Mitigating inequalities at a large COVID-19 vaccination centre

ABSTRACT
Introduction The COVID-19 vaccination service is a key component in the UK approach to reducing disease morbidity and mortality. Groups within the population at increased risk of severe outcomes from COVID-19 overlap with groups that are less likely to take up the offer of vaccination. This article outlines some learning from approaches within a large vaccination centre in the UK to reduce inequalities.
Solution Continuous quality improvement processes were used to operationalise the mitigations to inequalities with vaccination uptake that were identified by a systematic equality impact assessment framework and continuous service feedback.
Outcome Quality improvement processes and community engagement enabled tailored mitigations to vaccination uptake. Engagement with community ambassadors strengthened community relationships and the co-creation of bespoke sessions encouraged vaccination uptake within specific groups.
Conclusion Recommendations for strengthening approaches to inequality reduction include having a systematic framework for assessment and mitigation of inequalities, embedding quality improvement, identifying resources, and taking a collaborative and co-design approach to services with underserved groups.
Introduction
The UK COVID-19 vaccination programme aims to reduce disease morbidity and mortality by maximising vaccine uptake across the population within a national framework.1 Large vaccination centres (VCs) were set up rapidly to support the pace and scale of roll-out. The VC in this article used a large conference centre in Bournemouth, a town in the county of Dorset.
The risk of severe illness and death from COVID-19 is increased for people who are older, are male, are from more deprived areas, are within specific ethnic minority groups, have a physical illness and have vulnerabilities. COVID-19 is widely acknowledged to have exacerbated and highlighted the impact of health, social and economic inequalities.2,3 Early data on the COVID-19 vaccination programme indicated lower uptake among specific ethnic minority groups and individuals from more deprived areas.4,5
Dorset county, and the Bournemouth, Christchurch and Poole (BCP) areas have a higher proportion of adults aged over 65 years, with health and life expectancy generally better than the national average. Although this an area that includes prosperity, there are pockets of significant deprivation and evidence of health inequalities.6,7
Multi-component approaches are recommended to address vaccination inequalities.8 There is a need for evaluation and evidence gathering to ensure that future robust evidence-based approaches through prioritisation and roll-out of vaccinations are used to prevent the widening of inequalities.9,10
A continuous quality improvement (QI) process was embedded within a large COVID-19 VC setting. The aim of this paper was to identify changes to the service resulting from the actions and methods used to mitigate inequalities in service-user experience of the VC. The outputs from continuous improvement measures have been described and learning was identified to support future application of QI methods within this setting. We have included two case studies of mitigation measures used to reduce inequalities, alongside learning gained from them.
Methods
The set-up and delivery of the new vaccination programme at this centre included embedding QI mechanisms to capture feedback from staff and service users to identify and monitor changes. Daily ‘huddles’ included representatives from all staff groups involved in the delivery of the service and were chaired by an on-site operations manager. Feedback was actively encouraged and discussed at the huddle including agreement on actions and mitigation measures. This was captured within the QI service log. Progress was monitored at weekly QI review meetings on site. QI learning cycles continued throughout the use of the site.
Service user feedback was captured ad hoc when volunteered onsite and through invitations to respond online after using the service. QR codes were provided on site, and the process was later adapted to send out emails and text messages requesting feedback when it was found that the QR option had a low uptake rate.
An equality impact assessment (EIA) framework based on national guidance was adapted from the locally agreed template to ensure systematic inclusion of groups with protected characteristics and those identified by contemporaneous research at the time of development (January 2021).
The EIA was performed on 8 February 2021 using information from a site visit, observations within the patient flow and ad hoc feedback from onsite staff to provide an assessment of the service user journey. Information was obtained to inform the EIA from service user feedback (1,369 responses) from the week prior to the assessment, captured through online questionnaires and collated by patient experience staff. This was supplemented with collated feedback from a visit by local ‘experts by experience’. These sources of collated feedback were read in full; themes were identified regarding access to and access within the VC, and service user experience. At the time of the EIA, the Joint Committee on Vaccination and Immunisation cohorts 1–4 were eligible for vaccination.1
EIA findings were reported to an operations manager within the vaccination programme and escalated to the daily huddle to inform about mitigations to inequitable access through the embedded QI process.
Operations managers proactively strengthened links and relationships with community ambassadors (CAs) to invite and tailor vaccination clinics. CAs were asked to advise on culturally appropriate processes, languages and support through their networks, and to invite community members to attend for vaccination.
EIA documentation, service improvement logs, service user feedback and an in-depth interview with the VC operations manager were used to identify outcomes.
Outcomes
Readily accessible printed or audio–visual communications in a variety of formats and languages were made available at the VC. Resources were collated into a readily accessible folder of pre-printed materials. Where the correct language / best suited format was unclear, options were presented to the service user to choose their preferred option. Staff and volunteers received training to identify and provide additional support.
Establishing open lines of communication through CAs enabled the provision of evidence-based information. Negative information and misinformation through social media and community discussions were identified as reasons for apprehension in attending for vaccination. To mitigate these, questions and comments from phone calls and via social media were answered promptly, and in partnership with the VC staff and CAs using positive, evidence-based information. Transparent communication with communities via CAs provided an important method by which concerns could be addressed to encourage acceptance of the vaccination offer. This resulted in positive feedback and active engagement with the local community.
Engagement with frequently underserved groups enabled the development of a focused social media campaign to communities, including people from ethnic minorities. It also enabled peer support and questions to be answered via trusted community members.
The VC supplemented the national booking system by inviting people at higher risk of not attending and by providing drop-in slots. Specific clinics provided opportunities for CAs to be a bridge between official NHS communications and their communities to encourage attendance at drop-in clinics. This flexibility of approach and openness to co-creation drawing on community assets was positively received by attendees.
Please see Table 1 for a summary of results and Table 2 for details of working examples.
Mitigation measures aligned to the evaluation framework
Case study examples taken from the vaccination centres
Conclusion and next steps
The systematic identification of inequalities and mitigating actions using a standardised methodology was operationally deliverable in the face of heightened service pressure. Mitigations of inequitable uptake of vaccinations evolved throughout the programme through a continuous quality improvement approach. Identifying additional needs and providing support to service users became an element of the services' ethos, with staff and volunteers trained and encouraged to proactively identify service users who would benefit from additional support.
The approach that was used at the VC aimed to reduce barriers to vaccination within a wider system-level programme. CA engagement supported the building of trust and aimed to reduce misinformation to encourage uptake of vaccination.12 Specific toolkits have been made publicly available and examples shared to mitigate inequalities linked to place of residence, and with specific ethnicities, faith communities and health status.13
Capturing service-user and CA feedback within the embedded processes meant that clinics and communication aids could be tailored and adapted. Targeted social media packages, clinics and simple aids helped to support feelings of being welcome and create positive communication.
CA engagement and enthusiasm aided successful vaccination uptake through encouraging acceptance of vaccination in underserved groups. Working with specific communities to co-create vaccination events required flexibility in approach outside of routine invitation and booking systems. Communications from CAs into communities may have acted as a behavioural nudge, however, research is required to establish whether this was a similar mechanism for encouraging engagement with vaccination.14
These findings are from one centre within the county of Dorset in the delivery of a single vaccination programme. The backdrop of the pandemic and a vaccination programme during a time of national lockdown lends itself to challenges with generalisability. However, it does demonstrate the application of tools to mitigate inequalities despite extraordinary service pressures.
Due to the limitations of the data collection methods and access, it was not possible to measure changes in vaccination uptake across centres throughout the process. As part of a national programme, when community centred clinics were held (as described in case study 1; Table 2), services users reported attendance from residences out of the area to take up the offer of the vaccination within their preferred setting (conversation between B Andrews-Jones and a service user, May 2021), making the denominator challenging to accurately identify.
In keeping with literature at the time of writing, this case study demonstrates the need for a multi-component and asset-based approach to service design and engagement inequalities.8 Implementation of mitigation strategies were facilitated by collaboration and support from other areas of the organisation, sufficient time for implementing measures, collaboration with community partners, and the inclusion of EIAs in the programme's operational plans.15
The themes of learning identified for strengthening future approaches to reducing inequalities in vaccination uptake were embedding a systematic process for identifying inequalities and mitigations (EIA), and utilising a continuous QI approach within the organisation to learn and adapt to service user needs. This is supported by proactive engagement with CAs and trusted voices that strengthened and created opportunities to reach underserved groups. Although the setting is specific to the COVID-19 vaccination service, transferrable processes have been utilised that could be applied to other settings aiming to address inequalities.
- © Royal College of Physicians 2022. All rights reserved.
References
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- Department of Health and Social Care
- ↵The Lancet Public Health. COVID-19 - break the cycle of inequality. Lancet Public Health 2021;6:e82. www.thelancet.com/action/showPdf?pii=S2468-2667%2821%2900011-6 [Accessed 29 May 2021].
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- Public Health England
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- The OpenSAFELY Collaborative
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- Scientific Advisory Group for Emergencies.
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- Our Dorset
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- Our Dorset
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- SAGE
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- Prins W
- Office for National Statistics
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- Frost M
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- NHS England
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- Sadare O
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