Introduction: Analyses of large sets of electronic health-related data (Big Data), including local community indicators, may improve knowledge of the outcomes of chronic diseases among patients and healthcare systems. Our study will estimate the prevalence of chronic obstructive pulmonary disease (COPD) and its exacerbations in elderly patients in the Lodz region, Poland; it will also evaluate local community factors potentially associated with disease exacerbations and rank local communities according to health and local community indicators.
Methods: and analysis : Local community factors, including medical/health, socioeconomic and environmental values potentially associated with COPD exacerbations will be identified. A retrospective analysis of a cohort of about half a million people 65 years old and older, living in local communities of the Lodz region in 2016 will be performed. Relevant data will be extracted from databases, including those of the National Health Fund, Tax Office and National Statistics Centre. This cross-sectional study will include data for a 1 year period, from 1 January until 31 December 2016. The data will first be checked for quality, cleaned and analysed using data mining techniques, and then multilevel logistic regression will be used to discover the community determinants of COPD exacerbations.
Ethics and dissemination: The study protocol has been approved by the Bioethical Committee of Medical University of Lodz (RNN/248/18/KE, 10 July 2018). Our findings will be published in peer-reviewed journals and reports.
Keywords: COPD; COPD prevalence; elderly; exacerbations; local community; medical big data.
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