Evidence map›Paper›PMID 36765414›Full record

Trial reportImplementation science : IS2023

De-Implementing Opioids for Dental Extractions (DIODE): a multi-clinic, cluster-randomized trial of clinical decision support strategies in dentistry.

Jan Gryczynski, Shannon Gwin Mitchell, Stephen E Asche, Anjali R Truitt, Donald C Worley, D Brad Rindal

Registry-linked trialOpen access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Implementation science : IS, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03584789 (De-Implementing Opioid Use and Implementing Optimal Pain Management Following Dental Extractions), which is not on this map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 11% 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.

NCT03584789 nacompletednot on this map

De-Implementing Opioid Use and Implementing Optimal Pain Management Following Dental Extractions

TypeinterventionalSponsorHealthPartners InstituteRan2020 to 2021Enrolled5,722ConditionsTooth ExtractionArmsClinical Decision Support, Patient education
3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
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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 at 2 institutions in 1 country.

Jan GryczynskiFriends Research Institute, Baltimore, MD, USA. jgryczynski@friendsresearch.org.
Shannon Gwin MitchellFriends Research Institute, Baltimore, MD, USA.
Stephen E AscheHealthPartners, Minneapolis, MN, USA.
Anjali R TruittHealthPartners, Minneapolis, MN, USA.
Donald C WorleyHealthPartners, Minneapolis, MN, USA.
D Brad RindalHealthPartners, Minneapolis, MN, USA.
HealthPartners · USFriends Research Institute · US

Funding

De-Implementing Opioid Use and Implementing Optimal Pain Management Following Dental ExtractionsU01DE027441 · NIDCR · HEALTHPARTNERS INSTITUTE · PI RINDAL, D. BRAD · 2017 to 2020
$3.3M
NIDCR NIH HHS U01 DE027441
6 · The paper itself

Abstract

backgroundOpioid pain relievers are commonly prescribed following dental extractions, but evidence shows that non-opioid analgesics often provide adequate pain relief with fewer risks. The current study examined clinical decision support (CDS) as a tool for de-implementing opioid prescribing in dentistry.

methodsThis prospective, cluster-randomized trial examined CDS for dental pain management at 22 HealthPartners Dental Group clinics in Minnesota. Dental providers (n = 49) were randomized to deliver care using CDS, CDS with patient education materials (CDS-E), or standard practice (SP). Randomization was stratified by provider type (dentist vs. oral surgeon) and baseline opioid prescribing volume. Patient records of dental extractions were examined for January 2019 through May 2021, representing a 12-month baseline and 15-month intervention period (N = 12,924). Opioid prescription at the visit (no vs. yes) was the primary outcome. Data were analyzed using generalized linear mixed models, adjusting for patient sex and age, extraction complexity, and baseline prescribing strata (volume and provider type).

resultsPatients were 56.2% female, with a mean age of 46.7 (SD = 20.0) years. Providers were 8% oral surgeons, 57% female, and with a mean age of 43.7 (SD = 11.2) years. There were significant decreases in opioid prescribing during the study (P < 0.001), representing a continuation of pre-existing trends to reduce opioid prescribing in these dental practices. There were no significant differences in opioid prescribing between CDS and SP (OR = 1.29; 97.5% CI = 0.93, 1.79; P = 0.08), or CDS-E and SP arms (OR = 1.27; 97.5% CI = 0.86, 1.79; P = 0.18). The direction of the association favored greater reductions in opioid prescribing in the SP arm. Despite training and implementation support, utilization of the CDS was low, particularly among oral surgeons, who were significantly more likely than other dentists to prescribe opioids. Among non-oral surgeon providers with the opportunity to access it, CDS utilization was not significantly associated with opioid prescribing.

conclusionsEquipping dentists with CDS resources, whether alone or accompanied by patient education materials, did not accelerate reductions in opioid prescribing beyond those observed in standard practice. Strategies are needed to enhance CDS utilization for patient care and safety surrounding analgesia following dental extractions.

trial registrationClinicaltrials.gov, NCT03584789.

Indexed as

Analgesics, OpioidDecision Support Systems, ClinicalAdultDentistryFemaleHumansMaleMiddle AgedPainPractice Patterns, Physicians'Prospective StudiesTooth ExtractionAnalgesics, OpioidClinical decision supportDe-implementationDentistryOpioids

Identifiers

PMID36765414
PMCPMC9913004
OpenAlexW4319959438

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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.