摘要
Purpose: To determine if nurses are able to identify medication errors that have the potential to bypass computer physician order entry (CPOE) and smart ordering systems. Background: Medical care systems employ computer “smart” systems to reduce medication errors by using artificial intelligence (preprogrammed methods of decision support and error reduction). However, these systems are not perfect and they can be bypassed. Nurses who carry out the order represent the last check point in error prevention prior to the administration of medication orders. Methods: A paper exercise was created with 513 physician orders. Nurses were asked to indicate whether they would carry out the order, refuse to carry out the order, consult a pharmacist for clarification, or carry out the order with special precautions. Nurses were given the option of using any nursing or medical reference. Results: The rate of correctly identifying 23 of the contraindicated orders was low. Both experienced and inexperienced nurses had high rates of not identifying the errors despite similar use of references and requests for assistance from pharmacists. Conclusions: This study demonstrates that if an error escapes a smart system, nurses were able to identify most of these errors, but not all of these. The current system features high stress, self-esteem issues, time pressure, high volume, and high risk. The system must change radically to meet the public’s expectations of being nearly error free which can only be achieved with smarter systems that are more resistant to human errors.
Purpose: To determine if nurses are able to identify medication errors that have the potential to bypass computer physician order entry (CPOE) and smart ordering systems. Background: Medical care systems employ computer “smart” systems to reduce medication errors by using artificial intelligence (preprogrammed methods of decision support and error reduction). However, these systems are not perfect and they can be bypassed. Nurses who carry out the order represent the last check point in error prevention prior to the administration of medication orders. Methods: A paper exercise was created with 513 physician orders. Nurses were asked to indicate whether they would carry out the order, refuse to carry out the order, consult a pharmacist for clarification, or carry out the order with special precautions. Nurses were given the option of using any nursing or medical reference. Results: The rate of correctly identifying 23 of the contraindicated orders was low. Both experienced and inexperienced nurses had high rates of not identifying the errors despite similar use of references and requests for assistance from pharmacists. Conclusions: This study demonstrates that if an error escapes a smart system, nurses were able to identify most of these errors, but not all of these. The current system features high stress, self-esteem issues, time pressure, high volume, and high risk. The system must change radically to meet the public’s expectations of being nearly error free which can only be achieved with smarter systems that are more resistant to human errors.
