Choosing optimal outcome measures maximizes statistical power, accelerates discovery and improves reliability in early-phase trials. We devised and evaluated a modification to a pragmatic measure of oxygenation function, the ratio. Because of the ceiling effect in oxyhaemoglobin saturation, ratio ceases to reflect pulmonary oxygenation function at high values. We found that the correlation of with the reference standard (/ ratio) improves substantially when excluding and refer to this measure as . Using observational data from 39,765 hospitalised COVID-19 patients, we demonstrate that is predictive of mortality, and compare the sample sizes required for trials using four different outcome measures. We show that a significant difference in outcome could be detected with the smallest sample size using . We demonstrate that is an effective intermediate outcome measure in COVID-19. It is a non-invasive measurement, representative of disease severity and provides greater statistical power.