Knowledge support for optimising antibiotic prescribing for common infections in general practices: evaluation of the effectiveness of periodic feedback, decision support during consultations and peer comparisons in a cluster randomised trial (BRIT2) – study protocol

Abstract

IntroductionThis project applies a Learning Healthcare System (LHS) approach to antibiotic prescribing for common infections in primary care. The approach involves iterations of data analysis, feedback to clinicians and implementation of quality improvement activities by the clinicians. The main research question is, can a knowledge support system (KSS) intervention within an LHS implementation improve antibiotic prescribing without increasing the risk of complications?Methods and analysisA pragmatic cluster randomised controlled trial will be conducted, with randomisation of at least 112 general practices in North-West England. General practices participating in the trial will be randomised to the following interventions: periodic practice-level and individual prescriber feedback using dashboards; or the same dashboards plus a KSS. Data from large databases of healthcare records are used to characterise heterogeneity in antibiotic uses, and to calculate risk scores for clinical outcomes and for the effectiveness of different treatment strategies. The results provide the baseline content for the dashboards and KSS. The KSS comprises a display within the electronic health record used during the consultation; the prescriber (general practitioner or allied health professional) will answer standard questions about the patient’s presentation and will then be presented with information (eg, patient’s risk of complications from the infection) to guide decision making. The KSS can generate information sheets for patients, conveyed by the clinicians during consultations. The primary outcome is the practice-level rate of antibiotic prescribing (per 1000 patients) with secondary safety outcomes. The data from practices participating in the trial and the dashboard infrastructure will be held within regional shared care record systems of the National Health Service in the UK.Ethics and disseminationApproved by National Health Service Ethics Committee IRAS 290050. The research results will be published in peer-reviewed journals and also disseminated to participating clinical staff and policy and guideline developers.Trial registration numberISRCTN16230629.

Risk of emergency hospital admission related to adverse events after antibiotic treatment in adults with a common infection: impact of COVID-19 and derivation and validation of risk prediction models

“…Krockow et al emphasised the need for effective strategies, such as behavioural interventions, to minimise repetitive antibiotic prescribing [ 45 ]. This underscores the significance of incorporating well-informed support tools in clinical decision-making [ 12 ]. In this study, developed prediction models will be incorporated into a Knowledge Support System (KSS) intervention, utilising a Learning Healthcare System (LHS) approach for antibiotic prescriptions related to common infections in primary care [ 12 , 46 , 47 ].…”

“…This underscores the significance of incorporating well-informed support tools in clinical decision-making [ 12 ]. In this study, developed prediction models will be incorporated into a Knowledge Support System (KSS) intervention, utilising a Learning Healthcare System (LHS) approach for antibiotic prescriptions related to common infections in primary care [ 12 , 46 , 47 ]. We conducted mixed-method co-design workshops with clinicians to assess the model’s acceptability among prescribing healthcare professionals and to identify key factors that could enhance uptake [ 48 ].…”

“…Studies highlight that implementing a more personalised evidence-based decision-making approach for antibiotic prescriptions could enhance patient care. The concept of prescribing based on a patient’s objective risk assessment and prognosis is gaining traction [ 12 , 13 ].…”

Pharmacogenetics Clinical Decision Support Systems for Primary Care in England: Co-Design Study

“…[21] An example of active alerts was implemented by van Staa et al to inform antibiotic prescribing in primary care with a view to improve the adherence to best practice guidelines. [22] Though such tools are useful, their impact on care and outcomes can be limited. A recent meta-analysis on clinical decision support systems by Kwan et al showing only small to moderate improvements in clinical endpoints.…”