PubMed Health⌕ Search

PubMed · 17215468

Interrater agreement with a standard scheme for classifying medication errors.

Abstract

PURPOSE: The interrater agreement for and reliability of the National Coordinating Council for Medication Error Reporting and Prevention (NCC MERP) index for categorizing medication errors were determined. METHODS: A letter was sent by the U.S. Pharmacopeia to all 550 contacts in the MEDMARX system user database. Participants were asked to categorize 27 medication scenarios using the NCC MERP index and were randomly assigned to one of three tools (the index alone, a paper-based algorithm, or a computer-based algorithm) to assist in categorization. Because the NCC MERP index accounts for harm and cost, and because categories could be interpreted as substantially similar, study results were analyzed after the nine error categories were collapsed to six. The interrater agreement was measured using Cohen's kappa value. RESULTS: Of 119 positive responses, 101 completed surveys were returned for a response rate of 85%. There were no significant differences in baseline demographics among the three groups. The overall interrater agreement for the participants, regardless of group assignment, was substantial at 0.61 (95% confidence interval [CI], 0.41-0.81). There was no difference among the kappa values of the three study groups and the tools used to aid in medication error classification. When the index was condensed from nine categories to six, the interrater agreement increased with a kappa value of 0.74 (95% CI, 0.56-0.90). CONCLUSION: Overall interrater agreement for the NCC MERP index for categorizing medication errors was substantial. The tool provided to assist with categorization did not influence overall categorization. Further refining of the scale could improve the usefulness and validity of medication error categorization.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Ryan A Forrey, Craig A Pedersen, Philip J Schneider. 2007-01-15. Interrater agreement with a standard scheme for classifying medication errors.. https://doi.org/10.2146/ajhp060109

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Post Launch Monitoring of food products: what can be learned from pharmacovigilance.

Post Launch Monitoring (PLM) is one of the new approaches that are used in assessing the safety of novel foods or ingredients. It shares a close resemblance with procedures applied in the field of medicines, where Post Marketing Surveillance (PMS) has been carried out since the beginning of the 1960s. For this reason, Unilever and the Netherlands Pharmacovigilance Centre Lareb, maintaining the national reporting scheme in the Netherlands for adverse drug reactions, have been working together to optimize the Unilever's Post Launch Monitoring service. As a result of this cooperation a practical model for conducting PLM for food products has been developed. This model is also applicable for consumer products in general. The system allows for coding and assessing reports and the early detection of 'signals' of unintended health reactions. The methodological issues surrounding reporting of possible health reactions and practical issues surrounding coding and assessment of the reports that were encountered in the first period of this partnership are discussed. In addition, similarities and differences concerning PMS and PLM are described.

Adverse Drug Reaction Reporting Systems↗

An analysis of the exclusion criteria used in observational pharmacoepidemiological studies.

PURPOSE: The application of exclusion criteria in pharmacoepidemiological studies could have a major impact on the findings but there appears to have been no previous research to examine the types of exclusion criteria applied. METHODS: We searched the literature and identified 10 senior pharmacoepidemiologists who had published five or more relevant papers between 1999 and 2004. All their published drug safety studies during this period were reviewed. A classification system was developed to categorise the exclusion criteria, with 5 categories and 11 sub-categories. The categories were: (1) data quality and validation, (2) disease-related, (3) exposure-related, (4) patient characteristics and (5) miscellaneous reasons. Within each sub-category, only the first exclusion criterion identified for that study was counted. RESULTS: We identified 200 studies, from which a total of 752 exclusion criteria sub-categories had been applied (mean 3.8 per study; between-author range of means 2.8-5.1). At the category level, exclusion criteria relating to data quality and validation were the most commonly applied (87% of publications), followed by patient characteristics (75%), disease-related (69%), exposure-related (38%) and miscellaneous (3%). The main categories for which research practice appeared to differ were those relating to diseases and exposures. The application of sub-category 'risk factors and alternative causes' varied between authors from 0% to 81% of studies, and for the sub-category 'medication of interest' it varied from 5% to 93%. CONCLUSIONS: There are important differences between investigators in the application of exclusion criteria in pharmacoepidemiological studies. It is likely that a substantial part of the observed variation reflects different research practices of investigators.

Adverse Drug Reaction Reporting Systems↗