Development and validation of a hospital frailty risk score focusing on older people in acute care settings using electronic hospital records: an observational study
Development and validation of a hospital frailty risk score focusing on older people in acute care settings using electronic hospital records: an observational study
Background: older people are increasing users of healthcare globally; the aim of this study was to determine if older people with characteristics of frailty and at risk of adverse healthcare outcomes could be identified using routinely collected data.
Methods: a three-step approach was used to develop and validate a Hospital Frailty Risk Score from ICD-10 diagnostic codes. First, we carried out a cluster analysis to identify a group of hospitalised older people (75 years+) with high resource use and diagnoses associated with frailty. Second, we created a Hospital Frailty Risk Score based on ICD-10 codes that characterised this group. Third, in separate cohorts, we tested how well the score predicted adverse outcomes, and whether it identified similar groups as other frailty tools.
Findings: in the development cohort (n = 22,139), older people with frailty diagnoses formed a distinct group, and had higher non-elective hospital use. In a national validation cohort (n = 1,013,590), compared to patients with the lowest 40%, patients with the highest 20% of Hospital Frailty Risk Scores had increased odds of 30-day mortality (odds ratio 1·71, 95% confidence interval 1·68 to 1·75), long length of stay (OR 6·03, 95% CI 5·92 to 6·10) and 30-day readmission (OR 1·48, 95% CI 1·46 to 1·50). Model discrimination (c-statistic) between individuals for these three outcomes was 0·60, 0·68 and 0·56, respectively. The Hospital Frailty Risk Score exhibited fair or moderate overlap in the identification of frailty with the Fried or Rockwood frailty scales respectively.
Interpretation: the Hospital Frailty Risk Score provides hospitals and health systems with a low cost, systematic way to screen for frailty, identifying a group of hospitalised patients at greater risk of adverse outcomes for whom a frailty-attuned approach might be useful.
Funding: National Institute for Health Research.
1775-1782
Gilbert, Thomas P.
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Neuburger, Jenny
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Kraindler, Joshua
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Keeble, Eilis
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Smith, Paul
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Ariti, Cono
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Arora, Sandeepa
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Street, Andrew
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Parker, Stuart
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Roberts, Helen
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Bardsley, Martin
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Conroy, Simon
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5 May 2018
Gilbert, Thomas P.
a48f98e3-6a47-4b46-9054-610e54657d5f
Neuburger, Jenny
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Kraindler, Joshua
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Keeble, Eilis
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Smith, Paul
5971135c-98d0-47e0-9f40-94085befbd20
Ariti, Cono
713b0365-65a5-4062-94a0-b02f453bc26c
Arora, Sandeepa
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Street, Andrew
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Parker, Stuart
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Roberts, Helen
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Bardsley, Martin
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Conroy, Simon
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Gilbert, Thomas P., Neuburger, Jenny, Kraindler, Joshua, Keeble, Eilis, Smith, Paul, Ariti, Cono, Arora, Sandeepa, Street, Andrew, Parker, Stuart, Roberts, Helen, Bardsley, Martin and Conroy, Simon
(2018)
Development and validation of a hospital frailty risk score focusing on older people in acute care settings using electronic hospital records: an observational study.
The Lancet, 391 (10132), , [D-17-07092R2].
(doi:10.1016/S0140-6736(18)30668-8).
Abstract
Background: older people are increasing users of healthcare globally; the aim of this study was to determine if older people with characteristics of frailty and at risk of adverse healthcare outcomes could be identified using routinely collected data.
Methods: a three-step approach was used to develop and validate a Hospital Frailty Risk Score from ICD-10 diagnostic codes. First, we carried out a cluster analysis to identify a group of hospitalised older people (75 years+) with high resource use and diagnoses associated with frailty. Second, we created a Hospital Frailty Risk Score based on ICD-10 codes that characterised this group. Third, in separate cohorts, we tested how well the score predicted adverse outcomes, and whether it identified similar groups as other frailty tools.
Findings: in the development cohort (n = 22,139), older people with frailty diagnoses formed a distinct group, and had higher non-elective hospital use. In a national validation cohort (n = 1,013,590), compared to patients with the lowest 40%, patients with the highest 20% of Hospital Frailty Risk Scores had increased odds of 30-day mortality (odds ratio 1·71, 95% confidence interval 1·68 to 1·75), long length of stay (OR 6·03, 95% CI 5·92 to 6·10) and 30-day readmission (OR 1·48, 95% CI 1·46 to 1·50). Model discrimination (c-statistic) between individuals for these three outcomes was 0·60, 0·68 and 0·56, respectively. The Hospital Frailty Risk Score exhibited fair or moderate overlap in the identification of frailty with the Fried or Rockwood frailty scales respectively.
Interpretation: the Hospital Frailty Risk Score provides hospitals and health systems with a low cost, systematic way to screen for frailty, identifying a group of hospitalised patients at greater risk of adverse outcomes for whom a frailty-attuned approach might be useful.
Funding: National Institute for Health Research.
Text
preprint Lancet accepted
- Accepted Manuscript
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PIIS0140673618306688
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More information
Accepted/In Press date: 8 March 2018
e-pub ahead of print date: 26 April 2018
Published date: 5 May 2018
Additional Information:
invited commentary by Prof Rockwood on the article was also published at the same time
Identifiers
Local EPrints ID: 418829
URI: http://eprints.soton.ac.uk/id/eprint/418829
ISSN: 0140-6736
PURE UUID: 7ca1a577-8c55-4914-a03f-70b65c5acdf2
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Date deposited: 23 Mar 2018 17:30
Last modified: 16 Aug 2024 04:02
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Contributors
Author:
Thomas P. Gilbert
Author:
Jenny Neuburger
Author:
Joshua Kraindler
Author:
Eilis Keeble
Author:
Paul Smith
Author:
Cono Ariti
Author:
Sandeepa Arora
Author:
Andrew Street
Author:
Stuart Parker
Author:
Martin Bardsley
Author:
Simon Conroy
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