Evidence map›Paper›PMID 40489070›Full record

ReviewPain management2025

Opioid deprescribing: rethinking policies to facilitate better patient outcomes.

Aili V Langford, Kellia Chiu

Abstract readReview
In one paragraph

Review in Pain management, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Aili V LangfordSydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.ORCID 0000-0003-0509-5136
Kellia ChiuSydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.ORCID 0000-0002-4358-6641

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deprescribing, the patient-centered process of reducing or stopping a medication when the potential harms outweigh the likely benefits, has emerged as a promising strategy to mitigate opioid-related harm. Typically, opioid deprescribing occurs at the individual level, however, adopting a policy-driven approach could expand its reach and impact. To date, prescription opioid control policies that have been implemented with the intention of reducing opioid use and harm have often resulted in unintended consequences. In this article we discuss whether and how the concept of opioid deprescribing can be operationalized at a policy level. We review the goals, challenges and consequences of opioid control policies, explore how they intersect with system-level factors, and propose pathways for developing and implementing future opioid deprescribing policies. We argue that the development and implementation of patient-centered opioid deprescribing policies are both essential and feasible, if key challenges such as structural stigma and the complex interplay between pain and opioid use disorder are recognized and addressed. Robust evaluation frameworks will also be critical for monitoring outcomes and refining interventions. By prioritizing patient and provider needs, and carefully considering pertinent system-level factors, policymakers may be able to foster more effective and compassionate opioid management and reduce opioid-related harm.

Indexed as

Analgesics, OpioidDeprescriptionsHealth PolicyOpioid-Related DisordersHumansAnalgesics, Opioidanalgesiadeprescribinghealth policyOpioidspain

Identifiers

PMID40489070
PMCPMC12218589

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.