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  5. ​​Data-informed Models to Identify Optimal Opioid Use Disorder Treatment Trajectories
  1. Advancing Regulatory Science

​​Data-informed Models to Identify Optimal Opioid Use Disorder Treatment Trajectories

CERSI Collaborators: University of Maryland: Danya Qato, PharmD, MPH, PhD (PI); Bethany DiPaula, Pharm.D., BCPP, FASHP; Megan J. Ehret, PharmD, MS, BCPP

FDA Collaborators: Sara Eggers, PhD; Reza Kazemi-Tabriz, PhD; Blair Coleman, PhD, MPH

Project Start Date: July 1, 2020

Regulatory Science Challenge

As the public health crisis of opioid use and misuse continues and the urgency for greater access to treatment for Opioid Use Disorder (OUD) is amplified, there is critical need to characterize determinants and time-trends in OUD treatment utilization, treatment continuation, and successful health outcomes. Despite the tremendous progress made in our understanding of opioid use and misuse, there remain gaps in our collective knowledge of the current state of trajectories of OUD treatment interventions, especially over time. This project, in collaboration with the FDA Center for Drug Evaluation and Research (CDER), seeks to leverage the collective expertise in pharmacoepidemiology (the study of the effects of drugs in a large population), clinical pharmacy and health services research at the University of Maryland School of Pharmacy and School of Medicine to utilize large nationally representative public and private claims data to characterize patterns of initiation, maintenance, and continuation of OUD treatment and outcomes by OUD severity level over time. Such evidence-based information is beneficial to model and predict progression of OUD, optimize treatment, target treatment to the most at risk, and develop policies that mitigate harm and bridge gaps in care.

Project Description and Goals

The primary goal of this project is to support the FDA's CDER effort to develop a data-driven systems model of the opioid crisis by providing summary-level data that can be incorporated into the model using a diversity of datasets that cut across the privately and publicly insured.

While the FDA has focused other efforts on better explaining the trajectory from opioid use initiation to OUD, our focus in this proposal is to enhance models by illuminating factors associated with OUD treatment trajectories and the differential impact of modality type on treatment remission and recovery. Our work focuses on the chronic (and relapsing) nature of OUD and the cyclical nature of treatment and will thus expand the scope of previously conducted research by characterizing patterns and outcomes associated with single and multiple sequential treatment modalities over time. Such an approach provides a more textured understanding of the natural history of OUD treatment in the long term.

Specifically, in this project, we seek to utilize longitudinal data (data obtained from the same sample subject across multiple points in time) from the publicly insured and commercially insured adult population to characterize temporal patterns of treatment modalities and examine the differential impact of patterns of treatment modalities on critical health outcomes over time.

This work fits squarely within the FDA’s effort to develop methods and tools to improve and streamline clinical and post-marketing evaluation including specifically improving “approaches to leveraging large, complex data to inform regulatory decision-making, including the use of real-world data sources. In 2018, FDA's Center for Drug Evaluation and Research (CDER) began an effort to develop a comprehensive systems model of the opioid crisis. The purpose of the model is to help FDA better understand a) the complexity of the underlying mechanisms of the crisis, and b) potential impacts – including desired outcomes and unintended consequences— of possible policy actions. The anticipated research impact of University of Maryland CERSI’s (M-CERSI) proposed work will be to: 1) inform FDA’s opioid modeling efforts that help with identifying potential high-impact interventions, assessing intended and potential unintended consequences of policies, and identifying needs for further research; and 2) to contribute to the broader public health knowledge of the current state of OUD treatment.

M-CERSI will be responsible for achieving the goals and objectives of this project, including convening of project meetings, submission of Data Use Agreements (DUAs), data stewardship, study design, study conduct, and data analysis, and preparation of manuscripts and dissemination of findings. Pharmaceutical Research Computing (PRC) is housed in the same department as the Primary Investigator (PI) and has extensive experience with data stewardship. PRC will be responsible to serve as custodians of the data and to support development of analytic files based on the guidance of the M-CERSI team and the FDA.

 

 
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