Abstract
BackgroundAn electronic frailty index (eFI) has been developed and validated in the UK; it uses data from primary care electronic medical records (EMR) for effective frailty case-finding in primary care. This project examined the convergent validity of the eFI from Canadian primary care EMR data with a validated frailty index based on comprehensive geriatric assessment (FI-CGA), in order to understand its potential use in the Canadian context.MethodsA cross-sectional validation study, using data from an integrated primary care research program for seniors living with frailty in Edmonton, AB. Eighty-five patients 65 years of age and older from six primary care physicians’ practices were recruited. Patients were excluded if they were under 65 years of age, did not provide consent to participate in the program, or were living in a long term care facility at the time of enrolment. We used scatter plots to assess linearity and Pearson correlation coefficients to examine correlations.ResultsResults indicate a strong statistically significant correlation between the eFI and FI-CGA (r = 0.72, 95% CI 0.60–0.81, p < 0.001). A simple linear regression showed good ability of the eFI scores to predict FI-CGA scores (F (1,83) = 89.06, p < .0001, R2 = 0.51). Both indices were also correlated with age, number of chronic conditions and number of medications.ConclusionsThe study findings support the convergent validity of the eFI, which further justifies implementation of a case-finding tool that uses routinely collected primary care data in the Canadian context.
Highlights
An electronic frailty index has been developed and validated in the United Kingdom (UK); it uses data from primary care electronic medical records (EMR) for effective frailty case-finding in primary care
A recent breakthrough in the United Kingdom (UK) has been the development, validation and national implementation of an electronic frailty index for frailty case-finding in primary care using data from electronic medical records [9]
A pilot study in primary care in England demonstrated that the electronic frailty index (eFI) was simple and quick to use, acceptable to practice staff, and was able to discriminate older patients referred for comprehensive geriatric assessment (CGA) from the total practice population [16]
Summary
An electronic frailty index (eFI) has been developed and validated in the UK; it uses data from primary care electronic medical records (EMR) for effective frailty case-finding in primary care. The eFI is based on the Abbasi et al BMC Geriatrics (2019) 19:109 deficit accumulation approach to frailty This approach, developed first by Rockwood, Mitnitski and colleagues [10], identifies frailty based on a range of variables (e.g., signs, symptoms, diseases, disabilities, impairments, abnormal test values) collectively referred to as health deficits [11]. According to this model, frailty can be measured by calculating a frailty index (FI) that can be generated from any appropriately populated healthcare database [12,13,14] provided that there are a sufficient number of health deficits that satisfy certain criteria [13, 15]. A pilot study in primary care in England demonstrated that the eFI was simple and quick to use (i.e. it is fully automated and scores are available at point of care), acceptable to practice staff, and was able to discriminate older patients referred for comprehensive geriatric assessment (CGA) from the total practice population [16]
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