Abstract
Background & objectivesDifferent algorithms have been developed to standardize the causality assessment of adverse drug reactions (ADR). Although most share common characteristics, the results of the causality assessment are variable depending on the algorithm used. Therefore, using 10 different algorithms, the study aimed to compare inter-rater and multi-rater agreement for ADR causality assessment and identify the most consistent to hospitals.MethodsUsing ten causality algorithms, four judges independently assessed the first 44 cases of ADRs reported during the first year of implementation of a risk management service in a medium complexity hospital in the state of Sao Paulo (Brazil). Owing to variations in the terminology used for causality, the equivalent imputation terms were grouped into four categories: definite, probable, possible and unlikely. Inter-rater and multi-rater agreement analysis was performed by calculating the Cohen´s and Light´s kappa coefficients, respectively.ResultsNone of the algorithms showed 100% reproducibility in the causal imputation. Fair inter-rater and multi-rater agreement was found. Emanuele (1984) and WHO-UMC (2010) algorithms showed a fair rate of agreement between the judges (k = 0.36).Interpretation & conclusionsAlthough the ADR causality assessment algorithms were poorly reproducible, our data suggest that WHO-UMC algorithm is the most consistent for imputation in hospitals, since it allows evaluating the quality of the report. However, to improve the ability of assessing the causality using algorithms, it is necessary to include criteria for the evaluation of drug-related problems, which may be related to confounding variables that underestimate the causal association.
Highlights
IntroductionSince the 1970s, different methods to standardize the evaluation of the causal association of adverse drug reaction (ADR) have been available, ranging from small questionnaires to comprehensive algorithms[2]
The adverse drug reaction (ADR) causality assessment is a routine procedure in Pharmacovigilance[1], because it allows assessing drug safety parameters and the relationship and likelihood between drug exposure and the occurrence of ADR of health technologies in the post-marketing period.Since the 1970s, different methods to standardize the evaluation of the causal association of ADRs have been available, ranging from small questionnaires to comprehensive algorithms[2].The development of these tools, which are ordinary to use[3] and require minimal expertise to be employed[1,4], aims to solve methodological bias, reliability, and validity issues in the imputation of drug-induced adverse effects[5]
The ADR causality assessment algorithms were poorly reproducible, our data suggest that World Health Organization (WHO)-UMC algorithm is the most consistent for imputation in hospitals, since it allows evaluating the quality of the report
Summary
Since the 1970s, different methods to standardize the evaluation of the causal association of ADRs have been available, ranging from small questionnaires to comprehensive algorithms[2] The development of these tools, which are ordinary to use[3] and require minimal expertise to be employed[1,4], aims to solve methodological bias, reliability, and validity issues in the imputation of drug-induced adverse effects[5]. Establishing a causal link may influence the rationale for the correlation of an event that occurs to drug consumers[7]; the results of the causality assessments using algorithms must be reproducible This is important to ratify the viability of their employment in pharmacovigilance[8], as well as their capacity to detect ADR signals[9,10]. Using 10 different algorithms, the study aimed to compare inter-rater and multi-rater agreement for ADR causality assessment and identify the most consistent to hospitals
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