Development and validation of an electronic frailty index using routine primary care electronic health record data

Ronan Ryan, Tom Marshall

Research output: Contribution to journalArticlepeer-review

376 Citations (Scopus)


Frailty is an especially problematic expression of population ageing. International guidelines recommend routine identification of frailty to provide evidence-based treatment but currently available tools require additional resource.

To develop and validate an electronic frailty index (eFI) using routinely available primary care electronic health record data.

Study design and setting
Retrospective cohort study. Development and internal validation cohorts were established using a randomly split sample of the ResearchOne primary care database. External validation cohort established using THIN database.

Patients aged 65 to 95, registered with a ResearchOne or THIN practice on 14/10/2008.

We constructed the eFI using the cumulative deficit frailty model as our theoretical framework. The eFI score is calculated by the presence or absence of individual deficits as a proportion of the total possible. Categories of fit, mild, moderate and severe frailty were defined using population quartiles.

Outcomes were one, three and five year mortality, hospitalisation and nursing home admission.

Statistical analysis
Hazard ratios (HRs) were estimated using bivariate and multivariate Cox regression analyses. Discrimination was assessed using receiver operating characteristic (ROC) curves. Calibration was assessed using pseudoR2 estimates.

We include data from a total of 931,541 patients. The eFI incorporates 36 deficits constructed using 2,171 CTV3 codes. One year adjusted HR for mortality was 1.92 (95% CI 1.81 to 2.04) for mild frailty, 3.10 (95% CI 2.91 to 3.31) for moderate frailty and 4.52 (95% CI 4.16 to 4.91) for severe frailty. Corresponding estimates for hospitalisation were 1.93 (95% CI 1.86 to 2.01), 3.04 (95% CI 2.90 to 3.19) and 4.73 (95% CI 4.43 to 5.06), and for nursing home admission were 1.89 (95% CI 1.63 to 2.15), 3.19 (95% CI 2.73 to 3.73) and 4.76 (95% CI 2.73 to 3.73), with good to moderate discrimination but low calibration estimates.

The eFI uses routine data to identify older people with mild, moderate and severe frailty, with robust predictive validity for outcomes of mortality, hospitalisation and care home admission. Routine implementation of the eFI could enable delivery of evidence-based interventions to improve outcomes for this vulnerable group.
Original languageEnglish
JournalAge and Ageing
Early online date3 Mar 2016
Publication statusE-pub ahead of print - 3 Mar 2016


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