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A Regional Collaboration of Health (ARCH): Using health survey and linked routine data to understand wellbeing. / Fatemeh, Torabi
International Journal of Population Data Science, Volume: 3, Issue: 2
Swansea University Author: Fatemeh, Torabi
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BackgroundMonitoring social wellbeing and its relationship to health service utilisation by means of appropriate measurement tools can provide a complementary view towards service development. Welsh Health Survey (WHS) collects aspects of wellbeing while routine health data captures details around h...
|Published in:||International Journal of Population Data Science|
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BackgroundMonitoring social wellbeing and its relationship to health service utilisation by means of appropriate measurement tools can provide a complementary view towards service development. Welsh Health Survey (WHS) collects aspects of wellbeing while routine health data captures details around health service utilisation.ObjectiveThe aim of this project was to evaluate the linkage ability of routine health data with survey data and establish a methodology for utilizing survey data as a measure for self-reported health outcomes.MethodWe used WHS data from UK data archive to link self-reported wellbeing to health outcomes, a measure for personal wellbeing was developed using the personal wellbeing questions defined by Office of National Statistics (ONS), included in national surveys from 2011 onward. WHS was then linked to routine health data using SAIL Databank. We conducted regression analysis to identify potential predictors of personal wellbeing by linking primary care, hospital and emergency department datasets, to develop and provide insight into the relationship between wellbeing, multi-morbidity and health service utilisation.FindingsWellbeing questions had similar scoring patterns across age groups which is different to most health indicators that tend to show a marked health decline with increasing age. Our findings showed that self-reported of ‘excellent’ or ‘very good’general health has the largest positive effect on wellbeing while positive viewpoint on self-health has the second largest effect.ConclusionsCombining and harmonising data from multiple sources and linking them to information from a longitudinal cohort create useful resources for population health research. These methods are reproducible and can be utilised by other researchersand projects.
Swansea University Medical School