Measuring the prevalence of 60 health conditions in older Australians in residential aged care with electronic health re
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RESEARCH
Open Access
Measuring the prevalence of 60 health conditions in older Australians in residential aged care with electronic health records: a retrospective dynamic cohort study Kimberly E. Lind1,2* , Magdalena Z. Raban2, Lindsey Brett3, Mikaela L. Jorgensen2, Andrew Georgiou2 and Johanna I. Westbrook2
Abstract Background: The number of older Australians using aged care services is increasing, yet there is an absence of reliable data on their health. Multimorbidity in this population has not been well described. A clear picture of the health status of people using aged care is essential for informing health practice and policy to support evidence-based, equitable, highquality care. Our objective was to describe the health status of older Australians living in residential aged care facilities (RACFs) and develop a model for monitoring health conditions using data from electronic health record systems. Methods: Using a dynamic retrospective cohort of 9436 RACF residents living in 68 RACFs in New South Wales and the Australian Capital Territory from 2014 to 2017, we developed an algorithm to identify residents’ conditions using aged care funding assessments, medications administered, and clinical notes from their facility electronic health record (EHR). We generated age- and sex-specific prevalence estimates for 60 health conditions. Agreement between conditions recorded in aged care funding assessments and those documented in residents’ EHRs was evaluated using Cohen’s kappa. Cluster analysis was used to describe combinations of health conditions (multimorbidity) occurring among residents. Results: Using all data sources, 93% of residents had some form of circulatory disease, with hypertension the most common (62%). Most residents (93%) had a mental or behavioural disorder, including dementia (58%) or depression (54%). For most conditions, EHR data identified approximately twice the number of people with the condition compared to aged care funding assessments. Agreement between data sources was highest for multiple sclerosis, Huntington’s disease, and dementia. The cluster analysis identified seven groups with distinct combinations of health conditions and demographic characteristics and found that the most complex cluster represented a group of residents that had on average the longest lengths of stay in residential care. (Continued on next page)
* Correspondence: [email protected] 1 Department of Health Promotion Sciences, Mel & Enid Zuckerman College of Public Health, University of Arizona, 3950 S. Country Club Rd., Suite 330, Tucson, AZ 85714, USA 2 Centre for Health Systems and Safety Research, Australian Institute of Health Innovation, Macquarie University, Level 6, 75 Talavera Road, Sydney, NSW 2109, Australia Full list of author information is available at the end of the article © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as lo
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