Introduction: Adverse drug events (ADEs) may represent an important item of expenditure for healthcare systems and their prevention could be associated with a relevant cost saving.
Objective: The objective of this study was to simulate the annual economic burden for ADEs in Tuscany (Italy) and the potential cost savings related to avoidable ADEs.
Methods: A systematic review was performed, according to the Preferred Reporting Items for Systematic review and Meta-Analysis (PRISMA) and Meta-analysis Of Observational Studies in Epidemiology (MOOSE) statements, on observational studies published from 2006 to 2016 in MEDLINE and EMBASE, focusing on direct costs of ADEs in the inpatient setting from high-income countries. The mean probability of preventable ADEs was estimated over the included studies. The mean ADE cost was calculated by means of Monte Carlo simulation. We then extrapolated the spontaneous reports of ADEs in Tuscany, Italy in 2016 from the Italian National Pharmacovigilance Network (Rete Nazionale di Farmacovigilanza), and we assumed the same costs and preventability probability for these as obtained in the systematic review. Finally, we simulated the possible costs of ADEs and preventable ADEs in Tuscany. Three sensitivity analyses were also performed to test the robustness of the results.
Results: Of 11,936 articles initially selected, 12 observational studies were included. The estimated mean [± standard deviation (SD)] ADE cost was €2471.46 (± €1214.13). The mean (± SD) probability of preventable ADEs was 45% (± 21). The Tuscan expenditure for ADEs was €3,406,280.63 per million inhabitants (95% confidence interval (CI) 1,732,910.44-5,079,664.61) and the potential cost saving was €1,532,760.25 per million inhabitants (95% CI 779,776.1-2,285,750.60). Sensitivity analyses confirmed the robustness of the results.
Conclusions: The present simulation showed that ADEs could have a relevant economic impact on the Tuscan healthcare system. In this setting, the prevention of ADEs would result in important cost savings. These results could be likely extended to other healthcare systems.
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