Severity scoring systems are used in intensive care units for stratifying patients in clinical research and benchmarking ICU performance. A variant of the Acute Physiology and Chronic Health Evaluation (APACHE) system is used in Australia for benchmarking purposes – the APACHE III-j. This and other major scoring systems have been developed under an old paradigm of minimum data collection, while the current paradigm is to use all useful data. The APACHE III-j system uses the worst observations in the first 24-hours of a patient’s ICU stay, ignoring the rest of the distributional information. We hypothesise that scoring system performance can be improved by adding variables that capture this ignored distributional information. To test this hypothesis, the APACHE III-j system will be replicated and compared to a modified version that adds metrics describing the distribution of an underlying physiology variable utilising high frequency data.