A Regional Collaboration of Health (ARCH): Using health survey and linked routine data to understand wellbeing.

• Main Authors: Fatemeh Torabi, Ashley Akbari, Jane Lyons, Mathilde Castagnet, Ronan Lyons
• Format: Article
• Language: English
• Published: Swansea University 2018-06-01
• Series: International Journal of Population Data Science
• Online Access: https://ijpds.org/article/view/496

Background Monitoring 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. Objective The 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. Method We 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. Findings Wellbeing 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. Conclusions Combining 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 researchers and projects.