WS1 Health Citizenship & Innovation

Context: Health citizenship is the active, meaningful and equitable involvement of people with lived experience of living with or caring (in a professional or lay capacity) for people with MLTCs. Citizenship in this project aims to integrate experiences and viewpoints of lived experience end-user perspectives at the centre of the design and delivery of innovations. 9 It will cultivate a system that enables members of the public and potential users of an innovative solution to be involved in its underpinning research, design and evaluation – to a degree of their choosing. This might involve: participating in community events; capacity building through training to understand elements of research; joining a network of public advisors; being mentored by an experienced public advisor to increase confidence in PPIE participation; or participating in co-creation/-design processes as potential end-users

Aims: 1. Continue (from Stage 1) our work with patients with MLTCs, clinicians, other health/care professionals and the public to promote health citizenship to ensure full stakeholder engagement and involvement throughout; 2. Advance community-based, co-produced, participatory research targeting seldom heard, marginalised and at-risk populations to embed equity-focused, value-driven, and design-deep involvement; 3. Offer opportunities for public representatives to become advisors, and patients to become co-design partners, increasing capacity for health citizenship through engagement and the development of community champions in our testbeds

Defining MLTCs and Describing Our Local Populations

We have undertaken extensive research to understand the patterns of MLTC combinations in our populations and their effects on health-related quality of life. Our Stage 1 project generated actionable population insights from re-usable NHS data assets in Liverpool and Glasgow to ensure our innovation hub is tailored to our populations’ needs. From these, we arrived at the common MLTC phenotypes described in our Stage 2 bid and the data supporting these can be found on our digital commons under Health Intelligence. We were, for example, able to show the importance of combined mental/physical and painful conditions in those attending unscheduled care. These combinations were also identified repeatedly and reported to be the most troublesome, throughout participatory research with community groups.

Recruiting Study Populations with a Diversity of MLTC Lived Experience

Equity and seldom-heard voices are central to SysteMatic: see Figure 1 and WS1 (page 7, “Drivers”). Our populations over-represent those with barriers to digital access, including people with limited (digital) literacy and/or resources (see also WS3, Rapid Evaluation, page 10).

We will use pop-up design studios to take our work into the communities with the greatest barriers to accessing digital solutions, involving them in iterative design, testing and evaluation. We will create community testbeds in both cities, targeting hotspots of deprivation and combinations of mental and physical MLTCs. We will draw on our well-established networks of community organisations, and on purposive sampling to ensure a representative diversity of lived experiences. We have requested costs for community outreach to 'warm up' our communities to the work of SysteMatic through targeted events and will hold 'town hall' meetings to involve residents in co-creating the driver projects. We note that the specific populations targeted to trial wearables will depend on the devices available, stage-gated evaluation (through WS3) and stakeholder insight (for potential applications in monitoring different aspects of the MLTC phenotypes, via Steps 1–4 of WS3 including design studios).

For the specific driver project P1 preventing medication harms Liverpool will recruit patients receiving medication for both mental and physical illness through NIHR’s Mental Health Research for Innovation Centre, Clinical Research Facilities and Research Delivery Network leveraging mature linked data systems and consent schemes. Equivalent recruitment in Glasgow will use Byres Community Hub (as we have done successfully in Stage 1) plus Glasgow Riverside Innovation District and NHS West of Scotland Innovation Hub for system-wide scale. The comparator will be the current standard of care. Our research with patients in Stage 1 and NIHR’s DynAIRx project confirmed poor preparation of patients for medication review. Outcome measures will include recruitment and retention rates and feedback on patient acceptability of interventions.

Equity, Technology Adoption and Digital Exclusion

Our approach incorporates comprehensive strategies to address trust barriers. Our engagement strategy goes well beyond simply "informing" communities about solutions. We propose to implement a structured trust-building framework developed through our preliminary work with underserved communities. Furthermore, we aim to develop a transparent Benefit-Risk Assessment and an evidence-based approach to building trust. In addition, our ambient sensing and natural language processing technologies are specifically designed to overcome traditional barriers, such as low literacy or language barriers, to digital health engagement: * Passive Data Collection: Our ambient sensing system operates without requiring active user engagement with digital interfaces, with participants’ consent. Sensors discretely integrated into the home environment capture health-relevant data (movement patterns, sleep quality, routine disruptions, heart rate, air quality) without requiring manual input, app usage, or device management from the user. * Natural Language Interfaces: Rather than relying on complex app navigation or text-based inputs, our system prioritises natural conversation as the primary interaction method. Participants can share health information through ordinary speech, which is then processed using our contextually sensitive NLP tools. This approach removes barriers for those uncomfortable with traditional digital interfaces or with limited typing skills. * Co-designed Accessibility Features: Working directly with people with limited digital experience, we will ensure early evaluation and iterative refinement of tools.

We note that we three of SysteMatic's team are already re-designing mental health services -- including new mood clinics] -- to better meet the needs of patients with MLTCs and poor digital access. This is one of the reasons we are prioritising voice-based conversational AIs.