in paediatric intensive care in the UK by:
- assessing and comparing the current methods (PIM, PIM2, PRISM, PRISM III - 12 hours and PRISM III - 24 hours)
- optimising the performance of the current methods (‘recalibrating’ the models) and comparing the methods following recalibration
- comparing alternative health state valuation models for the HUI2 health related quality of life instrument
- developing and assessing a model for risk adjustment of health status, as measured by HUI2, at six months following admission to a paediatric intensive care unit
22 UK paediatric intensive care units took part in the study and collected data on 10,197 children admitted to the unit between March 2001 and March 2002. 450 members of the general public took part in surveys to estimate health state valuation models for the HUI2.
What did the study find?
PIM2, PRISM III - 12 hours and PRISM III - 24 hours all were found to be suitable for use in a UK paediatric intensive care setting following recalibration. All methods provided similar conclusions in assessing the distribution of risk-adjusted mortality in UK PICUs.
The preferred method for health state valuation using the HUI2 was the UK statistical inference valuation algorithm. Using the HUI2 identified significant morbidity among children at six months following admission to a paediatric intensive care unit.
This study contributed to establishing the Paediatric Intensive Care Audit Network (PICANet), the national clinical audit for paediatric intensive care in the UK.
Who led the study?
Dr Gareth Parry, Medical Care Research Unit, University of Sheffield
Dr Christopher McCabe, Medical Care Research Unit, University of Sheffield
Professor Kathy Rowan, ICNARC
The study was funded by the Medical Research Council (Project: G9900013)