Abstract
IntroductionA health care system is a complex adaptive system. The effect of a single intervention, incorporated into a complex clinical environment, may be different from that expected. A national database such as the Intensive Care National Audit & Research Centre (ICNARC) Case Mix Programme in the UK represents a centralised monitoring, surveillance and reporting system for retrospective quality and comparative audit. This can be supplemented with real-time process monitoring at a local level for continuous process improvement, allowing early detection of the impact of both unplanned and deliberately imposed changes in the clinical environment.MethodsDemographic and UK Acute Physiology and Chronic Health Evaluation II (APACHE II) data were prospectively collected on all patients admitted to a UK regional hospital between 1 January 2003 and 30 June 2004 in accordance with the ICNARC Case Mix Programme. We present a cumulative expected minus observed (E-O) plot and the risk-adjusted p chart as methods of continuous process monitoring. We describe the construction and interpretation of these charts and show how they can be used to detect planned or unplanned organisational process changes affecting mortality outcomes.ResultsFive hundred and eighty-nine adult patients were included. The overall death rate was 0.78 of predicted. Calibration showed excess survival in ranges above 30% risk of death. The E-O plot confirmed a survival above that predicted. Small transient variations were seen in the slope that could represent random effects, or real but transient changes in the quality of care. The risk-adjusted p chart showed several observations below the 2 SD control limits of the expected mortality rate. These plots provide rapid analysis of risk-adjusted performance suitable for local application and interpretation. The E-O chart provided rapid easily visible feedback of changes in risk-adjusted mortality, while the risk-adjusted p chart allowed statistical evaluation.ConclusionLocal analysis of risk-adjusted mortality data with an E-O plot and a risk-adjusted p chart is feasible and allows the rapid detection of changes in risk-adjusted outcome of intensive care patients. This complements the centralised national database, which is more archival and comparative in nature.
Highlights
A health care system is a complex adaptive system
Demographic and UK Acute Physiology and Chronic Health Evaluation II (APACHE II) data were prospectively collected on all patients admitted to a UK regional hospital between 1 January 2003 and 30 June 2004 in accordance with the Intensive Care National Audit & Research Centre (ICNARC) Case Mix Programme
In accordance with the national ICNARC Case Mix Programme (CMP) dataset (ICMPDS version 2) [5], episodes were excluded for patients less than 16 years old, for intensive care unit (ICU) admissions lasting less than eight hours, admissions for primary burns, admissions after coronary artery bypass grafting, transfers in from another ICU, readmissions within the same hospital stay or admissions lacking all 12 physiological variables
Summary
A health care system is a complex adaptive system. The effect of a single intervention, incorporated into a complex clinical environment, may be different from that expected. A national database such as the Intensive Care National Audit & Research Centre (ICNARC) Case Mix Programme in the UK represents a centralised monitoring, surveillance and reporting system for retrospective quality and comparative audit. This can be supplemented with real-time process monitoring at a local level for continuous process improvement, allowing early detection of the impact of both unplanned and deliberately imposed changes in the clinical environment. Constraints of rationing and redistribution of scarce resources, the paucity of rigorous examination of critical care practice and the adaptive and emergent features of a complex interactive system undermines the logic of expecting the application of pockets of experimental evidence to lead naturally to improved outcomes for all patients. It is not enough to incorporate the best empirical practice conscientiously into each step in the patient encoun-
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