| Learning Objective #1: Describe the nature and incidence of medication errors in surgical settings including the operating room, post-anesthesia care unit, day surgery units, labor and delivery, and post-partum units | |||
| Learning Objective #2: Identify system-related problems and strategies to prevent medication errors in acute care clinical settings |
Objective: Using data derived from secondary data analyses of a national medication error reporting system, this effort focused on describing and understanding the types and causes of medication errors in a variety of clinical settings operating room, day surgery settings, post-anesthesia care units, labor and delivery units, and post-partum care. Design: The study design was a secondary data analysis of MedMARxSM, an Internet-accessible, de-identified, anonymous medication error reporting database specific to hospitals and health systems. Concept or Variables Studied Together: Each of the medication error records were examined for the following fields: error description, location, staff who made the initial error, error categories, node, type(s) of error, cause(s) of error, contributing factor(s), product, level of care rendered to patient as a result of error, action(s) taken, and facility characteristics. Methods: Separate reports were generated using Microsoft Access® and Excel to describe medications errors in specific clinical settings. Error descriptions were analyzed to identify common themes and practice issues. Findings: The national database yielded hundreds of errors for each clinical setting and provided evidence of system-related problems and practice-related issues. Patterns identified include: 1) high rates of errors of omission, 2) administering medications for which the patient had previously identified allergies, 3)losing information at the time of patient transfer, 4) correctly identifying patients, and 5) significant management issues related to the care of patient-controlled analgesia and epidurals. Conclusions: Medication errors do occur in all clinical settings. While the majority are not life-threatening or injurious, these secondary analyses provide critical insights into the latent conditions contributing to medication errors. Implications: Secondary data analyses form national databases provide helpful insights on strategies to prevent medication errors. The patterns and trends identified in these analyses will be helpful to clinicians, educators, and researchers in their efforts to improve clinical systems and prevent patient injury.
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