Evidence map›Paper›PMID 36854603›Full record

ArticleBMJ open2023

Development and design of a mobile application for prescription opioid clinical decision-making: a feasibility study in New York City, USA.

Megan E Marziali, Mirna Giordano, Zachary Gleit, Jake Prigoff, Ruth Landau, Silvia S Martins

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 43% of its field
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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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 at 2 institutions in 1 country.

Megan E MarzialiDepartment of Epidemiology, Columbia University Mailman School of Public Health, New York, New York, USA.ORCID 0000-0002-8845-663X
Mirna GiordanoDepartment of Pediatrics, Columbia University Irving Medical Center, New York, New York, USA.
Zachary GleitDepartment of Surgery, Columbia University College of Physicians and Surgeons, New York, New York, USA.
Jake PrigoffDepartment of Surgery, Columbia University College of Physicians and Surgeons, New York, New York, USA.
Ruth LandauDepartment of Anesthesiology, Columbia University Vagelos College of Physicians and Surgeons, New York, New York, USA.
Silvia S MartinsDepartment of Epidemiology, Columbia University Mailman School of Public Health, New York, New York, USA ssm2183@cumc.columbia.edu.
Columbia University · USColumbia University Irving Medical Center · US

Funding

Clinical and Translational Science AwardUL1TR001873 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI REILLY, MUREDACH P · 2016 to 2025
$99.0M
Substance Abuse Epidemiology Training Program (SAETP) at Columbia UniversityT32DA031099 · NIDA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI DEBORAH S HASIN, Silvia Saboia Martins · 2012 to 2026
$6.1M
NCATS NIH HHS UL1 TR001873NCIPC CDC HHS R49 CE002096NIDA NIH HHS T32 DA031099
6 · The paper itself

Abstract

objectivesExcessive opioid prescribing is a contributing factor to the opioid epidemic in the USA. We aimed to develop, implement and evaluate the usability of a clinical decision-making mobile application (app) for opioid prescription after surgery.

methodsWe developed two clinical decision trees, one for opioid prescription after adult laparoscopic cholecystectomy and one for posterior spinal fusion surgery in adolescents. We developed a mobile app incorporating the two algorithms with embedded clinical decision-making, which was tested by opioid prescribers. A survey collected prescription intention prior to app use and participants' evaluation. Participants included opioid prescribers for patients undergoing (1) laparoscopic cholecystectomy in adults or (2) posterior spinal fusion in adolescents with idiopathic scoliosis.

resultsEighteen healthcare providers were included in this study (General Surgery: 8, Paediatrics: 10). Intended opioid prescription before app use varied between departments (General Surgery: 0-10 pills (mean=5.9); Paediatrics: 6-30 pills (mean=20.8)). Intention to continue using the app after using the app multiple times varied between departments (General Surgery: N=3/8; Paediatrics: N=7/10). The most reported reason for not using the app is lack of time.

conclusionsIn this project evaluating the development and implementation of an app for opioid prescription after two common surgeries with different prescription patterns, the surgical procedure with higher intended and variable opioid prescription (adolescent posterior spinal fusion surgery) was associated with participants more willing to use the app. Future iterations of this opioid prescribing intervention should target surgical procedures with high variability in both patients' opioid use and providers' prescription patterns.

Indexed as

Analgesics, OpioidMobile ApplicationsAdolescentAdultChildClinical Decision-MakingFeasibility StudiesHumansNew York CityPractice Patterns, Physicians'PrescriptionsAnalgesics, OpioidEPIDEMIOLOGYMEDICAL EDUCATION & TRAININGPUBLIC HEALTHSURGERY

Identifiers

PMID36854603
PMCPMC9980329
OpenAlexW4322626103

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.