Patient centred care needs patient centred planning

It is well recognised that our wealth, or lack thereof is linked to our health, those who are the least deprived can expect to enjoy better health and live longer. Increasingly, we see that other factors, including ethnicity, can be key determinants of healthcare interactions and outcomes. As demonstrated by the COVID-19 pandemic and its pronounced effect on certain ethnic populations, who we are can affect our health in many ways. As discussion and research has continued into outcomes around diseases which affect minority groups disproportionately, some have suggested that behaviours may play an important role alongside genetics and background, for example, older males may present less frequently to a GP for example. We know that certain groups across the UK and indeed the world, will be disadvantaged by institutional and personal racial attitudes, and that these can feed into many circumstances and challenges for people, even something which some might consider unrelated, choice of employment, which may in some fields have a higher risk of health effect.  

The challenges commissioners and providers face in attempting to ensure equity for all patients are complex, and beyond the scope of a single article, however, in well intentioned efforts to correct imbalance, are we still missing a part of the puzzle? 
 
We tend to group people according to outwardly obvious factors, the colour of their skin, their age, their economic status. In doing so, we continue to homogenise a disparate group of people. As has been shown throughout the COVID-19 pandemic, behaviours vary dramatically between different members of the same socio-demographic groups. One area which has shown this to be true is social media. Throughout the COVID-19 pandemic, populations have engaged in differing behaviours with regard to risk aversion, healthcare interaction and even public health monitoring and intervention. While some aspects of this may at times be due to cultural factors, the spread of disinformation and conspiracy theory has affected similar populations in very different ways, ranging from refusing to wear masks to shying away from seeking medical attention to declining COVID-19 testing. 
 
Similar messages may affect people in different ways dependent on their beliefs, for example, a “COVID-19 is a hoax” message may be received differently based on what else people have read. Someone who shares anti-mask sentiments may happily engage with healthcare when they require it, by the same token, someone who has seen posts suggesting that local hospitals are not treating people like them and instead are “letting them die” will likely wear a mask, but shy away from approaching a hospital if they become ill.  It is important to understand the difference as both people will be at different risk, one, a higher chance of contracting COVID-19, the other, a potentially greater chance of becoming seriously ill.  
 
We know these problems have occurred, and health systems have responded in many cases with admirable information campaigns and outreach, but these solutions were reactive rather than proactive. 
  
Social media is unlikely to go away or be reformed while at the same time being a key influence on the attitudes of people today. Increasingly then, as population health management becomes more important, so too will understanding the underlying social attitudes of different populations within an area. This will not be able to be simply done based on age, background or wealth. Instead, organisations will need to engage with the populace they are tasked with looking after. We live in a society which is increasingly polarised in its beliefs, but in social media, we have an opportunity to see what people are saying, how they view the world. Healthcare organisations can and should leverage the ability to utilise social media, not to see what 1 person is saying, but to identify prevailing attitudes. Data science, natural language processing and sentiment analysis are words you may hear and associate more with artificial intelligence, but these technologies can allow us to derive insight into the attitudes of communities and model the care, settings and messaging they are provided to ensure that all people are able to engage with primary, secondary and population healthcare in a way that makes them comfortable and that builds trust. We talk of targeted health interventions, but if we don’t know our patients, we are doomed to miss the mark. 

By Neil Mason, Head of Healthcare Strategy