·  Optimising the climate/environment

·  Improving nutrition

·  Maternal obesity

·  Tackling violence and promoting trauma-informed care

·  Tackling racism

·  Addressing delays and barriers in access to healthcare

·  Workforce development

·  Health literacy

·  Mental health

·  Miscarriage, stillbirth, and infant death

·  Multimorbidity

·  Infant feeding

·  Genetic disorders

·  Pre-pregnancy, pre-conception, and inter-pregnancy care

·  Community engagement and co-production

·  Working with underserved groups

·  Data and digital solutions

·  Addressing variation in clinical healthcare services

·  Improving the integration of the maternity ecosystem

·  Immigration and social policies

·  Translation and communication

·  Support for families and partners

·  Postnatal and aftercare services

·  Social influences and connections

·  Service location and accessibility

·  Commercial determinants of health

·  Workplace wellbeing and maternity leave policies

·  Intersectionality of disparities

·  Maternal death

·  Social housing and stability

·  Adolescent pregnancy support

·  Traditional medicine and integrative care

·  Community-based models

•Are there gaps or missing areas we need to address?

•What KPIs might be useful to consider?

•What research questions do you think we should be trying to answer?

• Some confusion over terminology

• Some overlap and not distinct entities

Framing need (ie level of action with overlaps coalesce together)

Can they be grouped/clarified in a way? Some feel like the same thing. Or is it like a grid? Ordering needed.

PPI important at any kind of level. Emphasis on technological solutions but also have to think about the unintended consequences.

Defining ethnicity in data is very challenging (if want to dive deep into reasons, we need to look at how we are defining the populations). How parents perceive ethnicity also different - the categories are not the same - a big challenge.

Maternity 'disparities' - define the word - areas of need?

Framing - Targeted vs universal approaches? (ie addressing the gradient of inequality or the gaps?) - additional targeted as well as getting house in order for everyone?

Some things we know work (eg staffing)!

Access to care important but "Acceptability" is important (and who decides that it's acceptable - some of the instruments are very crude - some things we should shift is the sophistication / quality of how we understand the disparities - but many areas not something off the shelf we can use) - METHODOLOGY needs to shift (crosscutting thread?) (eg in KPIs - maybe in each area do we need to review instruments that people have confidence in?) - need to update the nuance or disagreagation - maybe it's gap identification - are we gathering the right stuff - is it that we are not looking at the gap? If the data was capturing the data - do we have the right data and is it doing what we need to do? - Data & Digital should be together - methodology review - eg coproduction & digital solutions, how to make sense of the data & accessible) - surveillance?

Addressing dispraised in access - can we quantify I=on day 1 so we can see the change (quant & qualitative) - and how does that vary accross the regions & may been personalised based on region/ demographics. Need a benchmark

Service and systems - addressing delays and barriers in access to healthcare links with (what do we mean by delays? what is a KPI there?). Whatever KPI mean will have unintended consequences (interrelated - perverse effects) - KPIs need to be seen as nested (support each other) and what patients want (what women want / families - where PPI & coproduction comes in)

Proportionate universalism a key cross-cutting theme.

Can we use tools e.g. Health Equity Impact Assessment routinely/systematically to assess our plans/work

We think that poverty, racism, coproduction (separate to public involvement/engagement) are all cross cutting themes.

Access to services feels really important and how system is designed to meet people's different needs which builds in inequity

Behavioural understanding is important and potentially a cross-cutting theme - need to systematically break particular elements down into the different behaviours within a problem, e.g. access to services, obesity, racism.

Data and digital solutions feel like cross-cutting themes, possibly AI but not definitely.

Access to services (before, during, after, between pregnancy) is very important.

Inequalities based on ethnicity differ across regions, this needs to be taken into account when developing interventions. E.g. mostly white population in Northern Ireland, but racism is a big problem.

Need to consider emerging evidence, e.g. on how climate change (heat, floods) impact women.

Really important to keep going back to the EMBRRACE reports as a reference point; these are the statistics we want to change. Preventable causes of death highlighted repeatedly in these reports need to be tackled.

In addition to multimorbidity, also consider other chronic conditions with implications during pregnancy, e.g. diabetes and epilepsy (support needed from before pregnancy).

Data and digital innovations is key cross-cutting theme; while important to consider inequalities in/barriers to access.

Interventions have to be measurable in terms on maximum benefit to women.