Why the study?
Does a pharmacist-driven computerized surveillance model improve detection of opioid-related adverse drug events in perioperative care?
Does a pharmacist-driven computerized surveillance model improve detection of opioid-related adverse drug events in perioperative care?
A pharmacist-driven computerized surveillance model is an efficient and sustainable method for detecting rare but serious opioid-related adverse drug events in perioperative care.
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May enhance opioid ADE detection in perioperative care at modest cost; leaves open impact on outcomes pending prospective trials.
A small investment of resources into a pharmacist-driven surveillance model gave great gains in organizational adverse drug event detection. The patients who experienced multiple events are particularly relevant to future studies seeking risk factors for opioid induced respiratory depression. Computerized surveillance is an efficient, impactful, and sustainable model for ongoing capture and analysis of these rare, but potentially serious events.
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Eckstrand et al. (2009) studied this question.
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