# Improving pain management and opioid safety through a systemwide, data driven evaluation of the CDC opioid prescribing guideline best practices and the use of Clinical Decision Support

> **NIH NIH R61** · UNIVERSITY OF COLORADO DENVER · 2022 · $1,072,844

## Abstract

Project Summary
 Effectively treating pain while safely prescribing opioid pain medicines is a public health priority.
The CDC opioid prescribing guidelines are an evidence-based approach to decreasing unnecessary opioid
exposures, high-risk opioid use and abuse. The 2016 version produced modest improvements, but were
sometimes misapplied for unsafe opioid tapering; highlighting the challenges of implementation and
changing provider behavior. With guideline updates expected soon, there is a need for prospective trials
to identify strategies to efficiently and effectively deliver CDC guideline recommended practices while
documenting their impact on patient centered outcomes (e.g., pain control, morbidity and mortality).
 Clinical decision support (CDS) is a promising implementation strategy to both operationalize
evidence-based practices and maximize the value of routinely collected data. We will use electronic
health record (EHR) embedded CDS to modify clinical behavior toward CDC guideline-concordant
recommendations. We propose a hybrid effectiveness-implementation trial using accepted
implementation science frameworks PRISM (Practical, Robust Implementation and Sustainability Model)
and RE-AIM (Reach, Effectiveness, Adoption, Implementation and Maintenance) to consider the
multilevel contextual factors that influence implementation success. By developing a data-driven
learning health system with the ability to evaluate patient outcomes through linkages to Prescription
Drug Monitoring Program, insurance claims and death data, this project will evaluate:
(1) The effectiveness of CDC guideline-concordant prescribing by describing the association between
guideline concordant actions and patient outcomes.
(2) The user-centered design of EHR based CDS to facilitate CDC guideline concordant actions and
promote non-opioid approaches to pain management.
(3) The evaluation of the implementation and effectiveness of CDS strategies to deliver guideline-
concordant care in a pragmatic cluster randomized trial in a large, integrated health system. We will
systematically assess key implementation outcomes and then evaluate the effectiveness of CDS on
patient outcomes (vs usual care).
 This pragmatic research will address the need to link provider prescribing actions to individual
patient outcomes. Using established implementation science approaches to evaluate CDS as an
implementation strategy is innovative and important. Our results will provide robust data to document
the effectiveness of CDC guideline concordant prescribing and evaluate an emerging, scalable
implementation strategy using existing data to decrease morbidity and mortality from the opioid crisis.

## Key facts

- **NIH application ID:** 10588405
- **Project number:** 1R61DA057610-01
- **Recipient organization:** UNIVERSITY OF COLORADO DENVER
- **Principal Investigator:** Jason Hoppe
- **Activity code:** R61 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $1,072,844
- **Award type:** 1
- **Project period:** 2022-09-30 → 2024-09-29

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10588405

## Citation

> US National Institutes of Health, RePORTER application 10588405, Improving pain management and opioid safety through a systemwide, data driven evaluation of the CDC opioid prescribing guideline best practices and the use of Clinical Decision Support (1R61DA057610-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10588405. Licensed CC0.

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