Feb 17, 2018. Distribution of clinically significant medication errors according to hospitalization day. Springer; 2009.
Impact of pharmacist care in the management of cardiovascular disease risk factors: View Project. When compared with a decision to treat based on the criterion of age, our model enhanced the interception of potential adverse drug events by 17.
Of these, 475 were considered as events of interest due to their association with harm or potential harm Table 2. BootStrap incorrect.
See Bootstrap 4 document for more information. After fitting a similar predictive model on a bootstrap sample training model , we randomly assigned patients from our initial sample testing sample into one of two groups in a 1: This model was reported using international standards [ 22 , 23 ] and assessed for robustness using resampling methods.
There are three ways to install and include Bootstrap 4 for your project:. In contrast, focusing interventions on high-risk patients might be essential in the setting of resource limitations. For clinically significant ME prediction, we fitted a multivariate logistic model composed of 11 predictors Table 3.
Description of reported medication errors, with illustrative examples. While some focus on a subcategory [ 17 — 20 ], others are specific to certain age groups or diagnostic populations [ 17 , 19 , 20 ].
Most occurred on the first day of hospitalization Fig 2 , with a majority of unintentional discrepancies resulting from inaccurate information about current medications, which were corrected by physician after notification.