Effect of changes over time in the performance of a customized SAPS-II model on the quality of care assessment

Abstract

Purpose: The aim of our study was to explore, using an innovative method, the effect of temporal changes in the mortality prediction performance of an existing model on the quality of care assessment. The prognostic model (rSAPS-II) was a recalibrated Simplified Acute Physiology Score-II model developed for very elderly Intensive Care Unit (ICU) patients.

Methods: The study population comprised all 12,143 consecutive patients aged 80 years and older admitted between January 2004 and July 2009 to one of the ICUs of 21 Dutch hospitals. The prospective dataset was split into 30 equally sized consecutive subsets. Per subset, we measured the model's discrimination [area under the curve (AUC)], accuracy (Brier score), and standardized mortality ratio (SMR), both without and after repeated recalibration. All performance measures were considered to be stable if <2 consecutive points fell outside the green zone [mean ± 2 standard deviation (SD)] and none fell outside the yellow zone (mean ± 4SD) of pre-control charts. We compared proportions of hospitals with SMR>1 without and after repeated recalibration for the year 2009.

Results: For all subsets, the AUCs were stable, but the Brier scores and SMRs were not. The SMR was downtrending, achieving levels significantly below 1. Repeated recalibration rendered it stable again. The proportions of hospitals with SMR>1 and SMR<1 changed from 15 versus 85% to 35 versus 65%.

Conclusions: Variability over time may markedly vary among different performance measures, and infrequent model recalibration can result in improper assessment of the quality of care in many hospitals. We stress the importance of the timely recalibration and repeated validation of prognostic models over time.

Fig. 1

Area under the receiver operating characteristic curve (AUC) of the rSAPS-II over time. Means and standard deviations (SD) are based on the bootstrap sample distribution obtained by taking 3000 samples of size 405 from the internal validation set. rSAPS-II Model developed for assessing the quality of care based on the Simplified Acute Physiology Score (SAPS)

Fig. 2

Brier scores of rSAPS-II over time. Means and standard deviations (SD) are based on the bootstrap sample distribution obtained by taking 3000 samples of size 405 from the internal validation set

Fig. 3

Standardized mortality ratio (SMR) of rSAPS-II over time. Means and standard deviations (SD) are based on the bootstrap sample distribution obtained by taking 3000 samples of size 405 from the internal validation set

Fig. 4

Mortality over time

Fig. 5

Mean age over time