Antibiotic prescribing for acute medical patients: A qualitative study in Sri Lanka, South Africa and the United Kingdom 2017-2018

This study used a qualitative interview design in Sri Lanka, South Africa and the UK. Semi-structured interviews were conducted between 2017 and 2018. The topic guide contained 17 questions about antibiotic prescribing decisions with a focus on broad spectrum antibiotics (BSA) versus narrow spectrum antibiotics (NSA) prescriptions and participants’ risk perceptions of antibiotic resistance. Antimicrobial resistance is one of the largest and most widely-acknowledged problems in 21st century medicine. Attempts to change the ways antibiotics are prescribed, in order to tackle the problem of antimicrobial resistance, have met with variable success. This is partly because the prescription of antibiotics is influenced by many social, cultural and organisational factors, and those prescribing antibiotics have to balance competing interests, values and short and long term benefits when making decisions. Healthcare providers have a responsibility both to individual patients and to 'society at large', and since there is often not a 'technical' solution to problems with prescribing, decisions are usually based on moral values and the customs of the healthcare community. Therefore attempts to change the ways antibiotics are prescribed will be more effective if they take these social factors into account. These social factors, and thus decisions made by individuals about prescribing antibiotics, are strongly influenced by the local and national context. By comparing attitudes to prescribing antibiotics in England, Sri Lanka, and South Africa this study will consider and predict the influence of different contextual factors on various attempts to change the ways antibiotics are prescribed. This will make it easier to assess which attempts will be successful and could be repeated in different international contexts. Models, which take these factors into account, can be used to predict how changes in individual behaviour, social, cultural, or economic factors will impact on decisions about prescribing antibiotics, and the broader problem of antimicrobial resistance. The project has three main aims: 1) To develop an international group of academics and clinicians who will work together to use social science theory and methods to look at the use of antibiotics in treating seriously ill patients. Close collaboration will make sure that the work of the project will be relevant to many contexts in which people are trying to improve antimicrobial resistance, particularly in non-high income countries. 2) To use theory to build a model that describes the use of broad spectrum antibiotics in treating seriously ill patients. The model will identify the risks, tensions, and elements of social and cultural context that effect the way antibiotics are prescribed. To find ways to improve antibiotic prescribing, and to consider the potential of various actions to address problems with the use of antibiotics in treating seriously ill patients in different parts of the world. 3) To begin work on a future proposal which would use two types of mathematical models to predict the effect of various attempts to try and improve the use of antibiotics in different contexts. The model or models developed within the grant could be used to improve the success of attempts to influence antibiotic prescription, by making it clearer which actions have the best chance of success in different contexts, particularly in non-high income countries. This would reduce the risk of investing finances, time, and energy in unsuccessful projects. The work will lay the ground work for future international collaborations, and for the development of larger projects to research and test attempts to improve the way antibiotics are prescribed. This might involve a study which interviews patients to explore their role in the prescription of antibiotics. The study will also involve training local researchers in Sri Lanka and South Africa in interviewing skills

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Geographic Coverage:

GB, LK, ZA

Temporal Coverage:

2017-01-01/2018-12-31

Resource Type:

dataset

Available in Data Catalogs:

UK Data Service

Topics: