INCIDENCE OF PRESCRIBING ERRORS IN HOSPITALIZED PATIENTS IN SAUDI ARABIA

Author(s)

Mahmoud MA1, Aljadhey H2, Hassali MA1
1Universiti Sains Malaysia, Penang, Malaysia, 2King Saud University, Riyadh, Saudi Arabia

OBJECTIVES: The aim of this study was to determine the incidence of prescribing errors using a validated definition and assess their severity and identify contributing factors METHODS: This was a 4 month retrospective chart review study. Patients admitted to medical, surgical and intensive care units (ICU) and aged 12 years or older were included in the study. The main study outcomes were the percentage of medication orders and hospital admissions with prescribing errors; and the types of prescribing errors. The secondary study outcomes were the severity of prescribing errors determined by two independent reviewers using the National Coordination Council for Medication Errors Reporting and Prevention (NCC MERP) index and patient’s related factors associated with prescribing errors.  RESULTS: A total of 691 prescribing errors were identified in 2,033 patients’ files. The incidence of prescribing errors was 3.6 (95% CI, 3.3 - 3.9) per 100 prescriptions, 33.9 (95% CI, 31.5 - 36.6) per 100 admissions and 76.5 (95% CI, 70.9 - 82.3) per 1000 patients days. The most commonly identified prescribing errors type was dosing errors (127; 18.4%) with 74 overdoses and 53 under doses. Antibiotic (230; 33.3%) was the most common drug class involved with prescribing errors. Out of the identified prescribing errors 20 (2.9%) were judged to be actual, 330(47.8%) potential and 341(49.3%) prescribing errors with no harm. Prescribing errors were significantly most common in surgical unit compared to the other study units (P<0.001)with small effect size (Eta = 0.089) and (Carmer’s v = 0.089). There was a significant differences in the mean length of hospital stay between those who had prescribing errors 5.42 (±6.26) days and those who didn’t 4.04 (±4.01) days (p<0.001).  CONCLUSIONS: The study has identified important prescribing errors and their associated factors and based on these findings strategies to prevent future errors should be developed.

Conference/Value in Health Info

2016-05, ISPOR 2016, Washington DC, USA

Value in Health, Vol. 19, No. 3 (May 2016)

Code

PRM1

Topic

Clinical Outcomes

Topic Subcategory

Clinical Outcomes Assessment

Disease

Multiple Diseases

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