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  1. Advancing Regulatory Science

Community-Level Simulation of Opioid-Related Health Outcomes

CERSI Collaborators: Richard (Andrew) Taylor, MD, MHS (Yale PI); Jeromie Ballreich, PhD (JHU PI); Joseph Ross, MD, MHS (Main Yale CERSI PI); Molly Jeffery, PhD (Main Yale CERSI PI); Caleb Alexander, MD, MS (Main JHU PI); Michelle Bernabeo (Yale PM)

FDA Collaborators: Center for Drug Evaluation and Research: Mitra Ahadpour, MD, DABAM; Rashedul Hasan, Ph.D.; Robert Whetsel, DCS., MSCS

Project Start: September 10, 2021

Regulatory Science Challenge

The Opioid Use Disorder (OUD) epidemic has gripped numerous communities, necessitating comprehensive strategies to identify and assist vulnerable populations. FDA is exploring the utility of an Agent-Based Model (ABM) to identify vulnerable populations affected by the OUD epidemic and deepen its understanding of OUDs. An ABM is a computer simulation that analyzes systems through the interactions of individual agents. Individual agents in an ABM can be people, households, vehicles, equipment, or products – whichever is relevant to the system. Connections between them are formed, environmental variables are assigned, and the computer simulation is then run. The results that emerge from the interactions of the many individual agent behaviors predict the most probable outcomes. The ABM under development at FDA in the context of OUD will integrate micro-level population characteristics, incorporate vital aspects such as demographics, policy, and applications using real-world data, and potentially reflect true community dynamics leveraging census data.

The regulatory science issue here lies in refining and validating the ABM to effectively simulate and project OUD's nuanced patterns and implications within communities. This includes using electronic health data to synthesize a real-world simulation that could provide invaluable insights into OUD health outcomes, preventive measures, and treatment protocols, particularly in small communities. The data resulting from the ABM simulation, may inform policy-making and regulatory planning. The ABM has the potential to target prevention and intervention strategies more effectively, ultimately aiming to mitigate the pervasive and detrimental impacts of the OUD epidemic.

Project Description and Goals

The ongoing project seeks to explore integrating data from electronic health records (EHRs) from a specific subset of OUD patients treated at the INOVA Hospital System in Alexandria, Virginia, and community data from the City of Alexandria.

The study aims to:

  • Explore the applicability of ABM to this problem through literature exploration and comparison with other models.
  • Determine and document evaluation methods for the ABM, considering clinical and modeling expertise and available data.
  • Evaluate the developed ABM, scrutinizing its potential risks and benefits.
  • Propose recommendations to enhance its accuracy relative to alternative models.

The methodology used to achieve these objectives will include a study with a comprehensive investigation and documentation process, which involves:

  • Employing EHRs encapsulating patient admission and treatment data to substantiate the ABM.
  • Conducting verification of projected outcomes based on defined data elements and flows.
  • Assessing misuse profiles and their capability to inform the definition of an EHR search strategy for OUD.
  • Defining and evaluating clinical and demographic outcomes.
  • Assessing real-world data from the community.

Investigators will investigate this question by:

  • Deploying a systematic and comparative analysis of the ABM with alternative models, utilizing available literature.
  • Implementing diverse evaluation strategies, including verifying projected outcomes, assessing misuse profiles, and defining clinical and demographic outcomes, all based on acquired EHR data.

Finally, investigators will explore the developed ABM, carefully evaluate its creation, potential risks and benefits, and identify where its use is most appropriate and impactful.

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