Drug safety
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Comparative Study Observational Study
A Comparative Assessment of Observational Medical Outcomes Partnership and Mini-Sentinel Common Data Models and Analytics: Implications for Active Drug Safety Surveillance.
An often key component to coordinating surveillance activities across distributed networks is the design and implementation of a common data model (CDM). The purpose of this study was to evaluate two drug safety surveillance CDMs from an ecosystem perspective to better understand how differences in CDMs and analytic tools affect usability and interpretation of results. ⋯ Differences were observed between OMOP and Mini-Sentinel CDMs. The analysis of both CDMs at the data model level indicated that such conceptual differences had only a slight but not significant impact on identifying known safety associations. Our results show that differences at the ecosystem level of analyses across the CDMs can lead to strikingly different risk estimations, but this can be primarily attributed to the choices of analytic approach and their implementation in the community-developed analytic tools. The opportunities of using CDMs are clear, but our study shows the need for judicious comparison of analyses across the CDMs. Our work emphasizes the need for ongoing efforts to ensure sustainable transparent platforms to maintain and develop CDMs and associated tools for effective safety surveillance.
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What has been learned about electronic health data as a primary data source for regulatory decisions regarding the harms of drugs? Observational studies with electronic health data for postmarket risk assessment can now be conducted in Europe and the US in patient populations numbering in the tens of millions compared with a few hundred patients in a typical clinical trial. With standard protocols, results can be obtained in a few months; however, extensive research published by scores of investigators has illuminated the many obstacles that prevent obtaining robust, reproducible results that are reliable enough to be a primary source for drug safety decisions involving the health and safety of millions of patients. The most widely used terminology for coding patient interactions with medical providers for payment has proved ill-suited to identifying the adverse effects of drugs. ⋯ Evaluation of some accepted statistical methods revealed systematic bias, while others appeared to be unreliable. When electronic health data studies detected no drug risk, there were no robust and accepted standards to judge whether the drug was unlikely to cause the adverse effect or whether the study was incapable of detecting it. Substantial investment and careful thinking is needed to improve the reliability of risk assessments based on electronic health data, and current limitations need to be fully understood.
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Information technology (IT) has the potential to prevent medication errors. While many studies have analyzed specific IT technologies and preventable adverse drug events, no studies have identified risk factors for errors still occurring that are not preventable by IT. ⋯ Despite extensive IT implementation at the studied institution, approximately one-half of the medication errors identified by voluntarily reporting or a trigger tool system were not preventable by the utilized IT systems. Inappropriate use of IT systems was a common cause of errors. The identified risk factors represent areas where IT safety features were lacking.
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Randomized Controlled Trial
Effect of an educational intervention to improve adverse drug reaction reporting in physicians: a cluster randomized controlled trial.
The yellow-card scheme continues to be one of the principal methods for signal generation in pharmacovigilance. Nevertheless, under-reporting, one of its disadvantages, delays alert signals and has a negative influence on public health. Educational interventions in pharmacovigilance may have a positive impact on the spontaneous reporting of adverse drug reactions (ADRs). ⋯ Pharmacovigilance educational interventions that have proved effective can be successfully applied in different geographical areas. A high baseline notification rate could account for the educational program having a moderate effect.
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Review
Benefits and risks of using smart pumps to reduce medication error rates: a systematic review.
Smart infusion pumps have been introduced to prevent medication errors and have been widely adopted nationally in the USA, though they are not always used in Europe or other regions. Despite widespread usage of smart pumps, intravenous medication errors have not been fully eliminated. ⋯ The literature suggests that smart pumps reduce but do not eliminate programming errors. Although the hard limits of a drug library play a main role in intercepting medication errors, soft limits were still not as effective as hard limits because of high override rates. Compliance in using smart pumps is key towards effectively preventing errors. Opportunities for improvement include upgrading drug libraries, developing standardized drug libraries, decreasing the number of unnecessary warnings, and developing stronger approaches to minimize workarounds. Also, as with other clinical information systems, smart pumps should be implemented with the idea of using continuous quality improvement processes to iteratively improve their use.