If we use pharmacist interventions in determining errors, we are measuring possible/potential errors.
However, this is not employed within health technology assessments of 'curative' interventions and to do so only in the assessment of preventive interventions would be introducing an adverse bias for such interventions in determining resource allocation.
Results thus emphasize the importance of the duration of the intervention's effect in determining its cost effectiveness.
The results of this study have application for the planning and conduct of intervention trials, especially in determining potential risks.
The discordance in results among studies could be caused by contextual factors (differences in populations of patients and usual practice within units) or intervention factors (differences in determining readiness to wean, ventilator modes, and variables used in weaning protocols).
The first part is the exploration of the knowledge of caregivers about malaria, the prevailing treatment seeking behaviour in the community prior to the intervention and the participants' involvement in determining the intervention activities.
Considering the findings from Winkley et al. and their challenge to develop more potent psychological interventions, we were interested in determining whether existing interventions that include adherence-promoting components would fare better with regard to improving glycemic control.
Intervening variables (i.e., in determining intervention fidelity) are assessed from surveys of front-line staff pre- and post-intervention.
We also found the consultation context important in determining intervention practices.
However, different results were found in the Prevention and DCIS cohorts, suggesting that trial population characteristics are important in determining intervention efficacy.
Provider characteristics and attitudes, in particular the team in which the providers worked and beliefs about perceived effectiveness and accessibility of support services, were most important in determining intervention practices (explaining over 60% of the between provider variance), compared to patient or consultations factors (explaining 20% of the between provider variance).
