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Table 1 Estimated Odds Ratio and 95% Confidence Intervals for the GEE* regression model for new prescribing error in a prescription.

From: Chronology of prescribing error during the hospital stay and prediction of pharmacist's alerts overriding: a prospective analysis

GEE* regression model Univariate analysis Final multivariate model†
Variable Crude Odds Ratio [95% CI] P value Adjusted Odds Ratio [95% CI] P value
Number of order lines, for 10 lines increase 2.34 [1.54-3.55] <0.001 3.13 [1.89-5.16] <0.001
Day, for 1 day increase 0.57 [0.47-0.70] <0.001    
Log(day)   <0.001    <0.001
   day2 versus day 1 0.39 [0.29-0.52]   0.34 [0.25-0.47]  
   day3 versus day 2 0.57 [0.49-0.67]   0.54 [0.45-0.64]  
   day4 versus day 3 0.67 [0.60-0.76]   0.64 [0.56-0.73]  
   day5versus day 4 0.74 [0.67-0.81]   0.71 [0.64-0.79]  
   day6 versus day 5 0.78 [0.72-0.84]   0.76 [0.69-0.82]  
   day7 versus day 6 0.81 [0.76-0.86]   0.79 [0.73-0.85]  
Renal failure    <0.001    0.002
   No 1.00    1.00   
   Yes 2.19 [1.41-3.39]   2.16 [1.35-3.43]  
Hypertension    0.49    
   No 1.00      
   Yes 0.85 [0.54-1.34]     
Thromboembolic disease    0.061    
   No 1.00      
   Yes 1.65 [0.97-2.80]     
Ward    0.016    
   diabetes care 1.00      
   geriatrics 2.08 [0.62-6.99]     
   internal medicine (ward 1) 2.48 [0.72-8.42]     
   internal medicine (ward 2) 3.20 [0.95-10.65]     
   immunology 3.33 [0.99-11.15]     
   vascular medicine 3.41 [1.03-11.28]     
   nephrology 6.31 [1.94-20.46]     
Day of discharge    0.124    
   No 1.00      
   Yes 0.49 [0.19-1.22]     
  1. * GEE = Generalized Estimating Equations; † After backward selection with all potential confounders; ‡ The log-linearity relationship traduces that the decrease of the risk to have a new prescribing error was not constant over time but "digressive".