A new risk-adjusted Bernoulli cumulative sum chart for monitoring binary health data.
To monitor a health event in patients with a specific risk of developing the event, a risk-adjusted cumulative sum chart is needed. The risk-adjusted cumulative sum chart proposed in the literature has some limitations. Setting appropriate control limits is not straightforward, there is no simple formula for constructing them, and they remain sensitive to changes in the underlying risk distribution and the baseline incidence rate. To overcome these limits, we propose a new risk-adjusted Bernoulli cumulative sum chart as a simple and efficient solution. Analyses of simulated and real data sets illustrate the performance and usefulness of the proposed procedure.
Unit of Epidemiology and Biostatistics, Institute of Clinical Physiology, National Research Council and G. Monasterio Foundation, Pisa, Italy giuseppe.rossi@ifc.cnr.it.
Giuseppe
G
Rossi
Unit of Epidemiology and Biostatistics, Institute of Clinical Physiology, National Research Council and G. Monasterio Foundation, Pisa, Italy.
Simone Del
SD
Sarto
Department of Statistics, University of Florence, Florence, Italy.
Marco
M
Marchi
D066264:Datasets as Topic; D006331:Heart Diseases / Q000401:mortality / Q000601:surgery; D006801:Humans; D015994:Incidence; D009010:Monte Carlo Method; D020379:Risk Adjustment / Q000379:methods*; D013903:Thoracic Surgery; D006113:United Kingdom / Q000453:epidemiology
Bernoulli variate; cumulative sum chart; health data; risk-adjustment; surveillance