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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".