Presenting Patient-generated Data in axSpA Care

Axial spondyloarthritis (axSpA) is a chronic inflammatory rheumatic disease primarily affecting the spine and sacroiliac joints. AxSpA usually develops in the second or third decade of a patient's life and impacts quality of life, mobility, function and work ability . Cornerstones of treatment are non-steroidal anti-inflammatory drugs, disease-modifying antirheumatic drugs and physical activity/rehabilitation . However, across the UK, there is huge variation in care provided for axSpA, and a significant residual burden on healthcare services post-pandemic . Capacity to deliver specialist rheumatology care is being exceeded by demand; the 2021 British Society for Rheumatology report highlighting a dangerous lack of consultants, specialist nurses and poor access to allied health professionals . The lack of healthcare capacity to meet demand is resulting in serious consequences for people living with rheumatic diseases in the UK, such as progressively worse health and debilitating pain . The 2022 NICE Impact Arthritis report suggested that support for education and non-pharmacological treatment is particularly lacking, making good long-term self-management more difficult for patients . Development of novel digital interventions to support patients in their self-management could revolutionise axSpA care in the UK by reducing pressure on healthcare services and ensuring that every patient has access to specialist treatment, thereby likely improving patient experience and clinical outcomes. The European Alliance of Associations for Rheumatology (EULAR, formerly European League Against Rheumatism) indeed suggest that digital healthcare is essential for supporting and optimising patient education and self-management in rheumatology.

As axSpA is highly variable across patients, personalised treatment plans are an important part of ensuring that patients receive effective care. However, as per current standard care in the UK, many people living with axSpA will see their rheumatologist or specialist physiotherapist once a year, or less - leaving them with 8,758 hours in a year where they must manage their condition somewhat independently . This results in limited time spent with patients in which to discuss treatment and management plans tailored to their individual needs. Additionally, previous work by Hue et al. with consultant rheumatologists and axSpA patients at the Royal National Hospital for Rheumatic Diseases (RNHRD), showed that clinicians were "acutely aware of time constraints placed on their interactions with the patient", and that these constraints limited opportunities for patients to lead conversations. It is therefore crucial that any activities that take place during consultations are as efficient as possible to maximize the time available for patients and clinicians to discuss topics that are important to them, and to collaboratively make decisions.

The increasing maturity and availability of digital health applications and wearable technologies are allowing patients to collect large amounts of health and lifestyle data outside of the clinic. This data can support patients in tracking their symptoms and disease progression, and has the potential to support existing patient-reported evidence that is often subject to recall bias, and is limited in its collection by appointment attendance. While a systematic review by Demiris et al. highlights several studies investigating the use of patient-gathered data in clinical practice, attempts to collaboratively use patient-gathered data in the clinic have been met with many challenges. These include a lack of mutual expectations between patients and clinicians when reviewing this data , clinical time constraints , and difficulties interpreting non-standard data formats . These challenges, among many others, highlight the importance of systems and visualisations that can support the efficient and meaningful use of patient-gathered data in clinical contexts.

At the Royal National Hospital for Rheumatic Diseases (RNHRD), Royal Untied Hospitals (RUH) Bath, a new digital health platform has been implemented for axSpA care. This platform helps patients to track their symptoms, share health data with their clinicians, review this data in clinic, and access educational resources. As this platform has not yet been evaluated in clinical practice, and given the historic barriers to utilising PGHD in clinic, it is important to understand how the platform is being used across the axSpA care pathway, and the experiences of clinicians and people living with axSpA in using the platform.

The study consists of three methodological approaches for data collection:

1. Observational study The first part of the study will involve observations and recordings of scheduled routine axSpA consultations. An observational approach was chosen to ensure that the role that the platform plays naturally in consultations is captured and understood. This method of data collection also aims to minimise intrusions or interruptions for participants, allowing them to focus on their consultation without needing to stop to fill in questionnaires or other forms of data collection.
2. Semi structured interviews The second part of the study will involve semi-structured interviews with patients and clinicians to gather their perspectives on the platform and how it was used during their consultation. A semi-structured interview format was chosen to allow participants to speak more freely about any points they feel are important, while retaining a focus on the topics relevant to the research questions.
3. Co-design workshops The final part of the study will involve optional co-design workshops with patients and clinicians. These will run as group sessions, in which participants will be asked to reflect on their experiences with the platform, and to co-design potential new platform features and use cases, aided by creative tools such as paper and pens to draw any ideas.

The objectives of this research are to understand: (1) how this platform is used during consultations to interact with PGHD; (2) the barriers surrounding its uptake and impact within axSpA care; (3) the perspectives of patients and clinicians on the platform and how it is used, and (4) the requirements of patients and clinicians for future versions or features of the platform. To guide and structure the process evaluation, a logic model will be created of the axSpA care pathway, with input from axSpA clinicians, academic researchers, and patients. This logic model will form the basis of the evaluation, which will allow for a better understanding of how the platform is (or is not) supporting the outputs and impacts of the logic model.

The outcomes of this research will be (1) qualitative analyses of consultation recordings to investigate how the platform was used to interact with PGHD; (2) thematic analyses of patient and clinician perspectives on the use of the platform during consultations; (3) outputs from co-design workshops exploring patient and clinician requirements for future versions and features of the platform. Ultimately, this research will provide a greater understanding of how the platform is used, the next steps to ensuring its future success, and the success of similar platforms. The findings from this research will be shared with the developer of the platform (Inhealthcare) to guide the development of subsequent versions of the platform, which will have a local impact at the RNHRD. The results will also be shared across the wider axSpA and rheumatology network to ensure that the findings are useful and generalisable beyond this project.