Evidence map›Paper›PMID 37857521›Full record

Trial reportBMJ open quality2023

Randomised trial of general practitioner online education for prescribing and test ordering.

Andrew Bonney, Conrad Kobel, Judy Mullan, Christine Metusela, Joel J Rhee, Stephen Barnett, Marijka Batterham

Open access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in BMJ open quality, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.9field-weighted citation impact, top 22% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. 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

7 authors at 2 institutions in 1 country.

Andrew BonneyGraduate School of Medicine, University of Wollongong, Wollongong, New South Wales, Australia abonney@uow.edu.au.ORCID 0000-0003-2477-1646
Conrad KobelFaculty of Science, Medicine and Health, University of Wollongong, Wollongong, New South Wales, Australia.
Judy MullanGraduate School of Medicine, University of Wollongong, Wollongong, New South Wales, Australia.
Christine MetuselaGraduate School of Medicine, University of Wollongong, Wollongong, New South Wales, Australia.
Joel J RheeSchool of Population Health, University of New South Wales, Sydney, New South Wales, Australia.
Stephen BarnettGraduate School of Medicine, University of Wollongong, Wollongong, New South Wales, Australia.
Marijka BatterhamSchool of Mathematics and Applied Statistics, University of Wollongong, Wollongong, New South Wales, Australia.
University of Wollongong · AUUNSW Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionPotentially inappropriate medicine prescriptions and low-value diagnostic testing pose risks to patient safety and increases in health system costs. The aim of the Clinical and Healthcare Improvement through My Health Record usage and Education in General Practice study was to evaluate a scalable online quality improvement intervention, integrating online education regarding a national shared electronic health record and rational prescribing, pathology and imaging ordering by Australian general practitioners (GPs).

methodsThe study was a parallel three-arm randomised trial comprising a prescribing education arm, a pathology education arm and an imaging education arm. Currently practising GPs in Australia were eligible to participate and randomised on a 1:1:1 basis to the study arms after consenting. The response to the intervention in reducing potentially unnecessary medicine prescriptions and tests in each arm was assessed using the other two arms as controls. The primary outcome was the cost per 100 consultations of predefined medication prescriptions, pathology and radiology test ordering 6 months following the intervention, compared with 6 months prior. Outcomes were assessed on intention-to-treat and post hoc per-protocol bases using multilevel regression models, with the analysts blinded to allocation.

resultsIn total, 106 GPs were enrolled and randomised (prescribing n=35, pathology n=36, imaging n=35). Data were available for 97 GPs at the end of trial (prescribing n=33, pathology n=32, imaging n=32) with 44 fully completing the intervention. In intention-to-treat analysis, there were no significant differences in the rates of change in costs across the three arms. Per protocol, there was a statistically significant difference in the rate of change in pathology costs (p=0.03). In the pathology arm, the rate of increase in pathology costs was significantly lower by $A187 (95% CI -$A340, -$A33) than the prescribing arm, and non-significantly $A9 (95% CI -$A128, $A110) lower than the imaging arm. DISCUSSION: This study provides some evidence for reductions in costs for low-value pathology test ordering in those that completed the relevant online education. The study experienced slow uptake and low completion of the education intervention during the COVID-19 pandemic. Changes were not significant for the primary endpoint, which included all participants. Improving completion rates and combining real-time feedback on prescribing or test ordering may increase the overall effectiveness of the intervention. Given the purely online delivery of the education, there is scope for upscaling the intervention, which may provide cost-effectiveness benefits. TRIAL REGISTRATION NUMBER: ACTRN12620000010998.

Indexed as

COVID-19Education, DistanceGeneral PractitionersAustraliaHumansPandemicsContinuing education, continuing professional developmentGeneral practiceHealthcare quality improvementPrimary care

Identifiers

PMID37857521
PMCPMC10603404
OpenAlexW4387769016

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.