Background: Quantitative prospective methods are widely used to evaluate the impact of new technologies such as electronic prescribing (eP) on medication errors. However, they are labour-intensive and it is not always feasible to obtain pre-intervention data. Our objective was to compare the eP medication error picture obtained with retrospective quantitative and qualitative methods. Methods: The study was carried out at one English district general hospital approximately two years after implementation of an integrated electronic prescribing, administration and records system. Quantitative: A structured retrospective analysis was carried out of clinical records and medication orders for 75 randomly selected patients admitted to three wards ( medicine, surgery and paediatrics) six months after eP implementation. Qualitative: Eight doctors, 6 nurses, 8 pharmacy staff and 4 other staff at senior, middle and junior grades, and 19 adult patients on acute surgical and medical wards were interviewed. Staff interviews explored experiences of developing and working with the system; patient interviews focused on experiences of medicine prescribing and administration on the ward. Interview transcripts were searched systematically for accounts of medication incidents. A classification scheme was developed and applied to the errors identified in the records review. Results: The two approaches produced similar pictures of the drug use process. Interviews identified types of error identified in the retrospective notes review plus two eP-specific errors which were not detected by record review. Interview data took less time to collect than record review, and provided rich data on the prescribing process, and reasons for delays or non-administration of medicines, including "once only" orders and "as required" medicines. Conclusions: The qualitative approach provided more understanding of processes, and some insights into why medication errors can happen. The method is cost-effective and could be used to supplement information from anonymous error reporting scheme
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