Transforming patient experience into valuable insights

What support networks exist for people with long-term conditions requiring specialist treatment?

Long-term conditions affect around 15 million people in England, with many needing specialist care. Learning to live with a specialist long-term condition requires a strong support network of healthcare professionals, family, friends and loved ones.

“The Company”[1] is a charity-run social network that fosters a unique and diverse community of over 40,000 people affected by a long-term specialist condition. It connects people remotely so they can share personal experiences, and hosts platforms and tools to facilitate autonomous peer support.

The social network is a collection of hundreds of thousands of textual data points, for users all around the world. The Company asked Edge Health to help it to understand how its data could be used to provide greater insight and understanding to its clients and the pharmaceutical companies that provide them with life-changing treatments.

Edge Health possesses the skills to extract maximum value from complex and nuanced data

Edge Health was selected to help because of their deep understanding of healthcare data and the importance of privacy and information governance. It was essential to ensure the security and confidentiality of The Company’s personal and identifiable data.

The interactions on the social network create a rich text-based source of information. Edge Health undertook an exploratory investigation on what could be learnt from data relating to two different pharmaceutical treatments that represent over a quarter of the market in England. This analysis was expanded to include data on all treatment courses for the long-term condition, using tools ranging from natural language processing (NLP) and sentiment analysis to multiple correlation analysis.

Edge Health worked with The Company to extract valuable insights, using these analysis methods to understand user preferences and discussions surrounding topics specifically relevant to the long-term condition. This was especially true at product launch where user sentiment activity spiked on the site as users shared and discussed experiences of new treatments – experiences that are often unseen or overlooked.

Marked-up and classified text data is a rich source of information – it provides countless unique perspectives on real-world events

Changes in conversation topics and post activity revealed posts on the social media network closely mirror real-world events. Post activity regarding certain treatments for the condition were linked to market availability of drugs, driven by changes in supply due to manufacturing and the COVID-19 pandemic.

Current and ubiquitous models provide a retrospective view on how the drug market has changed. Novel analysis by Edge Health showed that interpreting the buzz around a new treatment can provide real-time insight and be a leading indicator.

This novel use of real-world data emphasises the need to understand user perspectives. These data can be harnessed to develop a better understanding of who individual users are, an empathetic understanding of what they value, and how conversations on the platform reflect real-world events. It provides an opportunity for pharmaceutical companies to better tailor the development of their products, and to seek to better understand and support new or prospective users.

Extracting maximum value from text data for healthcare partners will lead to improved patient outcomes, as patient needs are better understood

As social media platforms like The Company continue to grow and expand into the health care sector, they offer substantial opportunities to deliver societal value. They possess rich data sources with potential for a variety of applications. However, to fully utilise the qualitative data from such sources to its full potential, high quality data collection and processing is necessary as well as tailored methods of analysis.

Interpreting a dynamic and nuanced data source requires modern analytical solutions. This includes techniques that longitudinally track discussion sentiment, effectively segment users, and use “smart” topic categorisation. These are necessary to filter masses of textual data, and to respond to and interact with key changes happening within the community.

The analysis by Edge Health and The Company demonstrates immense potential to better understand user preferences, to tailor and enhance the user experience, and to identify and strategize around areas of improvement on the platform. This can enable healthcare partners and pharmaceutical providers to optimise their products which in turn would improve quality of life for those affected by long-term conditions.

[1] Anonymised for confidentiality reasons