A cross-sectional study examining convergent validity of a frailty index based on electronic medical records in a Canadian primary care program.

Authors:
Marjan Abbasi
Marjan Abbasi
University of Alberta
Sheny Khera
Sheny Khera
University of Alberta
Julia Dabravolskaj
Julia Dabravolskaj
Edmonton Oliver Primary Care Network
Ben Vandermeer
Ben Vandermeer
University of Alberta
Canada
Olga Theou
Olga Theou
Dalhousie University
Darryl Rolfson
Darryl Rolfson
University of Alberta
Canada
Andrew Clegg
Andrew Clegg
University of Southampton
United Kingdom

BMC Geriatr 2019 Apr 16;19(1):109. Epub 2019 Apr 16.

NIHR CLAHRC Older People's Theme Academic Unit of Elderly Care and Rehabilitation, University of Leeds, Bradford Institute for Health Research, Temple Bank House, Bradford Royal Infirmary, Duckworth Lane, Bradford, BD9 6RJ, UK.

Background: 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. 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.

Methods: A 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.

Results: Results 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.

Conclusions: The 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.

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Source
https://bmcgeriatr.biomedcentral.com/articles/10.1186/s12877
Publisher Site
http://dx.doi.org/10.1186/s12877-019-1119-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6469123PMC
April 2019
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