Evidence map›Paper›PMID 34460825›Full record

ArticlePLoS medicine2021

Public preferences for delayed or immediate antibiotic prescriptions in UK primary care: A choice experiment.

Liz Morrell, James Buchanan, Laurence S J Roope, Koen B Pouwels, Christopher C Butler, Benedict Hayhoe, Sarah Tonkin-Crine, Monsey McLeod, Julie V Robotham, Alison Holmes and 3 more

Open access · goldAbstract read
In one paragraph

Article in PLoS medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 29% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

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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

13 authors at 6 institutions in 1 country.

Liz MorrellHealth Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.ORCID 0000-0001-6382-1795
James BuchananHealth Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.ORCID 0000-0003-2528-0638
Laurence S J RoopeHealth Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.ORCID 0000-0001-9098-9331
Koen B PouwelsHealth Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.ORCID 0000-0001-7097-8950
Christopher C ButlerNIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, United Kingdom.ORCID 0000-0002-0102-3453
Benedict HayhoeDepartment of Primary Care and Public Health, School of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0002-2645-6191
Sarah Tonkin-CrineNIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, United Kingdom.ORCID 0000-0003-4470-1151
Monsey McLeodNIHR Health Protection Research Unit in Healthcare-Associated Infections and Antimicrobial Resistance, Imperial College London, London, United Kingdom.ORCID 0000-0001-5571-2417
Julie V RobothamModelling and Economics Unit, National Infection Service, Public Health England, London, United Kingdom.ORCID 0000-0003-2515-4084
Alison HolmesNIHR Health Protection Research Unit in Healthcare-Associated Infections and Antimicrobial Resistance, Imperial College London, London, United Kingdom.ORCID 0000-0001-5554-5743
A Sarah WalkerNIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, United Kingdom.ORCID 0000-0002-0412-8509
Sarah WordsworthHealth Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.ORCID 0000-0002-2361-3040
STEPUP team
John Radcliffe Hospital · GBUniversity of Oxford · GBImperial College Healthcare NHS Trust · GBImperial College London · GBNIHR Imperial Biomedical Research Centre · GBPublic Health England · GB

Funding

Department of Health
6 · The paper itself

Abstract

backgroundDelayed (or "backup") antibiotic prescription, where the patient is given a prescription but advised to delay initiating antibiotics, has been shown to be effective in reducing antibiotic use in primary care. However, this strategy is not widely used in the United Kingdom. This study aimed to identify factors influencing preferences among the UK public for delayed prescription, and understand their relative importance, to help increase appropriate use of this prescribing option. METHODS AND

findingsWe conducted an online choice experiment in 2 UK general population samples: adults and parents of children under 18 years. Respondents were presented with 12 scenarios in which they, or their child, might need antibiotics for a respiratory tract infection (RTI) and asked to choose either an immediate or a delayed prescription. Scenarios were described by 7 attributes. Data were collected between November 2018 and February 2019. Respondent preferences were modelled using mixed-effects logistic regression. The survey was completed by 802 adults and 801 parents (75% of those who opened the survey). The samples reflected the UK population in age, sex, ethnicity, and country of residence. The most important determinant of respondent choice was symptom severity, especially for cough-related symptoms. In the adult sample, the probability of choosing delayed prescription was 0.53 (95% confidence interval (CI) 0.50 to 0.56, p < 0.001) for a chesty cough and runny nose compared to 0.30 (0.28 to 0.33, p < 0.001) for a chesty cough with fever, 0.47 (0.44 to 0.50, p < 0.001) for sore throat with swollen glands, and 0.37 (0.34 to 0.39, p < 0.001) for sore throat, swollen glands, and fever. Respondents were less likely to choose delayed prescription with increasing duration of illness (odds ratio (OR) 0.94 (0.92 to 0.96, p < 0.001)). Probabilities of choosing delayed prescription were similar for parents considering treatment for a child (44% of choices versus 42% for adults, p = 0.04). However, parents differed from the adult sample in showing a more marked reduction in choice of the delayed prescription with increasing duration of illness (OR 0.83 (0.80 to 0.87) versus 0.94 (0.92 to 0.96) for adults, p for heterogeneity p < 0.001) and a smaller effect of disruption of usual activities (OR 0.96 (0.95 to 0.97) versus 0.93 (0.92 to 0.94) for adults, p for heterogeneity p < 0.001). Females were more likely to choose a delayed prescription than males for minor symptoms, particularly minor cough (probability 0.62 (0.58 to 0.66, p < 0.001) for females and 0.45 (0.41 to 0.48, p < 0.001) for males). Older people, those with a good understanding of antibiotics, and those who had not used antibiotics recently showed similar patterns of preferences. Study limitations include its hypothetical nature, which may not reflect real-life behaviour; the absence of a "no prescription" option; and the possibility that study respondents may not represent the views of population groups who are typically underrepresented in online surveys.

conclusionsThis study found that delayed prescription appears to be an acceptable approach to reducing antibiotic consumption. Certain groups appear to be more amenable to delayed prescription, suggesting particular opportunities for increased use of this strategy. Prescribing choices for sore throat may need additional explanation to ensure patient acceptance, and parents in particular may benefit from reassurance about the usual duration of these illnesses.

Indexed as

Primary Health CareAdultAgedAged, 80 and overAnti-Bacterial AgentsDrug PrescriptionsEnglandFemaleHumansMaleMiddle AgedPatient SatisfactionRespiratory Tract InfectionsScotlandTime FactorsYoung AdultAnti-Bacterial Agents

Identifiers

PMID34460825
PMCPMC8439451
OpenAlexW3193569321

What OpenQuestion holds

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Registered trials

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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.