The prevalence and Nature of Prescribing and Monitoring Errors in English General Practice: a retrospective case note review - Avery, Anthony J.; Franklin, Bryony Dean; Armstrong, Sarah J.; Serumaga, Brian; Talabi, Olanrewaju; Mehta, Rajnikant L. (British Journal of General Practice, 2013)
Relatively little is known about prescribing errors in general practice, or the factors associated with error. To determine the prevalence and nature of prescribing and monitoring errors in general practices in England. Retrospective case-note review of unique medication items prescribed over a 12-month period to a 2% random sample of patients. Fifteen general practices across three primary care trusts in England. A total of 6048 unique prescription items prescribed over the previous 12 months for 1777 patients were examined. The data were analysed by mixed effects logistic regression. The main outcome measures were prevalence of prescribing and monitoring errors, and severity of errors, using validated definitions. Prescribing and/or monitoring errors were detected in 4.9% (296/6048) of all prescription items (95% confidence interval [CI] = 4.4% to 5.5%). The vast majority of errors were of mild to moderate severity, with 0.2% (11/6048) of items having a severe error. After adjusting for covariates, patient-related factors associated with an increased risk of prescribing and/or monitoring errors were: age <15 years (odds ratio [OR] = 1.87, 95% CI = 1.19 to 2.94, P = 0.006) or >64 years (OR = 1.68, 95% CI = 1.04 to 2.73, P = 0.035), and higher numbers of unique medication items prescribed (OR = 1.16, 95% CI = 1.12 to 1.19, P<0.001). Prescribing and monitoring errors are common in English general practice, although severe errors are unusual. Many factors increase the risk of error. Having identified the most common and important errors, and the factors associated with these, strategies to prevent future errors should be developed, based on the study findings.
Keywords: primary health care; general practice; prevalence; medication errors