Electronic prescribing systems as tools to improve patient care: a learning health systems approach to increase guideline concordant prescribing for venous thromboembolism prevention

Table 4 Estimated compliance from the segmented linear regression model and equivalent rates of change immediately before and after each intervention and medication switch

Intervention	Estimated compliance			Equivalent rate of change in compliance per 52 weeks
Intervention	Before	After	p value	Before	After	p value
1. Intervention 1. Introduction of a Junior doctor dashboard	73.2	70.7	0.035	3.4	9.8	< 0.001
2. Intervention 2. Introduction of mandatory VTE assessment and prescribing	82.9	95.4	< 0.001	9.8	− 0.7	< 0.001
3. Intervention 3. Change in order of ‘no reduced mobility’	94.2	93.2	0.010 (0.464)	− 0.7	− 1.0	N/A (0.085)
Medication switches
1. Enoxaparin to Tinzaparin	91.4	91.2	< 0.001	− 1.0	1.4	< 0.001
2. Tinzaparin back to Enoxaparin	93.3	92.5	0.023	1.4	0.0	0.011

Figures in parentheses for intervention 3 are p values if a slope change for intervention 3 is included in the model. As this was not significant, it was excluded and as a result the step change for intervention 3 became significant (the p value changing from 0.464 to 0.010). The final model includes five step changes and four slope changes

ISSN: 1472-6947