@article{7195, author = {Derar H. Abdel-Qader and Lindsay Harper and Judith A. Cantrill and Mary P. Tully}, title = {Pharmacists' interventions in prescribing errors at hospital discharge: an observational study in the context of an electronic prescribing system in a UK teaching hospital.}, abstract = {

BACKGROUND: Pharmacists have an essential role in improving drug usage and preventing prescribing errors (PEs). PEs at the interface of care are common, sometimes leading to adverse drug events (ADEs). This was the first study to investigate, using a computerized search method, the number, types, severity, pharmacists' impact on PEs and predictors of PEs in the context of electronic prescribing (e-prescribing) at hospital discharge.

METHOD: This was a retrospective, observational, 4-week study, carried out in 2008 in the Medical and Elderly Care wards of a 904-bed teaching hospital in the northwest of England, operating an e-prescribing system at discharge. Details were obtained, using a systematic computerized search of the system, of medication orders either entered by doctors and discontinued by pharmacists or entered by pharmacists. Meetings were conducted within 5 days of data extraction with pharmacists doing their routine clinical work, who categorized the occurrence, type and severity of their interventions using a scale. An independent senior pharmacist retrospectively rated the severity and potential impact, and subjectively judged, based on experience, whether any error was a computer-related error (CRE). Discrepancies were resolved by multidisciplinary discussion. The Statistical Package for Social Sciences was used for descriptive data analysis. For the PE predictors, a multivariate logistic regression was performed using STATA 7. Nine predictors were selected a priori from available prescribers', patients' and drug data.

RESULTS: There were 7920 medication orders entered for 1038 patients (doctors entered 7712 orders; pharmacists entered 208 omitted orders). There were 675 (8.5% of 7920) interventions by pharmacists; 11 were not associated with PEs. Incidences of erroneous orders and patients with error were 8.0% (95% CI 7.4, 8.5 [n = 630/7920]) and 20.4% (95% CI 18.1, 22.9 [n = 212/1038]), respectively. The PE incidence was 8.4% (95% CI 7.8, 9.0 [n = 664/7920]). The top three medications associated with PEs were paracetamol (acetaminophen; 30 [4.8%]), salbutamol (albuterol; 28 [4.4%]) and omeprazole (25 [4.0%]). Pharmacists intercepted 524 (83.2%) erroneous orders without referring to doctors, and 70% of erroneous orders within 24 hours. Omission (31.0%), drug selection (29.4%) and dosage regimen (18.1%) error types accounted for >75% of PEs. There were 18 (2.9%) serious, 481 (76.3%) significant and 131 (20.8%) minor erroneous orders. Most erroneous orders (469 [74.4%]) were rated as of significant severity and significant impact of pharmacists on PEs. CREs (n = 279) accounted for 44.3% of erroneous orders. There was a significant difference in severity between CREs and non-CREs (χ2 = 38.88; df = 4; p < 0.001), with CREs being less severe than non-CREs. Drugs with multiple oral formulations (odds ratio [OR] 2.1; 95% CI 1.25, 3.37; p = 0.004) and prescribing by junior doctors (OR 2.54; 95% CI 1.08, 5.99; p = 0.03) were significant predictors of PEs.

CONCLUSIONS: PEs commonly occur at hospital discharge, even with the use of an e-prescribing system. User and computer factors both appeared to contribute to the high error rate. The e-prescribing system facilitated the systematic extraction of data to investigate PEs in hospital practice. Pharmacists play an important role in rapidly documenting and preventing PEs before they reach and possibly harm patients. Pharmacists should understand CREs, so they complement, rather than duplicate, the e-prescribing system's strengths.

}, year = {2010}, journal = {Drug Saf}, volume = {33}, pages = {1027-44}, month = {11/2010}, issn = {1179-1942}, doi = {10.2165/11538310-000000000-00000}, language = {eng}, }