JRO protocol
As per the UCLH JRO template headings
See UCL/UCLH Interventional studies protocol template (section number matches the template)
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1. Introduction
Leave for now: will be written after Background and Rationale complete
2. Background and Rationale
Antimicrobial Resistance
Antimicrobial resistance (AMR) is a global problem, with an estimated 1.9 million deaths annually attributable to AMR forecast by 2050 (GBD 2021 Antimicrobial Resistance Collaborators, 2024, 10.1016/S0140-6736(24)01867-1). In 2019, it was estimated to cause more deaths than HIV/AIDS or Malaria. Within England, the burden of AMR is increasing with London comprising the highest rates of resistant bacteraemia. AMR rates are highest in deprived areas and certain ethnic groups, with particular impact on the elderly (ESPAUR 23-24 report). Human antibiotic consumption is a major driver in resistance at a population level and at an indicidual level(Thom KA, et al. Clin Infect Dis 2019; 68: 1581–84.)
Disease Specific Background
Urinary Tract Infections (UTIs) contribute to approximately 190,000 hospital admissions in England, resulting in 1.2 million bed days in 2023/4. They are the most frequently occurring healthcare associated infection and account for approximately 23% of all antibiotic prescriptions in primary care, second only to respiratory tract infections in the UK (Dolk et al. 2018, 10.1093/jac/dkx504).
Most UTI prescriptions are given empirically before culture results are available. An estimated 40% of bacteria that cause UTIs can be resistant to the antimicrobials used, with 18-21% of patients experiencing treatment failure. (McCowan et al 2022, https://doi.org/10.1186/s12879-022-07768-7, Moon et al 2022, https://doi.org/10.1371/journal.pone.0277713). UTI recurrence is common, with repeated infections, further compounding antimicrobial use and resistance.
Inadequately treated UTIs can lead to bacteraemia, with approximately 50% of E Coli bacteraemia originating from a urinary tract source (ESPAUR 2025). In 2024, Enterobacterales comprised 80.6% of urinary isolates, Escherichia coli (E. coli) accounting for around 70% of all episodes (ESPAUR 2025). These enterobacterales (E. coli, K. pneumoniae, and K. oxytoca) which commonly cause both UTIs and bacteraemia, accounted for 85% of resistant bacteraemia in 2024 (ESPAUR 2025).
Dilemma of empirical prescribing
Given this risk of resistance, prescribing the correct antibiotic for the correct pathogen is crucial to reduce immediate harm to the patient. However, a dilemma exists in prescribing broader-spectrum or unnecessary antibiotics will drive resistance, causing future harm to both the patient and society.Therefore, optimal antibiotic prescribing should be guided by confirmation of infection, and microbiology susceptibility testing of isolates, whilst taking into account the future harm of resistance. Several challenged hinder optimal prescribing in practice.
Microbiology results take days, meaning initial treatment decisions are made empiricially before susceptibility data is available. Prior antibiotic usage and resistance history is therefore crucial to guide therapy, yet this is often fragmented and not readily accessible due to patients accessing multiple providers across different non-interoperable systems. Even when information is available, the volume and complexity of clinical and microbiological data can make accurate, timely decision-making difficult, particularly in emergency settings where clinicians are under pressure. This challenge is further amplified by the fact that most prescribing decisions are not made by infection specialists, meaning that the nuanced judgement required to balance immediate patient need against the future risk of driving resistance is not always available at the bedside.
As a result, prescribers often rely on heuristics and local guidelines, rather than patient specific data. Whilst an infection specialist input can be sought, the volume of cases would make individual review impractical. Consequently, empirical therapies are frequently initiated without full consideration of patient-specific risk factors (9).
Antimicrobial Stewardship
Antimicrobial stewardship seeks to preserve antibiotic effectiveness by limiting resistance. This involves ensuring antibiotics are initiated only when indicated and that the most narrow spectrum agent is used to target the causative organism. Within the hospital setting, stewardship programmes that have focussed on enabling better prescribing rather than restricting prescribing have demonstrated reductions in antibiotic overuse and length of stay, without adversely affecting patient mortality outcomes.
The EHRS opportunity for antibiotic stewardship
The NHS 10 year plan calls for all NHS trusts to adopt an Electronic Health Record Systems (EHRS),presenting a significant opportunity to address the challenges of antimicrobial prescribing. Increasing adoption of comprehensive EHRS, encompassing prescribing, patient records and laboratory results including microbiology data creates an opportunity to creates the foundation of learning health system that can improve antibiotic use.
This may be achieved through modification of EPR architecture to embed better prescribing practices. This can be through real-time intervention via clinical decision support systems (CDSS) at the point of prescribing. Although conceptually straightforward, successful CDS alerts must deliver accurate information, in clinical context and at the point of care, and must be well-integrated into the clinical workflow. Otherwise they suffer from poor usability, alert fatigue which can itself be a patient safety risk.
The potential of this approach is supported by studies such as the INSPIRE trial which demonstrated that prompts at the time of prescribing significantly reduced the use of extended spectrum antibiotics.
The Local Context
University College London Hospitals NHS Foundation Trust (UCLH) provides acute and specialist services across six hospitals in North Central London, which share a single Electronic Health Record System (EHRS). In addition to serving the local population in the borough of Camden, UCLH receives referrals from across London and the wider country for specialist services including Neurology, Oncology, and Infectious Diseases. This includes sharing patients with neighbouring hospital trusts such as the Royal Free Hospital, Whittington Health, and North Middlesex Hospital amongst a multitude of others.
This geographic clustering of hospitals means that patients frequently move between institutions, receiving care across multiple sites and specialties. As these hospitals do not share the same EHRS, a patient's antibiotic history and microbiology results may be distributed across multiple non-interoperable systems, as well as between primary and secondary care, making prior resistance history difficult to access in a timely manner.
Ingles 2
The Ingles-2 study hypothesises that surfacing a patient's antibiotic history at the point of prescribing will enable more targeted and judicious antibiotic selection in patients who are thought to have a urinary source of infection.
Urinary Tract Infections have been selected as the indication as they frequently have prior microbiology and resistance history available, are prone to recurrence, and if inadequately treated can progress to pyelonephritis, bacteraemia and mortality.
Research Question Ingles 2
In patients attending secondary care with a presumed urinary tract infection or pyelonephritis, can an electronic alert that surfaces prior microbiological resistance data at the point of prescribing improve prescribing?
We would investigate this through the following design.
Where prior microbiological resistance data +/- antibiotic prescribing (depending on availability) history exists within the preceding 30 days, an alert will surface this information at the point of prescribing.
Where no prior microbiology is available, a nudge will fire if the prescribed antibiotic is not guideline-concordant, steering the prescriber toward recommended therapy.
These alerts would be randomised at the patient level, and if a patient was assigned to one group and repeated encounters would mean they remain with the pop up being triggered.
The alert is purely informational, it does not mandate a specific antibiotic choice or prevent the prescriber from proceeding with their intended prescription.
3. Objectives and outcome measures
Primary objective
Evaluate the effectiveness of a clinically-integrated digital prescribing nudge surfacing antimicrobial resistance information at the point of prescribing.
Secondary objectives
Evaluate the safety of the digital prescribing prompt
Evaluate the stewardship outcomes of a prescribing prompt
Outcome measures/endpoints
Effectiveness:
Primary outcome
Proportion of patients prescribed an antibiotic to which their most recent culture isolate (from the defined types) within the preceding 30 days demonstrated resistance in the two different groups.
Secondary outcomes
Proportion of patients whose urinary or blood culture isolate of a gram-negative organism likely to cause UTI (e.g Enterobacterales), obtained between 24 hours before and 48 hours after the index antibiotic prescription, demonstrated resistance to the antibiotic prescribed between the two groups.
Proportion of antibiotic prescription changes at the point of prescribing, in response to a fired nudge?
Proportion of empiric escalation of antibiotic therapy (broadening of antimicrobial spectrum in the absence of new microbiological evidence) within 72 hours of initial prescription.
Among prescribing episodes where the nudge fired and no resistance to the prescribed antibiotic was documented within the preceding 30 days, the proportion in which the antibiotic prescription was changed to adhere to guidance?
Among patients with documented resistance to the initially prescribed antibiotic within the preceding 30 days, the proportion whose current admission cultures grew an organism sensitive to the initially prescribed antibiotic.
Safety:
All cause in-hospital and 90-day mortality.
Length of hospital stay (days).
Escalation to level 2 or 3 care (ECU or ICU).
Readmission to hospital within 30 days of discharge.
Time to intravenous to oral antibiotic switch (hours).
Presence of infection or colonisation by antimicrobial resistant pathogens
Stewardship:
Antibiotic consumption measured as Defined Daily Doses per admission overall and in AWaRE categories split by indication
Days of Antibiotic Spectrum consumption per admission and indication
Days of therapy of antibiotics
Proportion of patients who receive IV or Oral antibiotic courses
Rates of Clostridoides Difficile in both groups, ESBL, CRO and Ciprofloxacin Resistance isolates, and Vancomycin resistant enterococci rates
PICOT
4. Trial design
This is a single centre prospective individually randomised control trial evaluating the effectiveness of a clinically integrated digital prescribing aide that surfaces relevant antimicrobial resistance and antimicrobial usage at the point of prescribing for a range of infections that affect the urinary tract.
Eligible patients would be randomised 1:1 to the intervention (digital nudge) or control (standard workflow) using an automated system within the EHRS. Once a patient is allocated, their assignment will be fixed for all subsequent prescribing episodes during the study period. This ensures consistency of the intervention within individual patients across multiple encounters.
Due to the nature of the intervention, prescribers cannot be blinded to treatment allocation, they will either see the digital nudge or they will not. Patients are not actively involved in the intervention and will not be aware of their allocation. Outcome assessment will be conducted using routinely collected electronic data and can be performed by analysts blinded to group allocation.
The patients randomised into three arms:
An interruptive Our Practice Advisory (OPA) card showcases prior antibiotic resistance history and antimicrobial prescription data for the last 30 days. The AMR data will be drawn from Helix, and the prescribing data from EPIC and... ? GP?
An interruptive Our Practice Advisory card showcases current guidance for each indication if a prescriber has prescribed against guidance if no prior microbiology history/ antimicrobial usage history is present in the last 30 days.
Usual workflow with no antimicrobial history surfaced.
Patient level randomisation introduces a risk of contamination as prescribers exposed to these alerts may modify their subsequent prescribing behaviour. However, the alternative method of randomising by prescriber does not eliminate this risk, as colleagues may discuss the alert with each other meaning that contamination may persist. Other trial designs such as a step wedged cluster randomised trial could be considered, where different wards had the alert or were sequentially included to the intervention arm as demonstrated in the SCREEN trial. However, very few prescribers are ward based and often rotate between clinical areas therefore would have similar contamination.
Therefore, patient level randomisation offers a pragmatic design. Furthermore, the nature of the intervention itself mitigates the impact of contamination: the interruptive alert in arm 1 surfaces individualised prior antimicrobial resistance and usage history specific to each patient. Unlike a generic prescribing prompt, each alert presents different information, limiting the extent to which exposure to one patient's alert can meaningfully influence prescribing decisions for another.
5. Sampling methods
Inclusion criteria
Patients admitted or prescribed antibiotics at UCLH
Age over 18
Patients prescribed of Antibiotics with Indication of:
LOWER urinary tract infection (Cystitis)
UPPER urinary tract infection (Pyelonephritis)
RECURRENT urinary tract infection
Catheter-associated UTI (incl Stent, Nephrostomy, Other)
Prostatitis
Exclusion criteria
Age under 18
Pregnancy
Recruitment
All wards or new admissions?
Consent
As this is only showing the data, we are testing whether showing the data is helpful therefore no patient level consent
6. Intervention
The patients randomised into three arms:
An interruptive Our Practice Advisory (OPA) card showcases prior antibiotic resistance history and antimicrobial prescription data for the last 30 days. The AMR data will be drawn from Helix, and the prescribing data from EPIC and... ? GP?
An interruptive Our Practice Advisory card showcases current guidance for each indication if a prescriber has prescribed against guidance if no prior microbiology history/ antimicrobial usage history is present in the last 30 days.
Usual workflow with no antimicrobial history surfaced.
7. Trial procedures
8. Finance and supply of equipment
9. Data management
10. Statistical considerations
Will need percentages of risks
11. Assessment and management of risk
12. Recording and reporting adverse events
13. Oversight committees
14. Regulatory review and patient and public involvement
Regulatory review
Peer review
Patient and public involvement
15. Monitoring and auditing
16. Training
17. Insurance and indemnity
18. Record keeping and archiving
19. Intellectual property
20. Publication and dissemination
21. References
22. Appendices
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