A mixed-methods process evaluation of an integrated care system's population health management system to reduce health inequalities in COVID-19 vaccination uptake
Georgia Watson, Cassie Moore, Fiona Aspinal, Andrew Hutchings, R. Raine, Jessica Sheringham
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引用次数: 0
Abstract
PurposeMany countries have a renewed focus on health inequalities since COVID-19. In England, integrated care systems (ICSs), formed in 2022 to promote integration, are required to reduce health inequalities. Integration is supported by population health management (PHM) which links data across health and care organisations to inform service delivery. It is not well-understood how PHM can help ICSs reduce health inequalities. This paper describes development of a programme theory to advance this understanding.Design/methodology/approachThis study was conducted as a mixed-methods process evaluation in a local ICS using PHM. The study used Framework to analyse interviews with health and care professionals about a PHM tool, the COVID-19 vaccination uptake Dashboard. Quantitative data on staff Dashboard usage were analysed descriptively. To develop a wider programme theory, local findings were discussed with national PHM stakeholders.FindingsICS staff used PHM in heterogeneous ways to influence programme delivery and reduce inequalities in vaccine uptake. PHM data was most influential where it highlighted action was needed for “targetable” populations. PHM is more likely to influence decisions on reducing inequalities where data are trusted and valued, data platforms are underpinned by positive inter-organisational relationships and where the health inequality is a shared priority.Originality/valueThe COVID-19 pandemic accelerated a shift toward use of digital health platforms and integrated working across ICSs. This paper used an evaluation of integrated data to reduce inequalities in COVID-19 vaccine delivery to propose a novel programme theory for how integrated data can support ICS staff to tackle health inequalities.