Abstract
Objectives: 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. Design: 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. Setting: Adult intensive care units in The Netherlands. Patients: Patients admitted to 73 intensive care units from the Dutch National Intensive Care Evaluation quality registry from the year 2009. Interventions: None. Measurements: We compared the performance of the different risk-adjusted control charts by the median time-to-signal and the 6-month detection rate. Main results: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. Conclusions: 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. (Crit Care Med 2012; 40:1799-1807)
| Original language | English |
|---|---|
| Pages (from-to) | 1799-1807 |
| Journal | Critical care medicine |
| Volume | 40 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 2012 |
Fingerprint
Dive into the research topics of 'Performance of risk-adjusted control charts to monitor in-hospital mortality of intensive care unit patients: A simulation study'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver