Measuring the prevalence of 60 health conditions in older Australians in residential aged care with electronic health records: a retrospective dynamic cohort study

Population Health Metrics

Johanna I. Westbrook¹  Andrew Georgiou¹  Mikaela L. Jorgensen¹  Magdalena Z. Raban¹  Lindsey Brett²  Kimberly E. Lind³ 

[1] Centre for Health Systems and Safety Research, Australian Institute of Health Innovation, Macquarie University, Level 6, 75 Talavera Road, 2109, Sydney, NSW, Australia;Department of Health Professions, Faculty of Medicine and Health Sciences, Macquarie University, Ground Floor, 75 Talavera Road, 2109, Sydney, NSW, Australia;Department of Health Promotion Sciences, Mel & Enid Zuckerman College of Public Health, University of Arizona, 3950 S. Country Club Rd., Suite 330, 85714, Tucson, AZ, USA;Centre for Health Systems and Safety Research, Australian Institute of Health Innovation, Macquarie University, Level 6, 75 Talavera Road, 2109, Sydney, NSW, Australia;

关键词: Health status;    Multimorbidity;    Multiple chronic conditions;    Aged care;    Long-term care;    Nursing homes;    Electronic health record;   

DOI  :  10.1186/s12963-020-00234-z

来源: Springer

【 摘 要 】

BackgroundThe 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, high-quality 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.MethodsUsing 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.ResultsUsing 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.ConclusionsThe prevalence of many health conditions among RACF residents in Australia is underestimated in previous reports. Aged care EHR data have the potential to be used to better understand the complex health needs of this vulnerable population and can help fill the information gaps needed for population health surveillance and quality monitoring.

【 授权许可】

CC BY