# Chicago Data-driven OUD Screening, Engagement, Treatment and Planning (C-DOSETaP) System

> **NIH NIH R61** · UNIVERSITY OF ILLINOIS AT CHICAGO · 2023 · $1,093,394

## Abstract

Project Summary/Abstract
In alignment with the HHS Overdose Prevention Strategy, this HEAL Data2Action Innovation Project
proposal addresses primary prevention, harm reduction, treatment of OUD, and recovery support using a
state-of-the-art data driven approach that will bring together elements of the University of Illinois
Hospital and Clinics (UI Health) and University of Illinois Chicago into a single, unified approach that is
capable of reducing mortality and morbidity from OUD on the westside of Chicago. We will deploy a
combination of machine learning (natural language processing of electronic health records data), state
reported prescription monitoring data, and patient reported measures to determine individual and group-
level OUD risk across the various UI Health care sites (Priority 2, Innovation Project). We will then use
this data at both the individual level (to facilitate clinical care) and at the community/system level (to
support resource allocation and planning).

## Key facts

- **NIH application ID:** 10745471
- **Project number:** 1R61DA057629-01A1
- **Recipient organization:** UNIVERSITY OF ILLINOIS AT CHICAGO
- **Principal Investigator:** Niranjan Subhash Karnik
- **Activity code:** R61 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $1,093,394
- **Award type:** 1
- **Project period:** 2023-09-01 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10745471

## Citation

> US National Institutes of Health, RePORTER application 10745471, Chicago Data-driven OUD Screening, Engagement, Treatment and Planning (C-DOSETaP) System (1R61DA057629-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10745471. Licensed CC0.

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