Causality Assessment in Pharmacovigilance: Still a Challenge

Causality in pharmacovigilance is a difficult and time consuming exercise. This paper presents the challenges in determining causation by drug therapy. The first is that causation is complex and needs to be viewed from the context of the patient treated, rather than the drug product. Multiple causal...

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Bibliographic Details
Published in:Drug safety 2017-05, Vol.40 (5), p.365-372
Main Author: Ralph Edwards, I.
Format: Article
Language:English
Subjects:
Algorithms
Causality
Causation
Consumer protection
Current Opinion
Data processing
Drug Safety and Pharmacovigilance
Drugs
E-books
Epidemiology
Guillain-Barre syndrome
Hypotheses
Hypothesis testing
International organizations
Medical errors
Medicine
Medicine & Public Health
Messages
Minority & ethnic groups
Neural networks
Norms
Outliers (statistics)
Patients
Pharmacology
Pharmacology/Toxicology
Pharmacovigilance
Public health
Risk analysis
Risk factors
Therapy
Transparency
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Summary:Causality in pharmacovigilance is a difficult and time consuming exercise. This paper presents the challenges in determining causation by drug therapy. The first is that causation is complex and needs to be viewed from the context of the patient treated, rather than the drug product. Multiple causal vectors should be considered if we are to tackle the many issues involved in, for example, medication error and the many other factors that lead to bad outcomes from therapy, including failure to recognise known risk factors. The aim of pharmacovigilance is not only a bureaucratic exercise in public health norms, but is mainly concerned with small minorities of statistical outliers—and even individuals—whose experiences from harms may together form messages about causation that will prevent further at-risk patients from exposure, or at least assist with earlier recognition of drug-related harm and better management of such harm. This requires more time, more data, more analysis and more patient and clinical involvement in reporting useful clinical detail. The paradigm shift back towards gathering more case data relating to possible causation can be selective and would not be just retrogressive, nor necessarily too costly. Greater transparency of hypotheses and availability of anonymised case data will enrol more expertise into evaluations and hypothesis testing, and the provision of more complete and useful information should reduce clinical burdens from bad patient outcomes as well as their overall costs to society.
ISSN:0114-5916
1179-1942
DOI:10.1007/s40264-017-0509-2