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Discussion
This work focused on developing the infrastructure to support optimisation of antibiotic prescribing in primary care in England using a learning health system.
To date, this project has successfully developed and implemented a trustworthy system within the HSCN capable of extracting and processing patient-level deidentified data and fed back actionable results to individual practices. In contrast to traditional feedback that compromises summary statistics, aggregated practice-level analyses, CCG and regional level assessments, this web-based platform is able to deliver information on prescribing at both the practice and patient level for each practice. Demonstrating a mechanism that allows practitioners to: query prescribing patterns by infection; observe prescriptions that deviate from recommended guidelines; improve prescribing based on the risk of hospitalisation in addition to symptom severity; as well as obtaining a holistic overview of their prescribing volume compared with peers. These mechanisms in turn will help optimise antibiotic prescribing and improve patient care. The analysis has observed significant variability in the prescribing of antibiotics, for example, some practices prescribed antibiotics to patients with an upper respiratory tract infection just 10% of the time, while other practices prescribe antibiotics 80% of the time, a problem well recognised nationally.12 13
Involving stakeholders throughout the process gave the infrastructure validity, codesigning a tool with end-users ensured each element of the tool was necessary and enhanced the utility of the product for each clinical need. Regular communication with stakeholders throughout the design process and during the pilot phases allowed for continuous modification to the platform in use, making it more fit for purpose with each redeployment. Once more, involvement of stakeholders at each stage has encouraged uptake and repeated regular use of the tool. Stakeholders recognise that the product was developed to assist them in their day-to-day work and contains features they personally recommended. This codesign and feedback process will continue to focus the analysis and the development of additional features within the platform that fit the evolving needs of each practice, providing continuous support to optimise antibiotic prescribing.
To validate the data displayed in the dashboards, first, all consultations resulting in antibiotic prescriptions were extracted from a large national database (~5.2 million patients) and the associated medical codes were grouped by infection type and reviewed by two clinicians. In order to evaluate any missing codes, the codes that occurred more frequently (OR >3) on the date of an antibiotic prescription compared with control were also reviewed and added to the code lists where clinically relevant. The second stage of validation involved visiting partner practices and reviewing their dashboard data. Here, we were able to further improve the grouping of the code lists as well as the data processing steps taken in the analysis. However, the limitation remains that until coding improves there will inevitably be some incidences displaying an unrealistic representation of a consultation (e.g., a prescription deviated from recommended guidelines but in reality, this may have been appropriate but inadequately entered into the system). Our partner practices agree that as part of this study, focus on improved coding will improve their practices dashboards for review.
One major challenge to overcome was the translation of coding across the three different systems as practices also used different versions of the same systems producing discrepancies in medical coding with no mapping catalogue available to translate different versions to one common data model. In the NHS in England, there is a challenge to get very different and disconnected systems to communicate, but this work demonstrates that this can be done on a system-wide level within primary care.
The infrastructure is currently active in 70 primary care centres across England. Future work includes a formal evaluation of the impact the platform has on antibiotic prescribing post implementation, as well as supporting a full scale roll out across the UK, of which discussions are ongoing with PHE. However, the project has observed an association between frequent review of practice-specific dashboards and behavioural changes within our partner practices. Recent feedback includes the desire to identify individual prescribers within a practice for prescribers to be accountable for their actions. Furthermore, practices are enthusiastic to investigate new interventions within their own practice and assess the effect each intervention has, for example, there is interest in reviewing how rescue packs for patients with chronic obstructive pulmonary disease are issued, as well as piloting a point-of-care test to distinguish between bacterial and viral infections.
Ultimately, the platform gives back control to practices, ensuring they are equipped to monitor, but also take responsibility for, their antibiotic prescribing. Additionally, practices that are targeted for overprescribing now have the evidence to defend (when necessary) their prescribing decisions using the more in-depth and detailed analysis compared with traditional aggregated prescribing assessment at the practice and CCG levels. Furthermore, a practice can pilot different interventions and review the impact each intervention has on their prescribing overtime, allowing for rapid uptake of interventions that work and rapid removal of those that fail; optimising antibiotic utility further and improving the quality of care their patients receive. This in turn can instigate a variety of changes within different practices, ultimately optimising prescribing across the UK as a whole. In the future, this infrastructure can be made available for other priority areas in health, adopting a data-driven approach to improve patient care, delivering research that is relevant, effective and can have a real impact on public health.
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