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Background The use of a ‘do not interrupt’ vest during medication administration rounds is recommended but there have been no controlled randomized studies to evaluate its impact on reducing administration errors. We aimed to evaluate the impact of wearing such a vest on reducing such errors. The secondary objectives were to evaluate the types and potential clinical impact of errors, the association between errors and several risk factors (such as interruptions), and nurses’ experiences. Methods This was a multicenter, cluster, controlled, randomized study (March–July 2017) in 29 adult units (4 hospitals). Data were collected by direct observation by trained observers. All nurses from selected units were informed. A ‘Do not interrupt’ vest was implemented in all units of the experimental group. A poster was placed at the entrance of these units to inform patients and relatives. The main outcome was the administration error rate (number of Opportunities for Error (OE), calculated as one or more errors divided by the Total Opportunities for Error (TOE) and multiplied by 100). Results We enrolled 178 nurses and 1346 patients during 383 medication rounds in 14 units in the experimental group and 15 units in the control group. During the intervention period, the administration error rates were 7.09% (188 OE with at least one error/2653 TOE) for the experimental group and 6.23% (210 OE with at least one error/3373 TOE) for the control group (p = 0.192). Identified risk factors (patient age, nurses’ experience, nurses’ workload, unit exposition, and interruption) were not associated with the error rate. The main error type observed for both groups was wrong dosage-form. Most errors had no clinical impact for the patient and the interruption rates were 15.04% for the experimental group and 20.75% for the control group. Conclusions The intervention vest had no impact on medication administration error or interruption rates. Further studies need to be performed taking into consideration the limitations of our study and other risk factors associated with other interventions, such as nurse’s training and/or a barcode system. Trial registration The PERMIS study protocol (V2–1, 11/04/2017) was approved by institutional review boards and ethics committees (CPP Ile de France number 2016-A00211–50, CNIL 21/03/2017, CCTIRS 11/04/2016). It is registered at ClinicalTrials.gov (registration number: NCT03062852, date of first registration: 23/02/2017).

Background Clinical pharmacists’ involvement has improved patients’ care, by suggesting therapeutic optimizations. However, budget restrictions require a prioritization of these activities to focus resources on patients more at risk of medication errors. Objective The aim of our study was to identify variables influencing the formulation of pharmaceutical to improve medication review efficiency. Setting This study was conducted in medical wards of a 643-acute beds hospital in Paris, France. Methods All hospital medical prescriptions of all patients admitted within four medical wards (cardiology, rheumatology, neurology, vascular medicine) were analyzed. The study was conducted in each ward for 2 weeks, during 4 weeks. For each patient, variables prospectively collected were: age, gender, weight, emergency admission, number of high-alert medications and of total drugs prescribed, care unit, serum creatinine. Number of pharmaceutical interventions (PIs) and their type were reported. Main outcome measures Variables influencing the number of pharmaceutical interventions during medication review were identified using simple and multiple linear regressions. Results A total of 2328 drug prescriptions (303 patients, mean age 70.6 years-old) were analyzed. Mean number of hospital drug prescriptions was 7.9. A total of 318 PIs were formulated. Most frequent PIs were drug omission (n = 88, 27.7%), overdosing (n = 69, 21.7%), and underdosing (n = 51, 16.0%). Among variables studied, age, serum creatinine level, number of high-alert medications prescribed and total number of drugs prescribed were significantly associated with the formulation of pharmaceutical interventions (adjusted R2 = 0.34). Conclusions This study identified variables (age, serum creatinine level, number of high-alert medication, number of prescribed drugs) that may help institutions/pharmacists target their reviews towards patients most likely to require pharmacist interventions.