Evaluating frailty scores to predict mortality in older adults using data from population based electronic health records: case control study

Background: recognising that a patient is nearing the end of life is essential, to enable professional carers to discuss prognosis and preferences for end of life care.

Objective: investigate whether an electronic frailty index (eFI) generated from routinely collected data, can be used to predict mortality at an individual level.

Design: historical prospective case control study.

Setting: UK primary care electronic health records.

Subjects: 13,149 individuals age 75 and over who died between 01/01/2015 and 01/01/2016, 1:1 matched by age and sex to individuals with no record of death in the same time period.

Methods: two subsamples were randomly selected to enable development and validation of the association between eFI 3 months prior to death and mortality. Receiver operator characteristic (ROC) analyses were used to examine diagnostic accuracy of eFI at 3 months prior to death.

Results: an eFI > 0.19 predicted mortality in the development sample at 75% sensitivity and 69% area under received operating curve (AUC). In the validation dataset this cut point gave 76% sensitivity, 53% specificity.

Conclusions: the eFI measured at a single time point has low predictive value for individual risk of death, even 3 months prior to death. Although the eFI is a strong predictor or mortality at a population level, its use for individuals is far less clear.