The impact of a computerized physician order entry system implementation on 20 different criteria of medication documentation—a before-and-after study

Table 4 Multivariable analysis of prescription-Fscores (outcome variables) estimated from a beta-distributed generalized linear mixed models (GLMM)

	Odds ratio	95% CI	P value
Baseline effect (intercept)	1.71	[1.31; 2.23]	< 0.001
Time point: post-implementation versus pre-implementation	10.11	[8.49; 12.05]	< 0.001
Prescription category (reference: standard peroral administration)
Risky route	0.76	[0.73; 0.79]	< 0.001
As needed	0.59	[0.57; 0.61]	< 0.001
Other	0.87	[0.80; 0.93]	< 0.001
Number of comedications (n)	0.99	[0.97; 1.02]	0.622
Ward indicator^a
Ward 1	0.80	[0.64; 1.01]	0.057
Ward 2	1.04	[0.83; 1.31]	0.707
Ward 3	0.53	[0.43; 0.67]	< 0.001
Ward 4	0.82	[0.64; 1.05]	0.115
Ward 5	1.29	[1.03; 1.63]	0.028
Ward 6	1.44	[1.11; 1.86]	0.005
Ward 7	1.21	[1.05; 1.40]	0.009

CI, confidence interval; prescription-Fscore, fulfilment score per prescription
Within-patient correlation (random-effects standard deviation): 0.762 [95% CI 0.699–0.831]; Prescription-Fscores estimated as odds ratios with 95% confidence intervals (CI)
^aCategories were included by weighted effect-coding[26]

ISSN: 1472-6947