Prescription Errors and the Impact of Computerized Prescription Order Entry System in a Community-based Hospital

Abstract

Adverse drug events occur often in hospitals. They can be prevented to a large extent by minimizing the human errors of prescription writing. To evaluate the efficacy of a computerized prescription order entry (CPOE) system with the help of ancillary support in minimizing prescription errors. Retrospective study carried out in a community-based urban teaching hospital in south Brooklyn, NY from January 2004 to January 2005. Errors were categorized into inappropriate dosage adjustment for creatinine clearance, duplication, incorrect orders, allergy verification, and incomplete orders. The pharmacists identified the type of error, the severity of error, the class of drug involved, and the department that made the error. A total of 466,311 prescriptions were entered in the period of 1 year. There were 3513 errors during this period (7.53 errors per 1000 prescriptions). More than half of these errors were made by the internal medicine specialty. In our study, 50% of the errors were severe errors (overdosing medications with narrow therapeutic index or over-riding allergies), 46.28% were moderate errors (overdosing, wrong dosing, duplicate orders, or prescribing multiple antibiotics), and 3.71% were not harmful errors (wrong dosing or incomplete orders). The errors were also categorized according to the class of medication. Errors in antibiotic prescription accounted for 53.9% of all errors. The pharmacist detected all these prescription errors as the prescriptions were reviewed in the CPOE system. Prescription errors are common medical errors seen in hospitals. The CPOE system has prevented and alerted the prescriber and pharmacist to dosage errors and allergies. Involvement of the pharmacist in reviewing the prescription and alerting the physician has minimized prescription errors to a great degree in our hospital setting. The incidence of prescription errors before the CPOE has been reported to range from 3 to 99 per 1000 prescriptions. The disparity could be due to the definition of medical errors, which has changed over the years, and also number of prescriptions included in the study and the study design.

An iconic language for the graphical representation of medical concepts

“…The installation of computerized physician order entry (CPOE) systems within hospitals may help to decrease the frequency of such errors [4-6], although an increase in errors was recently reported after the installation of such a system [7]. For maximal efficiency, CPOEs must be linked to decision-making systems using patient data encoded in the electronic patient record [8].…”

Evaluation of Diagnostic and Therapeutic Approaches for Suspected Influenza A(H1N1)pdm09 Infection, 2009–2010

“…We also did not include data from medical outpatient (nonemergency department) clinics where other patients with influenza may have been identified and treated, perhaps skewing our data to those who were more ill. As a retrospective study, our conclusions depend solely upon information documented in the medical record, which may be incomplete. Also, the use of an antiviral agent authorization form most likely improved the dosing practice, as has been shown in other settings ( 32 , 33 ). Last, our study population includes only a single academic medical center and therefore may not be representative of the region or the nation.…”

“…HUMC required the use of a preauthorization drug form that noted the appropriate age- and weight-based dose; an outpatient prescription for oseltamivir would not have been released without a completed form. Such tools have been shown to limit dosing errors ( 32 , 33 ). Also consistent with the CDC guidelines, >90% of hospitalized patients and patients with severe illness in our study received oseltamivir.…”

Auditing the Management of Vaccine-Preventable Disease Outbreaks: The Need for a Tool

“…Several studies have demonstrated that the adoption of electronic health records (EHR) can promote the quality of health care by reducing adverse events and improving management [21]; [22] in contrast with Keyhani et al [23] who conclude that further research on how EHR are implemented and how they will improve the understanding of theirimpact on the quality of care are needed. Other studies highlight the importance of electronic reporting systems in improving the timeliness and completeness of reporting notifiable diseases [24].…”