Validation of an automatically generated screening score for frailty: the care assessment need (CAN) score.

Background: Frailty is a state of vulnerability to stressors that is prevalent in older adults and is associated with higher morbidity, mortality and healthcare utilization. Multiple instruments are used to measure frailty; most are time-consuming. The Care Assessment Need (CAN) score is automatically generated from electronic health record data using a statistical model. The methodology for calculation of the CAN score is consistent with the deficit accumulation model of frailty. At a 95 percentile, the CAN score is a predictor of hospitalization and mortality in Veteran populations. The purpose of this study was to validate the CAN score as a screening tool for frailty in primary care.

Methods: This is a cross-sectional, validation study compared the CAN score with a 40-item Frailty Index reference standard based on a comprehensive geriatric assessment. We included community-dwelling male patients over age 65 from an outpatient geriatric medicine clinic. We calculated the sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy of the CAN score.

Results: 184 patients over age 65 were included in the study: 97.3% male, 64.2% White, 80.9% non-Hispanic. The CGA-based Frailty Index defined 14.1% as robust, 53.3% as prefrail and 32.6% as frail. For the frail, statistical analysis demonstrated that a CAN score of 55 provides sensitivity, specificity, PPV and NPV of 91.67, 40.32, 42.64 and 90.91% respectively whereas at a score of 95 the sensitivity, specificity, PPV and NPV were 43.33, 88.81, 63.41, 77.78% respectively. Area under the receiver operating characteristics curve was 0.736 (95% CI = .661-.811).

Conclusion: CAN score is a potential screening tool for frailty among older adults; it is generated automatically and provides acceptable diagnostic accuracy. Hence, the CAN score may be a useful tool to primary care providers for detection of frailty in their patient panels.