There is much evidence that as health services became digitalised, new kinds of inequity emerge, producing what one author has called the ‘digital inverse care law’ (patients most in need of care are even less likely to be able to access it than previously).120 As discussed in previous sections, equity was one of the main themes covered in this qualitative study. There is much evidence as that as health services became digitalised, new kinds of inequity emerge, producing what one author has called the ‘digital inverse care law’ (patients most in need of care are even less likely to be able to access it than previously).120 We took seriously the challenge of ensuring that our findings would apply to disadvantaged, underserved and seldom heard groups, and addressed this challenge in the following ways:
- While seeking a maximum variety sample of general practices, we oversampled from more deprived postcodes. Using the Index of Multiple Deprivation,121 there were four practices in the most deprived decile by postcode, two in the 2nd (next most deprived) decile, one each in the 3rd, 6th and 8th deciles, and two each in the 7th and 9th deciles.
- As noted under Approach to patient and public involvement, we supplemented our online PPI group with an additional patient panel recruited from individuals who had complex life circumstances, few or no digital devices and low digital literacy.
- We identified digital inequity as a major theme early in our study, and also identified that this theme had up to now been poorly theorised. This informed our study of digital care navigation for people with social care needs. We worked to develop and apply theory, and produced several novel theorisations of digital inequity.19,63,66
- We obtained additional funding for two linked PhD studies on multiply disadvantaged groups. One of these focused on elderly people from racially minoritised groups living in deprived postcodes and the other focused on patients from ‘Deep End’ practices serving populations with complex needs (including drug and alcohol use).
- When selecting participants, we actively sought to achieve diversity not merely in the different axes linked to disadvantage or discrimination (income, gender, age, race/ethnicity, health status, educational status) but also in intersectional factors (the participant who is poor and elderly and from a racial minority and low literacy and has multiple health conditions). Our work on digital personas was developed to draw these intersectional influences together.71
Despite these efforts, we did not cover every complex need group and our findings will need to be interpreted with attention to whether they are likely to apply to other groups.