Monitoring Mortality in Intensive Care
Author Information
Author(s): Cockings Jerome GL, Cook David A, Iqbal Rehana K
Primary Institution: Royal Berkshire Hospital
Hypothesis
Can cumulative expected minus observed mortality and risk-adjusted p charts effectively monitor patient outcomes in intensive care?
Conclusion
Using E-O plots and risk-adjusted p charts allows for rapid detection of changes in risk-adjusted outcomes for intensive care patients.
Supporting Evidence
- 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.
- Risk-adjusted p charts showed several observations below the 2 SD control limits.
Takeaway
This study shows that we can use simple charts to quickly see how well patients are doing in intensive care, helping doctors make better decisions.
Methodology
Demographic and APACHE II data were collected prospectively on all patients admitted to a UK regional hospital, and E-O plots and risk-adjusted p charts were used for analysis.
Potential Biases
Potential biases may arise from the retrospective nature of data collection and the specific patient population studied.
Limitations
The study may not generalize to all intensive care units due to variations in case mix and data collection methods.
Participant Demographics
The study included adult patients admitted to a regional intensive care unit, with a mean age of 57 years.
Statistical Information
P-Value
0.78
Confidence Interval
0.74 to 0.82
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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