Building inclusive solutions for underserved communities

Barts Life Sciences is located in north-east London which is home to one of the most diverse populations in Europe. This diversity enriches and enhances our ability to reduce health inequalities and improve outcomes for people in London and the world. 

As healthcare increasingly adopts digital technologies, it is essential that these innovations reach all populations fairly. We speak to Professor Chloe Orkin, Dean for Healthcare Transformation, Director of the SHARE Collaborative for health equity and Professor of Infection and Inequities, about the urgent need to address healthcare inequities through digital health. Drawing on her extensive experience, she explores how systemic issues like racism, sexism and digital exclusion can be mitigated to ensure that new technologies serve everyone – especially the most marginalised communities. 

Note the views expressed herein are those solely of the author. 

What do you see as the most pressing inequities in healthcare that digital innovation could address, and where do you think we are falling short? 

The most pressing inequities in healthcare are structural. They’re rooted in systemic issues like structural racism and sexism – legacies baked into our medical models, perpetuated through obsolete curricula, and still shaping our research and practices today. 

Let me give you an example. For instance, a woman in Tower Hamlets will have a shorter healthy life expectancy than a man by about 7 years. This inequity highlights the impact of the gender health gap.  

As a university, we know research is critical to closing these gaps. Without research, we lack the knowledge to develop interventions that could mitigate the gender gap. Structural sexism underpins this lack of innovation. For example, only a tiny fraction of the UK’s research budget has been allocated to female-specific health conditions like endometriosis. It’s been seen as less urgent, meaning it can take up to a decade for someone to receive a diagnosis. On top of that, there’s little innovation in treatments. Why? Because the condition simply hasn’t garnered enough interest and attention. That’s structural inequality in action. 

It’s important to understand that these inequities don’t exist in a vacuum. Structural racism is another stark reality. Take the intersection of racism and sexism in maternal outcomes: Black women are four to five times more likely to die during childbirth. This shocking statistic reflects how deeper systemic issues like racism and sexism can compound inequities in healthcare. 

Recent scandals have put a spotlight on this, but at the core lies one simple truth – Black women often aren’t heard. When they talk about their symptoms or concerns, their voices are frequently dismissed. Worse still, they’re sometimes stereotyped as ‘aggressive’ when they’re simply being assertive. When these biases compound, it can create a tsunami of racism and sexism. 

So, where does digital health come in? One possibility lies in limiting the impact of subjective biases inherent in clinical decision-making. Tools like large language models could help identify concerning symptoms more objectively – analysing medical tests or patient data to flag risks without the human prejudices that can often distort these clinical assessments. It’s about using technology to ensure everyone’s medical history is equally heard and treating people as credible narrators of their own experiences. 

How do you foresee digital health solutions improving access to care for underserved populations, particularly in infectious disease prevention and treatment? 

Digital health technologies are designed to reduce inefficiencies, improve access, lower costs, and personalise medicine. They can empower people who are able to access and use them to better track their health and wellness, but their potential to improve access for underserved populations is even more significant. 

For example, digital tools and telehealth can offer alternatives for people who may fear discrimination and be reluctant to engage with traditional healthcare settings. Someone who doesn’t feel comfortable visiting a clinic might be more open to using a telehealth platform or a digital tool for self-monitoring and management. 

Let’s take mpox (formerly known as monkeypox) as a case study of a condition particularly affecting men who have sex with men. AI has the potential to transform how we identify and manage cases of emerging or re-emerging infections. For instance, when non-specialists encounter a patient with symptoms, cases can often be missed. But large language models, trained on vast datasets, could interpret electronic health records and flag suspected cases with more accuracy and reliability. This could help clinicians identify these infections earlier, reducing missed diagnoses and limiting transmission. 

Other innovations, like imaging systems using trained AI algorithms, could assist in diagnosing skin lesions, which are a key symptom of infections like mpox. During COVID-19, we also saw geospatial tools come into their own – alerting you when you were near somebody with COVID. These technologies could be similarly applied in future infectious disease outbreaks, providing public health professionals with real-time data to guide interventions. 

This type of technology could also help in determining where outbreaks are occurring and focusing efforts on these areas, making responses more targeted and effective. In essence, digital health solutions have the power to bridge gaps in care, especially during outbreaks, by making healthcare more accessible, efficient and proactive for populations that need it most. 

From your experience as a Consultant Physician, what barriers do clinicians face when integrating digital health technologies into patient care, especially for marginalised communities? 

One of the biggest issues is digital exclusion. At its most obvious, this means people not having access to the devices – like smartphones – needed to support innovations like apps for data tracking or accessing medical appointments, such as the NHS app. Some people don’t have these devices, while others may lack the digital literacy to navigate them. For instance, many don’t know how to download an app or use it effectively. This can be an important barrier for older adults. Language barriers are another challenge, with most apps being designed in English, making them less accessible to non-English speakers. 

Digital exclusion isn’t just about access to devices; it’s also about access to skills and support. Many of us have had to teach a parent how to use a smartphone, but not everyone has someone around to provide that help. Think of people living far from family or in isolated circumstances – without support, engaging with digital tools becomes even harder. 

Motivation and trust are also significant barriers. People need to understand why using a new technology matters and how it can benefit them. But even with that understanding, trust can be a hurdle – trust in the technology itself, trust in those recommending it, and trust in what will happen to the data collected. 

So, when we talk about digital exclusion, it’s important to ask: Can someone access or afford a device and the internet to engage with the technology? Do they have the skills or language abilities to navigate it, or access to someone who can support them? Do they see the value in using this technology? And, crucially, do they trust the technology and the way their data will be handled? 

Beyond exclusion, there’s also a lack of public understanding about the scope of digital health. Most people don’t realise the extent of data being collected through wearable devices or smartphones – what’s being tracked, how it could be leveraged to improve health, and who owns or controls that data. While this data has immense potential to improve well-being, the nuances of its use – both beneficial and questionable – are not widely understood. 

These barriers make it clear that integrating digital health into patient care requires not just innovation but education, trust-building, transparency and accessibility at every level. 

How can data-driven technologies help reduce health disparities? Are there risks that digital health could unintentionally exacerbate inequities if not implemented correctly? 

Digital health tools have huge potential to improve how we diagnose and treat patients and deliver personalised medicine. From general wellness apps to wearable devices, telemedicine, and medical applications, they’re already changing the way healthcare is delivered. But how they’re designed and implemented is key to ensuring they don’t unintentionally widen health inequalities. 

Take something like pulse oximeters, which monitor oxygen levels in the blood. During the COVID-19 pandemic, these became critical for both home and hospital care. But it was discovered that they were far less accurate – and sometimes completely ineffective – on Black skin. 

How did this happen? The devices hadn’t been tested properly on Black populations. White skin was very much treated as the norm during development, and no one questioned whether they’d work for people with darker skin tones. This kind of bias isn’t limited to healthcare tech – similar examples exist across society, whether it’s tights or makeup historically being made only in shades that match white people’s skin tone, to optical technologies that haven’t been designed to include ethnic diversity. 

This bias has real consequences. In healthcare, it means tools like pulse oximeters may fail to pick up serious conditions in certain populations. This can actually be extremely dangerous.  

There has even been a legal case filed in the US against pulse oximeter manufacturers and distributers based on racial bias in the devices and whether this failure led to unnecessary fatalities. In healthcare, this kind of oversight can be fatal, with vital conditions going undetected because tools like pulse oximeters weren’t designed to work on everyone equally. 

When we talk about digital exclusion, what does this encompass, particularly in healthcare settings? 

It’s crucial to establish equity frameworks when developing digital health and AI innovations such as the University of Sussex framework to avoid further marginalising vulnerable populations. A major part of this is understanding the complexities around mistrust – especially in healthcare professionals and authority figures. There’s an enormous level of mistrust in science and in those who provide care, and it’s not just about vaccines. This impacts everything from general healthcare services to mental health support. 

When we think about building trust, we must consider people that may be particularly wary of healthcare services – like migrants or individuals accessing mental health services. It’s vital that we build and maintain trust in digital health by using only highly reliable, secure technology which is explainable. This includes making sure there’s proper clinical oversight and transparency, with technology being thoroughly tested with real patients and not just the typical populations that step forward for every study, which tend to be young, white men. 

Testing digital health tools in a diverse range of populations, providing clear information on data security, and being upfront about how health data will benefit the individual is essential. It’s also important to limit the transfer of data through third parties and to really use the NHS brand to strengthen trust. 

Another key consideration is fairness – people shouldn’t be excluded from healthcare just because they don’t engage with digital tools. Not having the right devices or digital literacy shouldn’t mean someone is left behind. We need to ensure there are offline or analogue ways to access good care. 

The question of who is responsible for providing devices also needs to be addressed. Should we look at social prescribing to help provide the necessary tech, just like we do for exercise or other forms of care? Like the NHS app, could other essential apps be made exempt from charging? What role could local authorities and libraries play, and what partnerships with internet service providers could be established to help those facing digital exclusion? If we’re moving toward a more digital approach to healthcare, it’s our responsibility to figure out how to bridge this gap. 

About the author 

Chloe has been a Consultant Physician at Barts Health NHS Trust since 2003 and was appointed by Queen Mary, University of London, in 2019. She leads an internationally renowned therapeutic trials unit that has made major contributions to the development and licensing of more than 20 novel therapies including the first ever long-acting HIV injectable treatment. Her research focuses on inclusive study design and the ways of including and engaging women, pregnant people, racially minoritised people and older adults in clinical trials. 

She was advisor to WHO Europe during Mpox and COVID-19 pandemics. Chloe has held multiple leadership positions including Chairing the British HIV Association, leading on Equality Diversion and Inclusion and is immediate Past President of the (MWF). She is a member of the governing council for the International AIDS Society. Chloe led the practice-changing blood-borne virus testing campaign Going Viral. She was awarded an MBE for services to the NHS in 2024.