# Novel Econometric Research Designs (NERD) to Help End Addiction Long-term

> **NIH NIH DP2** · WEILL MEDICAL COLL OF CORNELL UNIV · 2024 · $2,542,500

## Abstract

PROJECT SUMMARY/ABSTRACT
Opioid use disorder (OUD) is a public health emergency impacting the lives of an estimated 5.6 million individuals
in the United States. OUD is a particular concern for vulnerable populations (e.g., pregnant women, criminal-
legal system involved populations, etc.), where the barriers to evidence-based care and the economic burden
remain significant. Randomized controlled trials (RCTs) are considered the gold standard for identifying causal
treatment effects and is the primary scientific tool to inform clinical decisions. RCT research designs are also
growing in use for conducting robust health economic studies to ensure that evidence-based treatments can be
cost-effective and sustainable—reaching the broadest number of individuals with OUD while efficiently using
scarce healthcare resources. As such, health economic RCT research designs have become a critical tool in
identifying sustainable and cost-effective solutions to prevent and mitigate the opioid epidemic. The NIH HEAL
initiative has championed such research by funding economic evaluations alongside clinical trials in the Healing
Communities Study, NIDA's Clinical Trials Network (CTN) and Justice Community Opioid Innovation Network
(JCOIN), and The HEAL Prevention Cooperative (HPC), among others. Traditional RCTs have demonstrated
the effectiveness of medications for OUD (MOUD) but have limitations in addressing the unique needs of these
populations. Real-world data and evidence (RWE) research designs that use observational data from healthcare
claims, electronic medical records, and other sources have been used to answer critical questions in medicine
that are difficult or impossible to implement in equivalent RCTs. The 21st Century CURES Act reaffirmed the use
of RWE and provided greater research flexibility of data sources for the FDA drug approval process. Despite
this, significant concerns remain about the reliability of RWE due to its observational nature and potential for
confounding bias. To address these concerns, RCTs have been used to inform RWE research designs (e.g., the
popular “target RCT” framework) and augment RWE findings. The alternative and unconventional approach of
integrating RWE to inform inconclusive RCTs to support robust and causal conclusions that can inform clinical
practice has been systematically ignored but represents a potential opportunity to reduce research waste and
produce more reliable findings to inform clinical decision-making and improve outcomes for at-risk populations
with OUD. This project will develop novel econometric methods and unified framework for integrating RWE in
the analysis of inconclusive RCTs by adapting existing econometric and biostatistical techniques into
comparative economic and effectiveness assessments of OUD treatments conducted alongside RCTs. The
project will evaluate multiple maximum likelihood estimation (MLE) approaches combined with propensity score-
based causal inference methodologies to achi...

## Key facts

- **NIH application ID:** 10846091
- **Project number:** 1DP2DA062283-01
- **Recipient organization:** WEILL MEDICAL COLL OF CORNELL UNIV
- **Principal Investigator:** Ali Jalali
- **Activity code:** DP2 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $2,542,500
- **Award type:** 1
- **Project period:** 2024-09-01 → 2027-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10846091

## Citation

> US National Institutes of Health, RePORTER application 10846091, Novel Econometric Research Designs (NERD) to Help End Addiction Long-term (1DP2DA062283-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10846091. Licensed CC0.

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