The Digital Divide RT3– Reducing inequalities for better health

Covid-19 has revealed huge inequalities when it comes to digital transformation. In March last year, the classroom was downloaded onto Zoom and left thousands of children behind in the process. When it came to health, the pandemic accelerated what has always been an inevitable move toward digital over the past decade.

The digital and health inequality debate is often pitched as binary: either we move toward digital and leave underserved populations behind, or we don’t move technological advancements along to accommodate for those people. PPP’s health inequality work in 2022 will focus on what digital health can do for underserved populations. Focusing on underserved populations, this report will produce recommendations as to how technology can reduce health.

Inequality – including the use of data – at every point. With the NHS having asked Integrated Care Systems to be written into law by parliament, the need for ICSs to be utilising data to address health inequalities has never been greater. Whether society is ready for it or not, digital transformation is the future of healthcare and as such, good policy is in urgent demand when it comes to addressing those at risk of being left behind. We aim to meet that demand with this exciting piece of policy work in 2022

Agenda for this session

This roundtable will focus specifically on accelerating cross-sector approaches to reducing health inequality through merged datasets using both quantitative and qualitative data. The more datasets from different sectors can be joined up and analysed, the more tailored health services can become for underserved populations.

During this roundtable, participants are encouraged to explore the key challenges that need to be overcome to ensure this. The second half of this roundtable will focus on how trust and confidence can be built in digital, data and healthcare in underserved populations.

In order to collect data from under-served communities, trust in digital, data, and the healthcare system must be built. How can the process of data collection be made more trustworthy to get these underrepresented communities represented in data relating to health and its determinants? Should we approach data collection and processing in a different way, in order for these processes to be trusted by communities who are understandably mistrustful of healthcare and data usage?

Addressing inequalities also means asking when we should not collect data and why. Data collection should respect an individual and community expectations and boundaries. In some cases, being digitally included, or included in datasets, may cause more harm than good. How can we collect data in ways that benefit underserved communities most?

Format of the session

Speakers present for 5-10 minutes, which is followed by discussion. We tend to have 3 speakers per session. Discussion is solution oriented, and practical policy solutions to problems are sought.