# The Economic Viability and Value of Implementing an Inpatient Addiction Consult Model in Public Hospital Systems for Patients with Opioid Use Disorder

> **NIH NIH R03** · WEILL MEDICAL COLL OF CORNELL UNIV · 2024 · $84,750

## Abstract

Project Summary
An estimated 1.6 million persons in the US suffer from an opioid use disorder (OUD), which costs society $787
billion a year resulting from excess healthcare expenditures and societal resources. Evidence-based treatments
for OUD have been shown to improve health and attenuate healthcare costs, but utilization continues to be low.
Models of hospital-inpatient addiction consultation and linkage to community-based treatment following
discharge have preliminarily demonstrated effectiveness; however, little is known about the economic value or
sustainability of such models in public hospital settings. In 2018, to improve post-discharge utilization of
evidence-based pharmacotherapy for OUD, New York City Health & Hospitals, the largest municipal hospital
system in the US, introduced the Consult for Addiction Treatment and Care in Hospitals (CATCH) intervention.
CATCH is an addiction consult model which evaluates individuals with an opioid-related hospitalization for OUD,
initiates pharmacotherapy when indicated, and directly links patients to post-discharge treatment. An ongoing
NIDA-funded hybrid effectiveness-implementation trial is evaluating CATCH with regard to increased treatment
engagement, acute care utilization, and collecting implementation outcomes within the Reach, Effectiveness,
Adoption, Implementation, and Maintenance (RE-AIM) framework, the most widely applied framework for
measuring the impact of an intervention in real world environments. The study’s economic component focuses
on estimating the intervention costs and potential cost-offsets resulting from reductions in acute care utilization
and premature mortality. However, the participant population is primary composed of Medicaid beneficiaries and
key stakeholders will benefit from expanded economic information (additional healthcare paid by Medicaid, social
safety-net expenditures funded via state budgets) and tools to evaluate the viability of CATCH in a representative
setting. This project will leverage the research infrastructure of the aforementioned study to substantially increase
the economic information available to stakeholders, most specifically those who are largely responsible for
making treatment-access decisions on behalf of the study population, i.e., policymakers. This project will
estimate the costs required to implement and sustain the CATCH intervention utilizing data already collected as
part of the parent study to build a customizable budget impact tool that allows costs to be calculated for each
component of the RE-AIM framework for stakeholders (e.g., other public hospitals). The project will also estimate
the economic value of CATCH relative to treatment-as-usual from a state policymaker perspective by
incorporating: 1) nationally representative Medicaid unit costs of healthcare services 2) Medicaid claims data on
ambulatory care services, dispensed pharmaceuticals, and subsequent treatment for OUD in community and
outpatient settings as part ...

## Key facts

- **NIH application ID:** 10831427
- **Project number:** 5R03DA057465-02
- **Recipient organization:** WEILL MEDICAL COLL OF CORNELL UNIV
- **Principal Investigator:** Ali Jalali
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $84,750
- **Award type:** 5
- **Project period:** 2023-05-01 → 2026-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10831427

## Citation

> US National Institutes of Health, RePORTER application 10831427, The Economic Viability and Value of Implementing an Inpatient Addiction Consult Model in Public Hospital Systems for Patients with Opioid Use Disorder (5R03DA057465-02). Retrieved via AI Analytics 2026-05-29 from https://api.ai-analytics.org/grant/nih/10831427. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*