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Optimising Prescribing for Drug Resistant Bacteraemia in the COVID-19 Context
Safe People
Organisation name
Imperial College London
Organisation sector
Academic Institute
Applicant name(s)
Timothy Miles Rawson
Funders/ Sponsors
James Price
DEA accredited researcher?
Unknown
Sub-licence arrangements (if any)?
No
Safe Projects
Project ID
NIBDAPC_2022_0012
Lay summary
Antibiotics are medications used to treat bacterial infections. If antibiotics were not provided when needed, infection might get worse or even kill the patients. However, antibiotics can also cause the germs to become resistant to the medication and make treating future infections impossible. For drug resistant germs, the treatment options are even more limited. COVID-19 has made the problems more challenging because of the different burdens on health care system. Therefore, we must choose carefully how and when antibiotics are used for these germs. In this project, we have been supported by the individual level de-identified patient data collected from three hospitals from ICHT to explore the effects of different treatment options for these infections and try to find the best suitable options in the future.
Public benefit statement
Tackling AMRis one of the nation’s highest public health priorities. Our work is in line with UK’s 20 year vision of AMR, and England’s national strategy for infectious diseases. Benefited from the unique setting of our research group (NIHR HPRU in HCAI and AMR), which is a close collaboration between Imperial College, UKHSA, and local NHS trusts, research outputs can be disseminated and translated to policy and patient management guidelines rapidly to enhance the quality of care. This work will help improve the precision in antibiotic prescribing for drug resistant pathogens to increase the chance of better clinical outcomes and reduce overall drug exposure during therapy.
Request category type
Public Health Research
Other approval committees
Project start date
03/05/2022
Latest approval date
14/04/2022
Safe Data
Dataset(s) name
ICHT COVID-19 Research Dataset
Data sensitivity level
De-Personalised
Common Law Duty of Confidentiality
Not applicable
National data opt-out applied?
Not applicable
Request frequency
One-off
Release/Access date
03/05/2022
Safe Setting
Access type
TRE
Safe Outputs
Link to research outputs