Please use this identifier to cite or link to this item: https://doi.org/10.1136/bmjopen-2018-026759
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dc.titleDr Foster global frailty score: an international retrospective observational study developing and validating a risk prediction model for hospitalised older persons from administrative data sets
dc.contributor.authorSoong, John TY
dc.contributor.authorKaubryte, Jurgita
dc.contributor.authorLiew, Danny
dc.contributor.authorPeden, Carol Jane
dc.contributor.authorBottle, Alex
dc.contributor.authorBell, Derek
dc.contributor.authorCooper, Carolyn
dc.contributor.authorHopper, Adrian
dc.date.accessioned2019-10-30T00:41:13Z
dc.date.available2019-10-30T00:41:13Z
dc.date.issued2019-06
dc.identifier.citationSoong, John TY, Kaubryte, Jurgita, Liew, Danny, Peden, Carol Jane, Bottle, Alex, Bell, Derek, Cooper, Carolyn, Hopper, Adrian (2019-06). 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. BMJ Open 9 (6) : e026759-e026759. ScholarBank@NUS Repository. https://doi.org/10.1136/bmjopen-2018-026759
dc.identifier.issn20446055
dc.identifier.issn20446055
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/160886
dc.description.abstract<jats:sec><jats:title>Objectives</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Design</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Setting</jats:title><jats:p>34 hospitals from nine countries across Europe, Australia, the UK and USA.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>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 utilised for case-mix adjustment for older persons internationally.</jats:p></jats:sec>
dc.publisherBMJ
dc.sourceElements
dc.typeArticle
dc.date.updated2019-10-29T18:31:23Z
dc.contributor.departmentMEDICINE
dc.description.doi10.1136/bmjopen-2018-026759
dc.description.sourcetitleBMJ Open
dc.description.volume9
dc.description.issue6
dc.description.pagee026759-e026759
dc.published.statePublished
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