Evidence map›Paper›PMID 38725997›Full record

ArticleGynecologic oncology reports2024

Evidence-based prescribing of opioids after laparotomy: A quality-improvement initiative in gynecologic oncology.

Allison H Kay, Rachel Levy, Nancy Hills, Allyson Jang, Alison Mcgough-Maduena, Natalia Dematteo, Melissa Mark, Stefanie Ueda, Lee-May Chen, Jocelyn S Chapman

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Gynecologic oncology reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Trial
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

10 authors.

Allison H KayDivision of Gynecologic Oncology, Department of Obstetrics, Gynecology & Reproductive Sciences, University of California San Francisco, 490 Illinois Street, 10th Floor, Box 0132, San Francisco, CA 94143, USA.
Rachel LevyDivision of Gynecologic Oncology, Department of Obstetrics, Gynecology & Reproductive Sciences, University of California San Francisco, 490 Illinois Street, 10th Floor, Box 0132, San Francisco, CA 94143, USA.
Nancy HillsDepartment of Epidemiology and Biostatistics, University of California San Francisco, 550 16 Street, 2nd Floor, San Francisco, CA 94158, USA.
Allyson JangDivision of Gynecologic Oncology, Department of Obstetrics, Gynecology & Reproductive Sciences, University of California San Francisco, 490 Illinois Street, 10th Floor, Box 0132, San Francisco, CA 94143, USA.
Alison Mcgough-MaduenaDivision of Gynecologic Oncology, Department of Obstetrics, Gynecology & Reproductive Sciences, University of California San Francisco, 490 Illinois Street, 10th Floor, Box 0132, San Francisco, CA 94143, USA.
Natalia DematteoDivision of Gynecologic Oncology, Department of Obstetrics, Gynecology & Reproductive Sciences, University of California San Francisco, 490 Illinois Street, 10th Floor, Box 0132, San Francisco, CA 94143, USA.
Melissa MarkDivision of Gynecologic Oncology, Department of Obstetrics, Gynecology & Reproductive Sciences, University of California San Francisco, 490 Illinois Street, 10th Floor, Box 0132, San Francisco, CA 94143, USA.
Stefanie UedaDivision of Gynecologic Oncology, Department of Obstetrics, Gynecology & Reproductive Sciences, University of California San Francisco, 490 Illinois Street, 10th Floor, Box 0132, San Francisco, CA 94143, USA.
Lee-May ChenDivision of Gynecologic Oncology, Department of Obstetrics, Gynecology & Reproductive Sciences, University of California San Francisco, 490 Illinois Street, 10th Floor, Box 0132, San Francisco, CA 94143, USA.
Jocelyn S ChapmanDivision of Gynecologic Oncology, Department of Obstetrics, Gynecology & Reproductive Sciences, University of California San Francisco, 490 Illinois Street, 10th Floor, Box 0132, San Francisco, CA 94143, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Across specialties, surgeons over-prescribe opioids to patients after surgery. We aimed to develop and implement an evidence-based calculator to inform post-discharge opioid prescription size for gynecologic oncology patients after laparotomy. Methods: In 2021, open surgical gynecologic oncology patients were called 2-4 weeks after surgery to ask about their home opioid use. This data was used to develop a calculator for post-discharge opioid prescription size using two factors: 1) age of the patient, 2) oral morphine equivalents (OME) used by patients the day before hospital discharge. The calculator was implemented on the inpatient service from 8/21/22 and patients were contacted 2-4 weeks after surgery to again assess their opioid use at home. Results: Data from 95 surveys were used to develop the opioid prescription size calculator and are compared to 95 post-intervention surveys. There was no difference pre- to post-intervention in demographic data, surgical procedure, or immediate postoperative recovery. The median opioid prescription size decreased from 150 to 37.5 OME (p < 0.01) and self-reported use of opioids at home decreased from 22.5 to 7.5 OME (p = 0.05). The refill rate did not differ (12.6 % pre- and 11.6 % post-intervention, p = 0.82). The surplus of opioids our patients reported having at home decreased from 1264 doses of 5 mg oxycodone tabs in the pre-intervention cohort, to 490 doses in the post-intervention cohort, a 61 % reduction. Conclusions: An evidence-based approach for prescribing opioids to patients after laparotomy decreased the surplus of opioids we introduced into our patients' communities without impacting refill rates.

Indexed as

OpioidsPerioperative carePostoperative pain

Identifiers

PMID38725997
PMCPMC11078636

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.