Review of the application of risk-adjusted charts to analyse mortality outcomes in critical care.
This review describes the methods for displaying riskadjusted mortality data for critical care units. Two applications are considered. The comparison within a cohort of risk-adjusted mortality performance uses standardised mortality ratios (SMRs), league tables, caterpillar plots and funnel plots. Monitoring of riskadjusted performance over time is considered using SMRs, risk-adjusted p (RAP), observed minus expected outcome (VLAD), risk-adjusted cumulative sum (RACUSUM), riskadjusted sequential probability ratio test (RASPRT), and riskadjusted exponentially weighted moving average (RAEWMA) charts. Examples of the charts are provided, and calculation of the statistics and design of the charts are described in the Appendix. This overview is an introduction to the use of riskadjustment methods to track mortality rates. The importance of model performance and relevance of the risk-adjustment models is emphasised. The relative merits of different methods are discussed. Risk-adjusted monitoring plays a role in the context of a holistic quality development strategy. The importance of a planned approach to response and intervention is stressed.
Cook
David A
DA
Australian and New Zealand Intensive Care Society CORE Management Committee, Melbourne, VIC, Australia. d.cook@mailbox.uq.edu.au
Duke
Graeme
G
Hart
Graeme K
GK
Pilcher
David
D
Mullany
Daniel
D
D019985:Benchmarking / Q000379:methods / Q000706:statistics & numerical data*; D016638:Critical Illness / Q000401:mortality*; D003430:Cross-Sectional Studies; D017052:Hospital Mortality; D006801:Humans; D008137:Longitudinal Studies; D008499:Medical Records / Q000706:statistics & numerical data; D015233:Models, Statistical; D011159:Population Surveillance / Q000379:methods*; D020379:Risk Adjustment / Q000379:methods / Q000706:statistics & numerical data*