Evidence map›Paper›PMID 31478976›Full record

ReviewAnnals of surgery2020

A Pathway for Developing Postoperative Opioid Prescribing Best Practices.

Ryan Howard, Joceline Vu, Jay Lee, Chad Brummett, Michael Englesbe, Jennifer Waljee

Abstract readReview
In one paragraph

Review in Annals of surgery, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
–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

24 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Postoperative Opioid Consumption After Discharge: An Update From the Michigan Surgical Quality Collaborative Registry.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2024
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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

6 authors.

Ryan HowardDepartment of Surgery, University of Michigan, Ann Arbor, MI.
Joceline VuDepartment of Surgery, University of Michigan, Ann Arbor, MI.
Jay LeeDepartment of Surgery, University of Michigan, Ann Arbor, MI.
Chad BrummettDepartment of Anesthesiology, University of Michigan, Ann Arbor, MI.
Michael EnglesbeDepartment of Surgery, University of Michigan, Ann Arbor, MI.
Jennifer WaljeeDepartment of Surgery, University of Michigan, Ann Arbor, MI.

Funding

University of Michigan Surgical Oncology Research Training ProgramT32CA009672 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI JACQUELINE SARA JERUSS, WEIPING ZOU · 1991 to 2026
$6.0M
oPIOIDS: Prevention of Iatrogenic Opioid Dependence after SurgeryR01DA042859 · NIDA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BRUMMETT, CHAD M, WALJEE, JENNIFER FILIP · 2017 to 2021
$3.6M
Using Patient-Reported Outcomes to Assess the Quality of Hernia Care in MichiganF32DK115340 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI VU, JOCELINE VUONG-THU · 2018 to 2018
$63k
NCI NIH HHS T32 CA009672NIDA NIH HHS R01 DA042859NIDDK NIH HHS F32 DK115340
6 · The paper itself

Abstract

objectiveOpioid prescriptions after surgery are effective for pain management but have been a significant contributor to the current opioid epidemic. Our objective is to review pragmatic approaches to develop and implement evidence-based guidelines based on a learning health system model. SUMMARY BACKGROUND DATA: During the last 2 years there has been a preponderance of data demonstrating that opioids are overprescribed after surgery. This contributes to a number of adverse outcomes, including diversion of leftover pills in the community and rising rates of opioid use disorder.

methodsWe conducted a MEDLINE/PubMed review of published examples and reviewed our institutional experience in developing and implementing evidence-based postoperative prescribing recommendations.

resultsThirty studies have described collecting data regarding opioid prescribing and patient-reported use in a cohort of 13,591 patients. Three studies describe successful implementation of opioid prescribing recommendations based on patient-reported opioid use. These settings utilized learning health system principles to establish a cycle of quality improvement based on data generated from routine practice. Key components of this pathway were collecting patient-reported outcomes, identifying key stakeholders, and continual assessment. These pathways were rapidly adopted and resulted in a 37% to 63% reduction in prescribing without increasing requests for refills or patient-reported pain scores.

conclusionA pathway for creating evidence-based opioid-prescribing recommendations can be utilized in diverse practice environments and can lead to significantly decreased opioid prescribing without adversely affecting patient outcomes.

Indexed as

Practice Patterns, Physicians'Analgesics, OpioidDrug PrescriptionsHumansOpioid-Related DisordersPain ManagementPatient Reported Outcome MeasuresPostoperative PainAnalgesics, Opioid

Identifiers

PMID31478976
PMCPMC7106149

What OpenQuestion holds

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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.