Increases in case-mix adjusted mortality may be indications of decreasing quality of care. Risk-adjusted control charts can be used for in-hospital mortality monitoring in intensive care units by issuing a warning signal when there are more deaths than expected. The aim of this study was to systematically assess and compare, by computer simulation, expected delay before a warning signal was given for an upward shift in mortality rate in intensive care mortality data by different risk-adjusted control charts.
We compared the efficiency of the risk-adjusted P-chart, risk-adjusted Additive P-chart, risk-adjusted Multiplicative P-chart, monthly Standardized Mortality Ratio, risk-adjusted Cumulative Sum, risk-adjusted Resetting Sequential Probability Ratio Test, and risk-adjusted Exponentially Weighted Moving Average control chart to detect an upward shift in mortality rate in eight different scenarios that varied by mortality increase factor and monthly patient volume.
Adult intensive care units in The Netherlands.
Patients admitted to 73 intensive care units from the Dutch National Intensive Care Evaluation quality registry from the year 2009.
We compared the performance of the different risk-adjusted control charts by the median time-to-signal and the 6-month detection rate.
In all eight scenarios, the risk-adjusted Exponentially Weighted Moving Average control chart had the shortest median time-to-signal, and in four, the highest 6-month detection rate. The median time-to-signal for an average volume intensive care unit (i.e., 50 admissions per month) with an increase in mortality rate of R = 1.50 on the odds scale was 9 months for the risk-adjusted Exponentially Weighted Moving Average control chart.
The risk-adjusted Exponentially Weighted Moving Average control chart signaled the fastest in most of the simulated scenarios and is therefore superior in detecting increases in in-hospital mortality of intensive care patients compared to the other types of risk-adjusted control charts.
From the Department of Medical Informatics (AK, NFdK, NP), Academic Medical Center, University of Amsterdam, The Netherlands; Department of Intensive Care (EdJ), Leiden University Medical Center, Leiden, The Netherlands; Intensive Care Unit (DAC), Princess Alexandra Hospital, Brisbane, Australia; Southern Clinical School (DAC), Faculty of Health Sciences, University of Queensland, Brisbane, Australia.
*See also p. 1976.
The authors have not disclosed any potential conflicts of interest.
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