Imperial College London
Alternate

Emeritus ProfessorDerekBell

Faculty of Medicine, School of Public Health

Emeritus Professor in Acute Medicine
 
 
 
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Contact

 

+44 (0)7886 725 212d.bell

 
 
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Assistant

 

Miss Heather Barnes +44 (0)20 3315 8144

 
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Location

 

Chelsea and Westminster HospitalChelsea and Westminster Campus

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Summary

 

Publications

Citation

BibTex format

@article{Soong:2019:10.1136/bmjopen-2018-026759,
author = {Soong, JTY and Kaubryte, J and Liew, D and Peden, CJ and Bottle, A and Bell, D and Cooper, C and Hopper, A},
doi = {10.1136/bmjopen-2018-026759},
journal = {BMJ Open},
title = {Dr Foster global frailty score: an international retrospective observational study developing and validating a risk prediction model for hospitalised older persons from administrative data sets},
url = {http://dx.doi.org/10.1136/bmjopen-2018-026759},
volume = {9},
year = {2019}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - OBJECTIVES: This study aimed to examine the prevalence of frailty coding within the Dr Foster Global Comparators (GC) international database. We then aimed to develop and validate a risk prediction model, based on frailty syndromes, for key outcomes using the GC data set. DESIGN: A retrospective cohort analysis of data from patients over 75 years of age from the GC international administrative data. A risk prediction model was developed from the initial analysis based on seven frailty syndrome groups and their relationship to outcome metrics. A weighting was then created for each syndrome group and summated to create the Dr Foster Global Frailty Score. Performance of the score for predictive capacity was compared with an established prognostic comorbidity model (Elixhauser) and tested on another administrative database Hospital Episode Statistics (2011-2015), for external validation. SETTING: 34 hospitals from nine countries across Europe, Australia, the UK and USA. RESULTS: Of 6.7 million patient records in the GC database, 1.4 million (20%) were from patients aged 75 years or more. There was marked variation in coding of frailty syndromes between countries and hospitals. Frailty syndromes were coded in 2% to 24% of patient spells. Falls and fractures was the most common syndrome coded (24%). The Dr Foster Global Frailty Score was significantly associated with in-hospital mortality, 30-day non-elective readmission and long length of hospital stay. The score had significant predictive capacity beyond that of other known predictors of poor outcome in older persons, such as comorbidity and chronological age. The score's predictive capacity was higher in the elective group compared with non-elective, and may reflect improved performance in lower acuity states. CONCLUSIONS: Frailty syndromes can be coded in international secondary care administrative data sets. The Dr Foster Global Frailty Score significantly predicts key outcomes. This methodology may be feasibly utili
AU  - Soong,JTY
AU  - Kaubryte,J
AU  - Liew,D
AU  - Peden,CJ
AU  - Bottle,A
AU  - Bell,D
AU  - Cooper,C
AU  - Hopper,A
DO  - 10.1136/bmjopen-2018-026759
PY  - 2019///
SN  - 2044-6055
TI  - Dr Foster global frailty score: an international retrospective observational study developing and validating a risk prediction model for hospitalised older persons from administrative data sets
T2  - BMJ Open
UR  - http://dx.doi.org/10.1136/bmjopen-2018-026759
UR  - https://www.ncbi.nlm.nih.gov/pubmed/31230009
UR  - http://hdl.handle.net/10044/1/78507
VL  - 9
ER  -
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