A Protocol for a Mixed-Methods Process Evaluation of a Local Population Health Management System to Reduce Inequities in COVID-19 Vaccination Uptake

Georgia Watson, Cassie Moore, Fiona Aspinal, Claudette Boa, Vusi Edeki, Andrew Hutchings, Rosalind Raine and Jessica Sheringham
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Georgia Watson: London Boroughs of Camden & Islington, London N1 1XR, UK
Cassie Moore: London Boroughs of Camden & Islington, London N1 1XR, UK
Fiona Aspinal: Department of Applied Health Research, University College London, London WC1E 7HB, UK
Claudette Boa: Public Health England, London SE1 8UG, UK
Vusi Edeki: Public Health England, London SE1 8UG, UK
Andrew Hutchings: London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
Rosalind Raine: Department of Applied Health Research, University College London, London WC1E 7HB, UK
Jessica Sheringham: Department of Applied Health Research, University College London, London WC1E 7HB, UK

IJERPH, 2022, vol. 19, issue 8, 1-9

Abstract: Population health management is an emerging technique to link and analyse patient data across several organisations in order to identify population needs and plan care. It is increasingly used in England and has become more important as health policy has sought to drive greater integration across health and care organisations. This protocol describes a mixed-methods process evaluation of an innovative population health management system in North Central London, England, serving a population of 1.5 million. It focuses on how staff have used a specific tool within North Central London’s population health management system designed to reduce inequities in COVID-19 vaccination. The COVID-19 vaccination Dashboard was first deployed from December 2020 and enables staff in North London to view variations in the uptake of COVID-19 vaccinations by population characteristics in near real-time. The evaluation will combine interviews with clinical and non-clinical staff with staff usage analytics, including the volume and frequency of staff Dashboard views, to describe the tool’s reach and identify possible mechanisms of impact. While seeking to provide timely insights to optimise the design of population health management tools in North Central London, it also seeks to provide longer term transferable learning on methods to evaluate population health management systems.

Keywords: population health management; data linkage; population health; inequalities; inequities; process evaluation; protocol (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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