Developing and evaluating a framework for the rational design of antibiotic prescribing policies in resource-constrained hospital settings

Lead Research Organisation: University of Oxford
Department Name: Tropical Medicine


When hospitalised patients have a serious bacterial infection, they are usually given antibiotics. In rich countries, one third of the time the antibiotics are ineffective. This is often because the bacteria have acquired a gene that makes them resistant to that antibiotic. While it is possible to test for such resistance, it takes three or four days to get a result. For patients with serious infections this delay can be the difference between life and death.

In lower income countries the same is likely to be true, but little data are available. We do, however, know that patients in hospitals in poorer countries get infections more often and when they do they are more likely to die. Infections caused by antibiotic-resistant bacteria are also a major problem. As well as delaying effective treatment, such resistance can claim lives in low-income settings because remaining effective antibiotics are not available. Even if they are, they may be too expensive for many patients. The research aims to address the question of how we can more often give patients effective antibiotics when they need them and less often when they don't in hospitals with limited resources. We also want to find out how different antibiotics affect the spread of the most dangerous antibiotic-resistant bacteria, and we want to see if by changing patterns of antibiotic prescribing we can reduce the number of infections with resistant bacteria.

One part of the proposed work will use patient data (age, time in hospital, date last hospitalised, etc) and look for patterns that help to predict how likely infections with different types of bacteria are. For example, we know that patients who have been in hospital a long time are more likely to have infections with resistant bacteria. We can use this information to help choose which antibiotic is most likely to be effective. Our hunch is that by using computer models we can make optimal use of the information and choose an effective antibiotic more often than currently happens.

The second consideration doctors have to take into account when prescribing antibiotics is how this will affect other patients. The reason is that the more an antibiotic is used the more it creates an environment favourable to antibiotic-resistant bacteria. In general, increasing antibiotic use is associated with increased resistance to that antibiotic. The specifics, however, are complicated: some antibiotics promote resistance much more than others, and sometimes use of one antibiotic can cause an increase in resistance against a completely different antibiotic. To help design good antibiotic policies we need to understand these complex mechanisms better. Another part of the work will therefore use a computer modelling approach and new statistical techniques to develop and apply better methods to understand how levels of resistance change in response to changing antibiotic use.

The next stage of the research will combine these computer models and make extensive use of expertise from infectious disease doctors to design the best antibiotic policy we can for two hospitals. We will evaluate new policies in two ways: first we will run computer simulations, using real data from the hospitals to predict how well the new policy performs. If it performs worse than current practice we will redesign the policy until it performs better. Then, in one of the hospitals, we will perform an intervention study where we introduce the new policy and evaluate whether it really does improve antibiotic prescribing and reduce resistance as predicted.

Finally, use of new rapid tests that help determine what type of bugs are causing an infection can mean a patient has more chance of getting effective antibiotic treatment when it is needed and less chance of unnecessary treatment. We will use the previously-developed computer models to estimate how much patients would benefit from such tests, and evaluate which would represent good value for money.

Technical Summary

Empirical antibiotic therapy for hospitalized patients should be chosen based on consideration of the likely pathogens, local antibiotic susceptibility patterns, patient-specific factors relating to severity of illness and risk of infection with a resistant organism, cost-effectiveness, and the impact of the antibiotic on the selection for resistant bacteria within the patient and the hospital.

Designing antibiotic polices to satisfy these complex and competing requirements is difficult. Wide variation in resistance patterns and different local incidence rates with different organisms prevent simple generalization of findings from clinical trials. Currently setting-specific choices of empirical therapy are made using clinical judgement alone, without the support of quantitative analysis or a coherent framework for balancing the competing requirements. We hypothesize that patient outcomes could be improved in a cost-effective (and potentially cost-saving) manner and antibiotic resistance reduced by implementing an evidence-based approach to the design of antibiotic policies.

This proposal aims to develop and evaluate such a framework for the rational design of antibiotic policies and to quantify the value of improving prescribing through investment in enhanced diagnostic capability. This will involve developing, extending and synthesizing a suite of phenomenological and mechanistic modelling approaches for quantifying the impact of prescribing decisions on patient and population-level outcomes. We propose to evaluate this approach using both in silico experiments using real hospital data and in a cluster-randomized trial.

While this proposal has global significance, we will focus exclusively on the choice of empirical therapy in low and middle income countries in Asia, where the potential health benefits are greatest and where the prevalence, local impact and international significance of antibiotic resistance make it a global health priority.

Planned Impact

Though the precise burden of disease is unclear, serious bacterial infections are one of the most important causes of morbidity and mortality in developing countries. Bacterial infections acquired in hospital are also a major cause of morbidity and mortality globally. While healthcare associated infections (HCAIs) affect 5-10% of acute-care patients in developed countries, infection rates are far higher in developing countries and the consequences more severe. The best estimate is that about 15 in every 100 acute care patients in developing countries acquire an infection. Serious infections are also common. At the proposed study site in Thailand, for example, at least one in every 200 in-patients staying for more than two days acquires a bacteraemia. Though reliable data are lacking and few high quality studies have been conducted, there are reasons for thinking that hospital infections could be amongst the leading causes of death in developing countries. Such infections also place a large burden on already stretched health services in resource-poor settings. Efforts to reduce neonatal mortality by referring high-risk births to healthcare settings may also be undermined if neonates have high probabilities of contracting HCAIs. For all these reasons, control of HCAIs is considered a major priority for developing countries by the World Health Organization.

Few studies from developing countries have reported data on antibiotic resistance, but it is clear that this represents a major problem, particularly in Southeast Asia. Previous research at our study sites in Thailand and Cambodia has shown a high prevalence of infection with methicillin-resistant Staphylococcus aureus. Gram-negative bacteria account for an even greater burden of disease in Southeast Asia and here resistance is an even bigger concern. At the study site in Thailand Gram-negative infections account for 78% of bacteraemias and 59% of these are multiply antibiotic resistant (resistant to three or more classes of antibiotics). The situation could get far worse. The emergence of NDM-1 plasmids conferring resistance to nearly all antibiotics and capable of transfer to most important Gram-negative bacteria is a profound global concern. The NDM-1 pandemic appears to have originated in healthcare institutions in New Delhi and spread has recently been documented to many other countries and continents. One of the best ways to slow the spread of such multiply resistant bacteria in (and between) hospitals is to reduce antibiotic selection pressure by reducing unnecessary use and changing the antibiotics used (other measures are also important, and at the site in Thailand we are evaluating a hospital-wide hand hygiene programme).

The research will address these problems in three ways. First, amongst patients with serious bacterial infections, it will aim to increase the proportion who receive adequate antibiotic therapy by developing simple algorithms to identify those at risk of harbouring resistant bacteria. Second, it will aim to develop algorithms to inform antibiotic policies that reduce unnecessary use of antibiotics and reduce resistance. Third, it will aim to identify cost-effective investments in improved diagnostic capability that developing countries can make to help target antibiotic use more effectively.

The research also has significance beyond Southeast Asia. In the short term this is because the region, which has a large population and high antibiotic use (in hospitals, the community, and in animal husbandry) is a major potential source for novel resistance determinants capable of rapid global dissemination. Ultimately, however, the aim is to have a much larger impact by taking the guesswork out of antibiotic prescribing and policy-making, and to develop tools and approaches that can be used to help design the robust, effective and evidence-based prescribing policies that are needed to mitigate the global problem of antibiotic resistance.


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Deeny SR (2016) More Research Is Needed to Quantify Risks, Benefits, and Cost-Effectiveness of Universal Mupirocin Usage. in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America

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Deeny SR (2015) Impact of mupirocin resistance on the transmission and control of healthcare-associated MRSA. in The Journal of antimicrobial chemotherapy

Guideline Title Guidelines on Core Components of Infection Prevention and Control Programmes at the National and Acute Health Care Facility Level
Description Citation in WHO guidelines
Geographic Reach Multiple continents/international 
Policy Influence Type Citation in clinical guidelines
Description Citation in policy document from National Academies of Sciences, Engineering, and Medicine
Geographic Reach Multiple continents/international 
Policy Influence Type Citation in other policy documents
Description Infectious diseases modelling workshop (given primarily for Thai Ministry of Public Health staff), Bangkok
Geographic Reach National 
Policy Influence Type Influenced training of practitioners or researchers
Description Short course: introduction to epidemiological and economic modelling of infectious diseases
Geographic Reach Asia 
Policy Influence Type Influenced training of practitioners or researchers
Impact Taught skills in modelling studies and associated economic analysis ( both in critical understanding and implementation). Mixed audience but a significant proportion were made up of representatives from national health departments from the SE Asia region and this increased training of workforce would be expected to lead to indirect health impacts
Description Systematic review and network meta-analysis of hand hygiene interventions in hospitals in BMJ (would be expected to feed into policy decisions, leading to increased take-up of intervention, but difficult to quantify effect for now and only published recently)
Geographic Reach Multiple continents/international 
Policy Influence Type Citation in systematic reviews
Description Teaching on Oxford University MSc International Health and Tropical Medicine
Geographic Reach Multiple continents/international 
Policy Influence Type Influenced training of practitioners or researchers
Description JPI-EC-AMR (Joint programming initiative on antimicrobial resistance)
Amount £299,065 (GBP)
Funding ID MR/R004536/1 
Organisation Medical Research Council (MRC) 
Sector Academic/University
Country United Kingdom
Start 05/2017 
End 04/2020
Title Model of interactions resistant and sensitive bacteria in hospital and community 
Description Theoretical model for understanding epidemiological interactions between resistant and sensitive bacteria in hospitals and the community, and how hospital interventions impact on these. Note this is also listed under software. 
Type Of Material Model of mechanisms or symptoms - human 
Year Produced 2017 
Provided To Others? Yes  
Impact Not yet....we've only just posted it, but the underlying model is discussed here 
Title QSNICH carriage data 
Description Data concerning carriage of MDR Gram-negative bacteria from a Thai neonatal ICU + associated antibiotic use data. 
Type Of Material Database/Collection of data 
Year Produced 2017 
Provided To Others? No  
Impact in progress 
Title Research database of carriage of multiply-resistant Gram negative bacteria admitted to a NICU in Cambodia 
Description Results form one year carriage study of multiply-resistant Gram negative bacteria in neonates admitted to AHC 
Type Of Material Database/Collection of data 
Provided To Others? No  
Impact None yet. 
Title WGS for Cambodian Klebsiella pneumoniae 
Description research database of whole genome sequences MDR Klebsiella pneumoniae isolates from a Cambodian NICU carriage study. Associated with detailed epidemiological data. 
Type Of Material Database/Collection of data 
Year Produced 2017 
Provided To Others? Yes  
Impact work in progress 
Description AHC 
Organisation Angkor Hospital for Children
Country Cambodia 
Sector Hospitals 
PI Contribution Angkor Hospital for Children (AHC) in Siem Reap, Cambodia
Collaborator Contribution We are working with AHC to study the carriage of multiply resistant Gram-negative bacteria in infants in a newly formed neonatal intensive care unit.
Impact The first publication describing results from this study has been accepted and is now in press at PIDJ: Turner P, Pol S, Soeng S, Sar P, Neou L, Chea P, Day N, Cooper B, Turner C (2016). Extremely high prevalence of disease-associated an- timicrobial resistant Gram negative colonisation in hospitalized Cam- bodian young infants. Paed Infect Dis Journal. In press.
Start Year 2013
Description LOMWRU 
Organisation Wellcome Trust
Department Wellcome Trust-Mahosot Hospital-Oxford University Tropical Medicine Research Collaboration
Country Lao People's Democratic Republic 
Sector Academic/University 
PI Contribution Initiated collaboration to collected and analyse historical antimicrobial resistance (AMR) data and antibiotic useage data, with a view to better understanding epidemiology of AMR in those low income setting and the drivers for recent changes. My team will contribute analytical capacity.
Collaborator Contribution Partners will contribute data and clinical expertise.
Impact No outputs yets
Start Year 2015
Description OUCRU 
Organisation University of Oxford
Department Oxford University Clinical Research Unit Vietnam (OUCRU)
Country Viet Nam 
Sector Academic/University 
PI Contribution Initiated a collaboration to pool expertise in modelling (contributed by my team) and genomics (contributed by OUCRU) to better understand epidemiology of Klebsiella pneumoniae in SE Asia.
Collaborator Contribution Genomics expertise and also data from an epidemiological study.
Impact None yet.
Start Year 2015
Description QSNICH 
Organisation Queen Sirikit National Institute of Child Health
Country Thailand 
Sector Hospitals 
PI Contribution Design of carriage study for multiply reistant organisms in neonatal intensive care unit
Collaborator Contribution Collaboration in the carriage study
Impact Data has been collected and we an initial paper describing preliminary findings is being prepared. Brief details were reported at the SMBE Satellite Meeting in Japan 2016.
Start Year 2014
Title Model of interactions resistant and sensitive bacteria in hospital and community 
Description Theoretical model for understanding epidemiological interactions between resistant and sensitive bacteria in hospitals and the community, and how hospital interventions impact on these. 
Type Of Technology Software 
Year Produced 2017 
Impact none yet 
Title Web app to explore trade-offs in empirical antibiotic prescribing decisions 
Description To use prediction scores for lack of susceptibility to the default empiric antibiotic as part of a decision support system, a threshold score is needed above which a different antibiotic is recommended. A natural approach is to choose this threshold to maximize overall utility. This web-app provides illustrative interactive calculations to show how this can be done. 
Type Of Technology Webtool/Application 
Year Produced 2018 
Impact NA 
Description Blog entry at Reflections on Infection Control website 
Form Of Engagement Activity A magazine, newsletter or online publication
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Blog entry and popular website (REFLECTIONS ON INFECTION PREVENTION AND CONTROL ) highlighting recent research by collaborator
Year(s) Of Engagement Activity 2017
Description Board Game Development 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Schools
Results and Impact Hosted Célia Souque (a DPhil student from Oxford) who worked with a research assistant in my team, Mathupanee Oonsivillai, developing and testing a board game about antimicrobial resistance in Thai schools. The game aims to raise awareness about AMR. The game is available for download here
Year(s) Of Engagement Activity 2018
Description Cafe Scientifique, Bangkok 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Public/other audiences
Results and Impact Presentation at the Bangkok Science Cafe (Cafe Scientifique).
Intended purpose - to engage with general public interested in science.
This included a 30 minute talk and discussion with the audience afterwards. Quite wide-ranging including both AMR, evaluation of Ebola drugs, and, more generally, evidence based medicine. A number of participants tweeted about this event enabling it to reach a wider audience. Lots of positive feedback online afterwards too.
Year(s) Of Engagement Activity 2015
Description Podcast about research for Oxford NDM website 
Form Of Engagement Activity Engagement focused website, blog or social media channel
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Public/other audiences
Results and Impact Recorded a "video podcast" for the oxford website, talking about research for a general audience.
This is still being edited so hasn't been released yet, but it should be online very soon.

Hence no impact yet
Year(s) Of Engagement Activity 2016