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Clinical Decision Support to Improve System Naloxone Co-prescribing

University of Colorado Denver (CU Denver) logo

University of Colorado Denver (CU Denver)

Status

Invitation-only

Conditions

Medication Abuse
Opioid Overdose
Opioid Prescribing
Harm Reduction

Treatments

Other: Naloxone Co-prescribing Clinical Decision Support (CDS)

Study type

Observational

Funder types

Other
NIH

Identifiers

NCT06271668
23-2356
R61DA057610 (U.S. NIH Grant/Contract)

Details and patient eligibility

About

The objective of this study is to evaluate the impact of a clinical decision support (CDS) alert to facilitate the co-prescribing of naloxone, an opioid overdose reversal agent, with high-risk opioid prescriptions. Prescribing naloxone with opioids is a best practice described in the 2022 US Center for Disease Control and Prevention (CDC) guidelines on opioid prescribing. The CDS can improve quality of care delivered by improving compliance with the guideline defined best practices. The project will compare CDS alert facilitated co-prescribing of naloxone with high-risk opioid prescriptions vs usual care to evaluate the effectiveness of the CDS alert for improving naloxone prescribing. The patients are not assigned to an intervention and will be receiving any changes in care as part of their routine medical care, rather than a specific intervention that is distinct from their usual medical care. The researchers hypothesize that the CDS alert will be acceptable to providers while increasing naloxone co-prescribing which will reduce the number of opioid overdoses in subsequent 6 months.

Full description

Clinical decision support tools help clinicians make treatment decisions based on routinely collected data and offer a promising strategy to implement evidence-based practices for safe and effective pain management. This project will use clinical decision support tools embedded into electronic health records to help healthcare providers make treatment decisions that align with opioid prescribing guidelines from the Centers for Disease Control and Prevention (CDC). The project will also use information from prescription drug monitoring programs, insurance claims, and mortality data to evaluate patient outcomes. This research will evaluate how prescribing practices that align with CDC guidelines affect patient outcomes and whether clinical decision support tools provide an advantage over standard care practices for pain management.

Enrollment

200,000 estimated patients

Sex

All

Ages

12 to 89 years old

Volunteers

Accepts Healthy Volunteers

Inclusion criteria

  • Patients receiving an opioid prescription at discharge from inpatient/ED or close visit in outpatient settings where the clinical decision support (CDS) is implemented

Exclusion criteria

  • Patients <12 and >89 year of age
  • Cancer diagnosis
  • Hospice care/palliative care
  • Sickle cell disease diagnosis
  • Patients who arrived in error
  • Patients who were triaged to obstetrics

Trial design

200,000 participants in 2 patient groups

Clinical Decision Support (CDS): Naloxone Alert
Description:
Encounters where the naloxone clinical decision support (CDS) alert fired. CDS logic is programmed to fire alert when a provider places and order for a high-risk opioid analgesic prescription to a patient without an active naloxone prescription. High-risk prescription logic to trigger the Naloxone CDS: \[(NOT 1 AND (2 AND AT LEAST 1 OF (3, 4, 5, 6))) AND 7 AND NOT 8\] 1. ACTIVE OR PENDED NALOXONE PRESCRIPTION ORDER 2. OPIOID SCRIPT BEING PLACED CRITERIA 3. DAILY Milligram Morphine Equivalent (MME) \>=90 UNSIGNED ORDER 4. DAILY MME \>=90 EXISTING 5. DIAGNOSIS OF OPIOID USE DISORDER 6. DIAGNOSIS HISTORY OF OPIOID OVERDOSE 7. PROVIDER LOGGED INTO ELLIGIBLE DEPARTMENTS 8. DISCHARGE TO HOSPICE
Treatment:
Other: Naloxone Co-prescribing Clinical Decision Support (CDS)
Usual Care
Description:
Control group of contemporary encounters where clinical decision support (CDS) is not active. Usual care.

Trial contacts and locations

1

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Central trial contact

Heather Tolle, PhD

Data sourced from clinicaltrials.gov

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