Effect of mortality prediction models on resource use benchmarking of intensive care units

J Crit Care. 2024 Aug:82:154814. doi: 10.1016/j.jcrc.2024.154814. Epub 2024 Apr 20.

Abstract

Purpose: Intensive care requires extensive resources. The ICUs' resource use can be compared using standardized resource use ratios (SRURs). We assessed the effect of mortality prediction models on the SRURs.

Materials and methods: We compared SRURs using different mortality prediction models: the recent Finnish Intensive Care Consortium (FICC) model and the SAPS-II model (n = 68,914 admissions). We allocated the resources to severity of illness strata using deciles of predicted mortality. In each risk and year stratum, we calculated the expected resource use per survivor from our modelling approaches using length of ICU stay and Therapeutic Intervention Scoring System (TISS) points.

Results: Resource use per survivor increased from one length of stay (LOS) day and around 50 TISS points in the first decile to 10 LOS-days and 450 TISS in the tenth decile for both risk scoring systems. The FICC model predicted mortality risk accurately whereas the SAPS-II grossly overestimated the risk of death. Despite this, SRURs were practically identical and consistent.

Conclusions: SRURs provide a robust tool for benchmarking resource use within and between ICUs. SRURs can be used for benchmarking even if recently calibrated risk scores for the specific population are not available.

Keywords: Cost control; Health care benchmarking; Health resources; Hospital mortality; Intensive care unit; Resource allocation.

MeSH terms

  • Aged
  • Benchmarking*
  • Female
  • Finland / epidemiology
  • Health Resources / statistics & numerical data
  • Hospital Mortality*
  • Humans
  • Intensive Care Units* / statistics & numerical data
  • Length of Stay* / statistics & numerical data
  • Male
  • Middle Aged
  • Risk Assessment
  • Severity of Illness Index
  • Simplified Acute Physiology Score