Authors' objectives: Our aim was to develop and evaluate the electronic frailty index+, a prognostic tool, including four integrated prognostic-decision models, to stratify older people into subgroups for targeting key interventions. Members of our team led the eFI development, validation and national implementation. This has been translated into major NHS policy change through inclusion in the 2017–8 general practice (GP) contract, which supports frailty stratification using the eFI, and NHS Long Term Plan.

Authors' results and conclusions: We used data from 660,417 patients in SAIL, 88,947 in Connected Bradford and 252 CARE75+ participants. New home care package Model performance was promising in internal–external cross-validation, with average calibration slope 1.00 (95% confidence interval 0.99 to 1.01), average calibration-in-the-large −0.01 (95% confidence interval −0.02 to 0.01), average observed/expected ratio 0.99 (95% confidence interval 0.98 to 1.01) and average C-statistic 0.81 (95% confidence interval 0.81 to 0.81). We used data from 660,417 patients in SAIL, 88,947 in Connected Bradford and 252 CARE 75+ participants. New home care package The final model included 80 predictors. Model performance was promising when examined across the entire data set using internal–external cross-validation, with average calibration slope 1.00 [95% confidence interval (CI), 0.99 to 1.01], average calibration-in-the-large (CITL) −0.01 (95% CI −0.02 to 0.01), average observed/expected (O/E) ratio 0.99 (95% CI 0.98 to 1.01) and average C-statistic 0.81 (95% CI 0.81 to 0.81). The actual risk of needing a new care home package was low across the entire data set.

Authors' methods: Design Prognostic model development, internal validation and external validation using large data sets and longitudinal cohort study data, with decision curve and health economic analysis. We were unable to complete external validation of the home care prediction model. Design Prognostic model development, internal validation and external validation (EV) using large data sets [Secure Anonymised Information Linkage (SAIL) databank, Connected Bradford data set] and Community Ageing Research 75+ (CARE 75+) longitudinal cohort study data, with linked decision modelling and health economic analysis.

Project Status: Completed

URL for project: https://www.journalslibrary.nihr.ac.uk/programmes/hta/NIHR127905

Year Published: 2026

URL for published report: https://www.journalslibrary.nihr.ac.uk/hta/GJAC1008

URL for additional information: English

English language abstract: An English language summary is available

Publication Type: Full HTA

Country: England, United Kingdom

DOI: 10.3310/GJAC1008

Organisation Name: NIHR Health Technology Assessment programme

Contact Address: NIHR Journals Library, National Institute for Health and Care Research, Evaluation, Trials and Studies Coordinating Centre, Alpha House, University of Southampton Science Park, Southampton SO16 7NS, UK

Contact Name: journals.library@nihr.ac.uk

Contact Email: journals.library@nihr.ac.uk