Background Medication non-adherence is a major issue after transplant that can lead to misdiagnosis, rejection, poor health affecting quality of life, graft loss or death. Several estimations of adherence and related factors have previously been described but conclusions leave doubt as to the most accurate assessment method. Aim of the review To identify the factors most relevant to medication non-adherence in kidney transplant in current clinical practice. Method This systematic review is registered in the PROSPERO data base and follows the Prisma checklist. Articles in English in three databases from January 2009 to December 2014 were analysed. A synthesis was made to target adherence assessment methods, their prevalence and significance. Results Thirty-seven studies were analysed rates of non-adherence fluctuating from 1.6 to 96%. Assessment methods varied from one study to another, although self-reports were mainly used. It appears that youth (≤50 years old), male, low social support, unemployment, low education, ≥3 months post graft, living donor, ≥6 comorbidities, ≥5 drugs/d, ≥2 intakes/d, negative beliefs, negative behavior, depression and anxiety were the factors significantly related to non-adherence. Conclusion As there are no established guidelines, consideration should be given to more than one approach to identify medication non-adherence although self-reports should remain the cornerstone of adherence assessment.

Rationale, aims and objectivesTo assess the impact of an automated drug distribution system on medication errors (MEs).MethodsBefore-after observational study in a 40-bed short stay geriatric unit within a 1800 bed general hospital in Valenciennes, France. Researchers attended nurse medication administration rounds and compared administered to prescribed drugs, before and after the drug distribution system changed from a ward stock system (WSS) to a unit dose dispensing system (UDDS), integrating a unit dose dispensing robot and automated medication dispensing cabinet (AMDC).ResultsA total of 615 opportunities of errors (OEs) were observed among 148 patients treated during the WSS period, and 783 OEs were observed among 166 patients treated during the UDDS period. ME [medication administration error (MAE)] rates were calculated and compared between the two periods. Secondary measures included type of errors, seriousness of errors and risk reduction for the patients. The implementation of an automated drug dispensing system resulted in a 53% reduction in MAEs. All error types were reduced in the UDDS period compared with the WSS period (P < 0.001). Wrong dose and wrong drug errors were reduced by 79.1% (2.4% versus 0.5%, P = 0.005) and 93.7% (1.9% versus 0.01%, P = 0.009), respectively.ConclusionAn automated UDDS combining a unit dose dispensing robot and AMDCs could reduce discrepancies between ordered and administered drugs, thus improving medication safety among the elderly.