The effects of two methods for customising the original SAPS II model for intensive care patients from South England.

Abstract

Model customisation is used to adjust prognostic models by re-calibrating them to obtain more reliable mortality estimates. We used two methods for customising the Simplified Acute Physiology Score II model for 15,511 intensive care patients by altering the logit and the coefficients of the original equation. Both methods significantly improved model calibration, but customising the coefficients was slightly more effective. The Hosmer-Lemeshow chi(2)-value improved from 306.0 (p< 0.001) before, to 14.5 (p < 0.07) and 23.3 (p < 0.06) after customisation of the coefficients and the logit, respectively. Discrimination was not affected. The standardised mortality ratio for the entire population declined from 1.16 (95% confidence interval: 1.13-1.20, p < 0.001) to 0.99 (95% confidence interval: 0.96-1.02, p < 0.22) after customisation of the coefficients. The uniformity-of-fit for patients grouped by operative status and comorbidities also improved, but remained imperfect for patients stratified by location before intensive care unit admission. Amalgamation of large, regional databases could provide the basis for the re-calibration of standard prognostic models, which could then be used as a national reference system to allow more reliable comparisons of the efficacy and quality of care based on severity adjusted outcome measures.