Son Nghiem1, Disna Sajeewani2, Katrina Henderson3, Clifford Afoakwah2, Joshua Byrnes2, Wendy Moyle4, Paul Scuffham5. 1. Centre for Applied Health Economics, Griffith University, Queensland, Australia. Electronic address: s.nghiem@griffith.edu.au. 2. Centre for Applied Health Economics, Griffith University, Queensland, Australia. 3. Health Library, Griffith University, Queensland, Australia. 4. Menzies Health Institute Queensland, Griffith University, Queensland, Australia; School of Nursing and Midwifery, Griffith University, Queensland, Australia. 5. Centre for Applied Health Economics, Griffith University, Queensland, Australia; Menzies Health Institute Queensland, Griffith University, Queensland, Australia.
Abstract
OBJECTIVES: Frailty is an increasingly common health condition and is seen more often due to the ageing population. This study reviews the evidence on the development and validation of these automated frailty measurement tools. DESIGN: Six databases: PubMed, EMBASE, MEDLINE, CINAHL, Scopus, and Web of Science were electronically searched. Selected studies must have developed and validated a new frailty measurement tool using administrative health data and published results in a peer-reviewed, English-language journal. Selected studies were synthesized narratively. SETTING AND PARTICIPANTS: The review focused on large scale studies using administrative health data in developed countries. Participants included older people aged 65 years and above. MEASURES: The main measures of review studies include discrimination power and the prediction ability of adverse health outcomes; performance against established frailty measures; and validation records. RESULTS: Five studies were selected for narrative synthesis after screening the full-text. All frailty measurement tools in the selected five studies produced strong discrimination power with C-statistics ranging from 0.61-97. Two studies were independently validated in studies by other authors or conducted in other locations; one study developed an early prediction model, and no study has been applied in practice. CONCLUSIONS AND IMPLICATIONS: Automated frailty measurement tools using administrative health data are still in the early development stage with five tools developed since 2016. Selected studies have strong prediction of adverse health outcomes. Future studies should include validation and refinement of these tools in other countries and assessment of their clinical utility and capacity to inform cost-effective policy and practice.
OBJECTIVES: Frailty is an increasingly common health condition and is seen more often due to the ageing population. This study reviews the evidence on the development and validation of these automated frailty measurement tools. DESIGN: Six databases: PubMed, EMBASE, MEDLINE, CINAHL, Scopus, and Web of Science were electronically searched. Selected studies must have developed and validated a new frailty measurement tool using administrative health data and published results in a peer-reviewed, English-language journal. Selected studies were synthesized narratively. SETTING AND PARTICIPANTS: The review focused on large scale studies using administrative health data in developed countries. Participants included older people aged 65 years and above. MEASURES: The main measures of review studies include discrimination power and the prediction ability of adverse health outcomes; performance against established frailty measures; and validation records. RESULTS: Five studies were selected for narrative synthesis after screening the full-text. All frailty measurement tools in the selected five studies produced strong discrimination power with C-statistics ranging from 0.61-97. Two studies were independently validated in studies by other authors or conducted in other locations; one study developed an early prediction model, and no study has been applied in practice. CONCLUSIONS AND IMPLICATIONS: Automated frailty measurement tools using administrative health data are still in the early development stage with five tools developed since 2016. Selected studies have strong prediction of adverse health outcomes. Future studies should include validation and refinement of these tools in other countries and assessment of their clinical utility and capacity to inform cost-effective policy and practice.
Authors: John T Y Soong; Sheryl Hui-Xian Ng; Kyle Xin Quan Tan; Jurgita Kaubryte; Adrian Hopper Journal: BMJ Open Date: 2022-01-31 Impact factor: 2.692
Authors: Thomas Gilbert; Quentin Cordier; Stéphanie Polazzi; Marc Bonnefoy; Eilìs Keeble; Andrew Street; Simon Conroy; Antoine Duclos Journal: Age Ageing Date: 2022-01-06 Impact factor: 10.668