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Applied health economics and health policy
Mar, 2025;23 (2): 311-317.

Contextual Factors that Influence Antibiotic Prescribing: A Discrete Choice Experiment of GP Registrars.

Gregory Merlo, Lisa Hall, Parker Magin, Amanda Tapley, Katie J Mulquiney, Alison Fielding, Andrew Davey, Joshua Davies, Mieke van Driel
Author Information
  1. Gregory Merlo: School of Public Health, The University of Queensland, Brisbane, QLD, Australia. gregory.merlo@health.qld.gov.au. ORCID
  2. Lisa Hall: School of Public Health, The University of Queensland, Brisbane, QLD, Australia. ORCID
  3. Parker Magin: GP Synergy, Newcastle, NSW, Australia. ORCID
  4. Amanda Tapley: GP Synergy, Newcastle, NSW, Australia. ORCID
  5. Katie J Mulquiney: GP Synergy, Newcastle, NSW, Australia. ORCID
  6. Alison Fielding: GP Synergy, Newcastle, NSW, Australia. ORCID
  7. Andrew Davey: GP Synergy, Newcastle, NSW, Australia. ORCID
  8. Joshua Davies: School of Medicine and Public Health, The University of Newcastle, Newcastle, NSW, Australia.
  9. Mieke van Driel: General Practice Clinical Unit, Faculty of Clinical Medicine, The University of Queensland, Brisbane, QLD, Australia. ORCID
PMID: 39853598 DOI: 10.1007/s40258-025-00944-1

Abstract

INTRODUCTION: Antimicrobial resistance is a global emergency related to overprescribing of antibiotics. Few studies have explored how prescribing behaviours may change as the consequence of changing resistance. Understanding how contextual factors influence antibiotic prescribing will facilitate improved communication strategies to promote appropriate antibiotic prescribing. We aimed to develop and conduct a discrete choice experiment (DCE) to measure how contextual factors influence intended antibiotic prescribing of general practitioner (GP) registrars.
METHODS: Factors included as attributes in the DCE were level of antibiotic resistance, requirement for an authority to prescribe, existence of a Practice Incentives Program (PIP) for low prescribing and supervisor support for low prescribing. The survey was administered in an online format for GP registrars undergoing training between 2020 and 2021. Regression analysis using a conditional logit model with interaction effects was used on the basis of the assumptions of independence of irrelevant alternatives, independence of error terms and no preference heterogeneity.
RESULTS: In total, 617 unique respondents answered at least one choice set question. Respondents showed significant preference for avoiding prescribing antibiotics when antibiotic resistance was 25-35% or 40-60% compared with 5-8%. There was also a significant preference for avoiding prescribing when an authority to prescribe was required, or when there was supervisory support of low antibiotic prescribing. In the main effects analysis, respondents were significantly less likely to choose a prescribing option if there was a PIP; however, when interaction effects were included in the regression analysis there was a significant interaction between PIP and resistance rates, but the preference weights for PIP was no longer significant.
CONCLUSIONS: Knowledge about community resistance impacts the stated intention of GP registrars to prescribe antibiotics. The use of the DCE may have made it possible to determine factors influencing prescribing that would not be detected using other survey methods. These findings provide guidance for producing, explaining and communicating issues regarding antibiotic prescribing to GP registrars.

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MeSH Term

Humans
Anti-Bacterial Agents
Practice Patterns, Physicians'
Male
Female
Surveys and Questionnaires
Adult
Middle Aged
General Practitioners
Choice Behavior

Chemicals

Anti-Bacterial Agents
Journal Article

Word Cloud

Created with Highcharts 10.0.0prescribingantibioticresistanceGPregistrarsPIPpreferencesignificantantibioticsfactorsDCEprescribelowanalysisinteractioneffectsmaycontextualinfluencechoiceFactorsincludedauthoritysupportsurveyusingindependencerespondentsavoidingINTRODUCTION:AntimicrobialglobalemergencyrelatedoverprescribingstudiesexploredbehaviourschangeconsequencechangingUnderstandingwillfacilitateimprovedcommunicationstrategiespromoteappropriateaimeddevelopconductdiscreteexperimentmeasureintendedgeneralpractitionerMETHODS:attributeslevelrequirementexistencePracticeIncentivesProgramsupervisoradministeredonlineformatundergoingtraining20202021RegressionconditionallogitmodelusedbasisassumptionsirrelevantalternativeserrortermsheterogeneityRESULTS:total617uniqueansweredleastonesetquestionRespondentsshowed25-35%40-60%compared5-8%alsorequiredsupervisorymainsignificantlylesslikelychooseoptionhoweverregressionratesweightslongerCONCLUSIONS:KnowledgecommunityimpactsstatedintentionusemadepossibledetermineinfluencingdetectedmethodsfindingsprovideguidanceproducingexplainingcommunicatingissuesregardingContextualInfluenceAntibioticPrescribing:DiscreteChoiceExperimentRegistrars

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