Prescribing errors during hospital inpatient care: factors influencing identification by pharmacists

Pharm World Sci. 2009 Dec;31(6):682-8. doi: 10.1007/s11096-009-9332-x. Epub 2009 Sep 24.


Objective: To investigate the prevalence of prescribing errors identified by pharmacists in hospital inpatients and the factors influencing error identification rates by pharmacists throughout hospital admission.

Setting: 880-bed university teaching hospital in North-west England.

Methods: Data about prescribing errors identified by pharmacists (median: 9 (range 4-17) collecting data per day) when conducting routine work were prospectively recorded on 38 randomly selected days over 18 months.

Main outcome measures: Proportion of new medication orders in which an error was identified; predictors of error identification rate, adjusted for workload and seniority of pharmacist, day of week, type of ward or stage of patient admission.

Results: 33,012 new medication orders were reviewed for 5,199 patients; 3,455 errors (in 10.5% of orders) were identified for 2,040 patients (39.2%; median 1, range 1-12). Most were problem orders (1,456, 42.1%) or potentially significant errors (1,748, 50.6%); 197 (5.7%) were potentially serious; 1.6% (n = 54) were potentially severe or fatal. Errors were 41% (CI: 28-56%) more likely to be identified at patient's admission than at other times, independent of confounders. Workload was the strongest predictor of error identification rates, with 40% (33-46%) less errors identified on the busiest days than at other times. Errors identified fell by 1.9% (1.5-2.3%) for every additional chart checked, independent of confounders.

Conclusions: Pharmacists routinely identify errors but increasing workload may reduce identification rates. Where resources are limited, they may be better spent on identifying and addressing errors immediately after admission to hospital.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Clinical Competence
  • England
  • Hospitalization
  • Hospitals, University
  • Humans
  • Inpatients*
  • Logistic Models
  • Medication Errors / prevention & control*
  • Medication Systems, Hospital*
  • Odds Ratio
  • Personnel Staffing and Scheduling
  • Pharmacists*
  • Pharmacy Service, Hospital*
  • Prescription Drugs / adverse effects
  • Prescription Drugs / therapeutic use*
  • Professional Role*
  • Prospective Studies
  • Risk Assessment
  • Risk Factors
  • Time Factors
  • Workload*


  • Prescription Drugs