Skip to main content

Developing a shared definition of self-driven healthcare

Writing in the Journal of the Royal Society of Medicine, myself, Austen El-Osta and Chris Rowe set out a vision for building sustainable, self-driven healthcare spanning primary care, secondary care and the wider health and social care system has been set out by medical innovators. Self-driven healthcare (SDH) is an umbrella term introduced by Innovate UK, the UK’s national innovation agency, to conceptualise aspects of healthcare delivery that can support people in becoming more engaged in managing their own health and wellbeing, rather than being passive receivers of healthcare.

In our paper, we describe an SDH ecosystem that supports individuals to take more ownership of their health and wellbeing and in recording their own data (e.g. weight, blood pressure) using a phone app, tablet, computer or Bluetooth device. This self-generated data would then be uploaded onto a secure online SDH portal which holds all their health records, including those generated in the wider healthcare system.

Individuals would also enter other data such as what medication they had taken that day, the food they had eaten or the exercise they had done. They may even have a range of other devices that automatically record and upload useful information, such as environmental data about local air quality that day. A personalised dashboard would automatically present the user with their ‘digital twin’ and the portal may also be enabled to routinely offered insights and actionable advice, including microlearning and behaviour change interventions and a holistic picture of the person’s overall health and wellbeing status.

The SDH approach must create better access to all sections of the community rather than just wealthier and more technically literate individuals. It is also crucial that the SDH movement does not exacerbate inequalities due to the digital divide. How SDH is adopted in the future is very important, especially when it is applied to help enhance the consumer health system by trying to link it effectively with state-funded NHS health and social care systems. It will be important to determine if these online environments will be provided by expanding the NHS App, for example, or by commercial companies.


Comments

Post a Comment

Popular posts from this blog

What is the difference between primordial prevention and primary prevention?

Primordial prevention and primary prevention are both crucial strategies for promoting health, but they operate at different levels. Primordial prevention aims to address the root causes of health problems and improve the wider determinants of health. It focuses on preventing the emergence of risk factors in the first place by tackling the underlying social, economic, and environmental determinants of health. This involves broad, population-wide interventions such as: Policies that promote healthy food choices: Think about initiatives like taxing sugary drinks to discourage unhealthy consumption, or providing subsidies for fruits and vegetables to make them more accessible. Urban planning that prioritises well-being: This could include creating walkable neighborhoods with safe cycling routes, ensuring access to green spaces for recreation and relaxation, and designing communities that foster social connections. Social programs that address inequality: Initiatives aimed at reducing pov...
Post a Comment
Read more

What makes a good doctor – and who gets to decide?

What Makes a Good Doctor? This is the question that Waseem Jerjes and I explore in the Journal of the Royal Society of Medicine . It is a key question that underpins the architecture of medical education, clinical practice, regulation, and professional identity. It cannot be answered by regulators, educators, or employers in isolation. It must be answered together – by doctors and patients – revisited throughout a career, and adapted as society and the profession change. Without that shared reflection, the danger is not simply disillusionment, but the erosion of the moral foundations of clinical work. As we enter an era when diagnosis will increasingly involve artificial intelligence and when performance metrics reward volume over value, reclaiming this question as a professional one is imperative. The integrity of our institutions – and of the practitioners within them – depends on reimagining excellence in inclusive, relational terms. A good doctor is not a flawless technician or a f...
Post a Comment
Read more

Relevance Over Recall: Rethinking How AI Uses Clinical Data

Our article in the Journal of the Royal Society of Medicine argues that safe and effective AI in healthcare must incorporate mechanisms that emulate human judgement - down-weighting old, inaccurate or superseded information and prioritising what is recent, clinically relevant and reaffirmed - so that AI supports, rather than disrupts, high-quality patient care.  Clinicians constantly revise, reinterpret and filter past information so that only what is relevant, accurate and timely shapes present-day management decisions; medical records function as dynamic “working tools” rather than fixed archives. By contrast, many AI systems lack this capacity for selective forgetting and often treat all historical data as equally meaningful.  This can lead to outdated or low-confidence diagnoses being repeatedly resurfaced, persistent labels influencing clinical expectations, and irrelevant, long-resolved events cluttering summaries and decision-support outputs. Such indiscriminate recall...
Post a Comment
Read more