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Medication‐prescribing errors generated at interfaces‐in‐care are the most common cause of preventable health care errors and contribute substantially to adverse patient outcomes. For this reason, standardized medication reconciliation (MR) processes need to be inserted at these interfaces. However, MR is an inherently complex task, and little data exist to inform system‐based operationalization. The Portland Informatics Center addressed this challenge by creating an electronic patient‐directed multimedia survey to automate the medication history collection. This article describes a research protocol designed to compare the software's medication discrepancy detection rate with traditional history collection strategies. For this randomized, controlled, single‐blind trial, participants are randomly allocated into one of two groups: the control group reviews a paper list printed from the electronic record, whereas the intervention group uses a computer‐assisted reconciliation survey that includes display of visual data (i.e., medication pictures).
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Lesselroth et al. (2011) studied this question.
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