Developing and validating a primary care EMR-based frailty definition using machine learning (original) (raw)
International Journal of Population Data Science
Introduction. Individuals who have been identified as frail have an increased state of vulnerability, often leading to adverse health events, increased health spending, and potentially detrimental outcomes. Objective. The objective of this work is to develop and validate a case definition for frailty that can be used in a primary care electronic medical record database. Methods. This is a cross-sectional validation study using data from the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) in Southern Alberta. 52 CPCSSN sentinels assessed a random sample of their own patients using the Rockwood Clinical Frailty scale, resulting in a total of 875 patients to be used as reference standard. Patients must be over the age of 65 and have had a clinic visit within the last 24 months. The case definition for frailty was developed using machine learning methods using CPCSSN records for the 875 patients. Results. Of the 875 patients, 155 (17.7%) were frail and 720 (84.2%) were not ...
Loading Preview
Sorry, preview is currently unavailable. You can download the paper by clicking the button above.