Strategies for automating pharmacovigilance adverse event case processing

Abstract

Introduction:In 2020, the U.S. Food & Drug Administration received reports of 2.2 million adverse events, which is a 350% increase since 2010 with an associated increase in pharmaceutical companies' pharmacovigilance (PV) operational cost. Guided by the task technology fit model as the conceptual framework, the purpose of this qualitative single case study was to explore strategies used by PV systems leaders to implement innovative technology solutions. The objective of the study was to develop a system model to explore strategies to implement innovative technology to automate AE detection, processing, and reporting. Methods: Data were collected using semistructured interviews and company data to address the research question on strategies to implement innovative technology solutions to automate adverse events case processing. The collected data was analyzed using 5-step data analysis, compiling, disassembling, reassembling, interpreting data, and concluding the findings. Results: The implications for positive social change include the potential to identify strategies in making pharmaceutical medicines safer for human consumption. Discussion: PV leaders can redirect the savings from PV operations in terms of cost and workforce tasks towards investing in the actual PV tasks like benefit-risk assessments of products; thereby, improving patient outcomes and making the products more efficacious and safer for human use.

Development and Usability Testing of a System to Detect Adverse Events and Medical Mistakes

“…24 This approach toward automated contextual information retrieval could also make it more possible for AE review systems to shift from primarily being a retrospective chart review activity to a prospective system with potential for continual review and intervention before an AE or harm occurs. Easwar and colleagues 25 observed that with respect to pharmacovigilance, by automating AE surveillance systems, savings can be redirected toward interventions that decrease AEs. To explore this, they conducted a qualitative study interviewing pharmacovigilance managers about strategies for technology implementations.…”

“…To explore this, they conducted a qualitative study interviewing pharmacovigilance managers about strategies for technology implementations. They found that automation freed up workforce members from redundant tasks, allowing them to focus on more value-added tasks including process improvement activities 25 . Automated systems can remove reporting bias as well; Pascal metrics has built a “Virtual Safety System,” which continuously measures all-cause harm across all patients, an approach they refer to as “social determinants of safety.” At the core of their system is a focus on AE outcomes data versus proxy data such as incident reporting and billing data.…”