The use of a critical realist intersectional approach informed by human computer interaction (HCI) methods to reveal racialised exclusions from digital healthcare services

Healthcare services are increasingly directing patients towards digital channels with a promise to provide better healthcare deliveries (Shaw & Donia, 2021; Greenhalgh et al., 2012), however, evidence demonstrates that digital technologies have played a role in exacerbating health inequalities (Latulippe et al., 2017; Veinot et al., 2018). The widespread adoption of digital channels in primary care services in the UK entailed by national (macro) level policy initiatives (NHS England, 2019; Scottish Government, 2021) has put some sections of the UK population at risk because they have yet to adapt to the ‘Digital First’ healthcare approach.

Minoritised ethnic (ME) communities in the UK, such as the Bangladeshi, Pakistani, Indian, Chinese, Black African Caribbean communities which are the focus of our research, are known to face multiple challenges to access and engage with digital health services due to disproportionately high levels of poverty in some of these communities, the digital divide, language barriers and socio-spatial exclusions (Karlsen & Nelson, 2021; Topol, 2019). Moreover, facilities which could help overcome ethnicity-related constraints, such as interpreting support and culturally-competent healthcare professionals, are limited in some GP services (Greenhalgh et al., 2023; Greenhalgh et al., 2007; Lokugamage et al., 2023). These constraints within both households (micro) and GP services (meso) contribute to lower levels of satisfaction in GP services (England, 2023; Wise, 2022), and delays in diagnosis and referral to speciality care (Lokugamage et al., 2023; Sripa et al., 2019). At present, there is limited understanding of the extent to which individuals from ME communities with overlapping attributes of identity (e.g. ethnicity, class, language, gender, age etc) encounter socio-technical challenges in using digital healthcare services. The need to close this information gap compelled us to undertake interdisciplinary research by combining narrative interviews and human computer interaction (HCI)-prompted audio-visual interviews to explore the conditions under which some individuals from ME communities get by, while others remain completely excluded from digital healthcare services.

Underpinned by a critical realist intersectional approach (Netto et al., 2020; Rodriguez et al., 2016; Schlesinger et al., 2017), we applied a two-tier qualitative methodology combining 100 in-depth narrative interviews with 15 follow-up audio-visual interviews. The in-depth narrative interviews indicated how participants’ ethnicity interacted with multiple dimensions of identity as well as language, (digital) literacy, levels of informal support and income to influence access and use of digitalised primary care services. Analysis of this data informed the design of the follow-up audio-visual interviews by enabling us to incorporate visual prompts such as examples of anonymised digital platforms which were currently being used in general practices in the UK. The use of such methods enabled us to capture more nuanced narratives of the barriers ME communities face in accessing digital healthcare, supported in some cases by visual evidence provided by participants of the experiences in the form of screenshots. Together both sets of interviews have enabled us to generate a rich and robust evidence base
for proposing more ethnicity-inclusive, culturally-competent and user-friendly interface designs to ensure the effective delivery of ‘Digital First’ primary care services.