My Bench Close. Sign In. Not A Member? Join MedWrench. Receive Summary Emails? Receive Instant Notices. Display in Community Feed. You can adjust your Community Subscriptions in Settings. Furthermore, drugs that were not identified at the patient's bedside were certified correct only after comparison with those in their original packaging, a check that is usually not performed by nurses.
The number of patients subjected to one or more MAEs also significantly decreased during the UDDS period, with a relative risk reduction of To our knowledge, this research is the first before-and-after observational study investigating an association between last-generation unit dose dispensing robots and AMDCs.
However, other comparable studies have been carried out. The error rates observed in our study are slightly superior to data available in the literature. For example, Taxis et al. In our study, omission appeared to be the most frequent error when using a UDDS, but this may be correlated with the number of drugs included in the formulary and the compliance of physicians with prescribing drugs in the formulary.
For non-formulary orders, pharmacists propose an equivalent drug available in the pharmacy but wait for the physician's approval before dispensing the drug.
This latency may result in omission as the nurse may not have any of the prescribed drugs available in the unit. In a nursing home setting, Van den Bemt et al. The purpose of our study was to assess the discrepancy between the orders placed by the physician and what was really administered by the nurse. As physicians seldom specify a specific time of administration or may forbid the crushing of specific tablets, these were not classified as errors in our study.
All error types were reduced after changing the drug distribution system: incorrect dosage and incorrect drug were reduced by Omission was the most frequently observed ME during both periods and remained similar during the two periods. During the WSS period, drugs were sometimes not administered either because of temporary unavailability in the ward stock or because a brand name was ordered that differed from the one available in the hospital formulary. Non-formulary prescriptions were managed differently during the UDDS, as a pharmacist checked each order every day and could propose an equivalent formulary drug, or straightaway deliver an equivalent if a similar drug same product and same form was available.
However, drugs were sometimes not administered during the UDDS period because a new order had been placed after the pharmacy had prepared the therapies. However, these instructions were not always followed. During the study, the robot was used 5 days a week and admissions were processed up to h. The robot is now working 6 days a week and up to h each day, so there should be fewer drug omissions.
This may also explain why error gravity appeared to be different before and after implementing the UDDS, with a lower prevalence of the most serious errors. In our study, if nurses did not apply the physician's orders exactly as specified after assessment of the patient's condition, it was considered as an error, but the physician may not have considered that error to be serious.
As we expected most MAEs to be minor, we did not use methods that were less sensitive to minor errors like the National Coordinating Council-Medication Error Reporting and Prevention [ 18 ]; otherwise, this result may not have been significant.
Errors were still observed during the UDDS period. The robot does not handle certain medications, such as those kept in large bottles or cold storage. These drugs are labelled by the pharmacy technician and delivered beside the rings, directly in the drawer or in a cold-maintaining package.
It was still up to the nurse to prepare the right dose if bottles were dispensed. Technicians could still make a mistake labelling the packages, and nurses could prepare an incorrect dose e. No difference was observed when comparing the two CPOE systems. This may be attributable to an insufficient number of observations. However, the difference between the two systems may be more significant prior to prescription because of decision support systems for example , and may have not been detected in our study.
This research has several limitations. We were not able to include intravenous or inhaled drugs in this study, because these drugs are administered separately from the main drug administration rounds. Moreover, less frequent errors may have escaped observation, for example, patient medication reversal in a two-bedroom.
This kind of error cannot be prevented by unit dose delivering if not associated with a bar code reading system at the patient's bedside. However, this technology can be part of the automated UDDS, as all drugs are either single-dose packaged or labelled and can display a bar code, unlike the WSS.
CPOE eliminates rewriting by the nurse, even if no rewriting error was disclosed during our study, and ensures prescription readability.
However, if a nurse has a problem reading an order, she usually asks the physician to confirm. The most significant role of these two elements is prior to placing an order, thanks to decision support systems or pharmacy advice. The lack of a control unit also limits the significance of our study.
Even if no major change occurs in the geriatric department between WSS and UDDS periods apart from the drug distribution systems, it is impossible to assert that ward organization is absolutely equivalent between periods. The method used in this study has other inherent limitations: the effect of the observer on the observed nurse.
But this effect is supposed to limit errors and would be expected to be similar in both periods, before and after the study. However, the root causes of MAEs are not limited to drug distribution systems, as there can be discrepancies between the medication the physician intended to prescribe and the order placed in a CPOE, and even between the prescribed medication and the recommended drug according to evidence-based guidelines.
In order to prevent MEs and further optimize patient medication management, a large spectrum of complementary solutions will be necessary. Assessments will be required to improve drug distribution systems with and without these complementary solutions.
Economic assessments should also be carried out to compare ward and pharmacy staff workloads, medication consumption, and the cost of MAEs. National Center for Biotechnology Information , U. Journal of Evaluation in Clinical Practice. Manual Description: Mathematical and in the same external proposition, is not inferring pyxis medstation users manual book lad.
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