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HSyE Receives Funding for Continued Mitigation on U.S. Opioid Epidemic

October 16, 2018

James Benneyan, MIE Professor & Director of the Healthcare Systems Engineering Institute, received a $450K NIH/NIDA award for "Model-Informed Understanding and Mitigation of the U.S. Opioid and Heroin Epidemic." The grant will continue HSyE's work on the U.S. opioid epidemic, building on their current NSF grant to develop multi-scale computational models of the epidemic past and future spread.

Abstract Source: NIH

This proposal aims to develop, validate, and apply systems engineering models of the opioid-heroin epidemic to help evaluate, inform, and optimize effective policies to mitigate this growing problem. As highlighted by the U.S. Surgeon General, Secretary of Health and Human Services, and President Trump, this complex epidemic is affecting nearly all strata of the society, with profound social (3.8 million illicit users), financial ($78.5 billion), and health (420,000 overdoses and 33,000 deaths / year) impacts, and significant regional and socioeconomic disparities. Opioid-related deaths have more than quadrupled since 1999, at sharply higher rates since 2010, and with no indication of abating. Despite the enormity of this crisis, effective strategies remain elusive, often insufficiently addressing the inherent interactions and dynamics by which prescribing occurs, abuse begins and spreads, treatment is sought and provided, and substance availability and market forces affect behaviors. System science models are increasingly advocated by the National Academy of Medicine, National Institutes of Health, Agency for Healthcare Research and Quality, and others to help solve such complex issues, but have not yet been applied to the opioids epidemic. To address this gap, the proposed research aims to develop sys- tems engineering models at each phase of the drug use continuum (initiation, dependency, treatment) and pilot their use in multiple settings for robustness. Specific aims include: (1) develop and validate preliminary system dynamics, agent-based, capacity optimization, and discrete event logistics models across each phase; (2) con- duct pilot analysis using these models to identify insights and structural relationships, rapidly generate and test hypotheses, and estimate intervention effectiveness and consequences; and (3) generalize and expand results beyond the initial pilot applications, including identification of a larger technical and policy research agenda. The overarching objective is to use the envisioned models to gain knowledge about causality and dynamics for each phase, and to then investigate and inform effective interventions, resource allocations, and policies. While the planned work will be largely model-based, the proposed engineer-clinician research team will rely on feed- back from a diverse stakeholder advisory committee (comprising of behavioral health, primary care, addiction treatment, substance abuse, and policy experts drawing from several states and care systems) to validate the developed models and explore feasible intervention strategies. Anticipated outcomes include: (1) validated pre- scribing, abuse spread, and treatment models with demonstrated robustness in multiple settings and scales as well as broader applicability to other multi-substance phenomena; and (2) useful insights, explanatory hypothe- ses, and analysis of proposed polices and interventions that can meaningfully impact the opioid epidemic.