Cross-sectional study of prescribing errors in patients admitted to nine hospitals across North West England

Abstract

Objective: To evaluate the prevalence, type and severity of prescribing errors observed between grades of prescriber, ward area, admission or discharge and type of medication prescribed.

Design: Ward-based clinical pharmacists prospectively documented prescribing errors at the point of clinically checking admission or discharge prescriptions. Error categories and severities were assigned at the point of data collection, and verified independently by the study team.

Setting: Prospective study of nine diverse National Health Service hospitals in North West England, including teaching hospitals, district hospitals and specialist services for paediatrics, women and mental health.

Results: Of 4238 prescriptions evaluated, one or more error was observed in 1857 (43.8%) prescriptions, with a total of 3011 errors observed. Of these, 1264 (41.9%) were minor, 1629 (54.1%) were significant, 109 (3.6%) were serious and 9 (0.30%) were potentially life threatening. The majority of errors considered to be potentially lethal (n=9) were dosing errors (n=8), mostly relating to overdose (n=7). The rate of error was not significantly different between newly qualified doctors compared with junior, middle grade or senior doctors. Multivariable analyses revealed the strongest predictor of error was the number of items on a prescription (risk of error increased 14% for each additional item). We observed a high rate of error from medication omission, particularly among patients admitted acutely into hospital. Electronic prescribing systems could potentially have prevented up to a quarter of (but not all) errors.

Conclusions: In contrast to other studies, prescriber experience did not impact on overall error rate (although there were qualitative differences in error category). Given that multiple drug therapies are now the norm for many medical conditions, health systems should introduce and retain safeguards which detect and prevent error, in addition to continuing training and education, and migration to electronic prescribing systems.

Figure 1

Forest plot showing prescribing error rates in nine hospitals across North West England.

Figure 2

Categories of prescribing errors made by different grades of prescriber.

Figure 3

Forest plot showing prescribing error rates made by different prescriber grades.