Routine data (ie, data collected for clinical or administrative purposes) have long been used to describe and quantify end-of-life experiences, including inequitable outcomes. For example, studies using routine data have shown consistently that in high-income countries, people with lower socioeconomic position access hospital-based care more and specialist palliative care less in the last months of life.1 Population-based data, predominantly from the USA, have highlighted racial inequality in access to pain relief, showing that black, Hispanic and Asian patients are less likely than white patients to receive pain medication.2

Routine data studies also showed that the COVID-19 pandemic exacerbated health inequalities across the life course including towards the end of life where there was evidence of widening inequality in place of death and access to care.3 4 Before the pandemic, health inequalities were estimated to cost the US economy US$154.9 billion a year in excess medical care expenditures.5 There is now a strong moral and financial imperative for delivering more equitable palliative and end-of-life care.6 Within this agenda, there is an important role for routine data, not only to describe the problem of inequality but to inform decision-making. We outline three sets of challenges and opportunities for using routine data to address inequality and inequity in palliative and end-of-life care.

The first studies highlighting an association between area-based deprivation and place of death were published more than 30 years ago. Yet, even for this most well-described indicator, studies investigating the causes of this inequality remain rare.1 Routine data studies can be used to unpick for who and why inequalities emerge in palliative and end-of-life care, and in doing so help to understand the causes of inequalities and how to reduce them.

Inequalities in palliative and end-of-life care are not necessarily uniform across all groups in society …