Can Linked Electronic Medical Record and Administrative Data Help Us Identify Those Living with Frailty? - Wong, Sabrina; Katz, Alan; Williamson, Tyler; Singer, Alexander; Peterson, Sandra; Taylor, Carole; Price, Morgan; McCracken, Rita; Thandi, Manpreet (International Journal of Population Data Science, 2020)
Introduction Frailty is a complex condition that affects many aspects of a patients’ wellbeing and health outcomes. Objectives We used available Electronic Medical Record (EMR) and administrative data to determine definitionsof frailty. We also examined whether there were differences in demographics or health conditionsamong those identified as frail in either the EMR or administrative data. Methods EMR and administrative data were linked in British Columbia (BC) and Manitoba (MB) to identifythose aged 65 years and older who were frail. The EMR data were obtained from the CanadianPrimary Care Sentinel Surveillance Network (CPCSSN) and the administrative data (e.g. billing,hospitalizations) was obtained from Population Data BC and the Manitoba Population ResearchData Repository. Sociodemographic characteristics, risk factors, prescribed medications, use andcosts of healthcare are described for those identified as frail. Results Sociodemographic and utilization differences were found among those identified as frail from theEMR compared to those in the administrative data. Among those who were >65 years, who hada record in both EMR and administrative data, 5%-8% (n=191 of 3,553, BC; n=2,396 of 29,382,MB) were identified as frail. There was a higher likelihood of being frail with increasing age andbeing a woman. In BC and MB, those identified as frail in both data sources have approximatelytwice the number of contacts with primary care (n=20 vs. n=10) and more days in hospital (n=7.2vs. n=1.9 in BC; n=9.8 vs. n=2.8 in MB) compared to those who are not frail; 27% (BC) and 14%(MB) of those identified as frail in 2014 died in 2015. Conclusions Identifying frailty using EMR data is particularly challenging because many functional deficits arenot routinely recorded in structured data fields. Our results suggest frailty can be captured along acontinuum using both EMR and administrative data.