Predictors of Frequent Readmissions in Patients With Heart Failure

Wang, N; Gallagher, R; Sze, D; Hales, S; Tofler, G

Predictors of Frequent Readmissions in Patients With Heart Failure

Wang, N Gallagher, R

Sze, D Hales, S Tofler, G

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Publication Type:: Journal Article
Citation:: Heart Lung and Circulation, 2019, 28 (2), pp. 277 - 283
Issue Date:: 2019-02-01

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Field	Value	Language
dc.contributor.author	Wang, N	en_US
dc.contributor.author	Gallagher, R https://orcid.org/0000-0001-5588-9351	en_US
dc.contributor.author	Sze, D	en_US
dc.contributor.author	Hales, S	en_US
dc.contributor.author	Tofler, G	en_US
dc.date.available	2017-10-31	en_US
dc.date.issued	2019-02-01	en_US
dc.identifier.citation	Heart Lung and Circulation, 2019, 28 (2), pp. 277 - 283	en_US
dc.identifier.issn	1443-9506	en_US
dc.identifier.uri	http://hdl.handle.net/10453/129587
dc.description.abstract	© 2017 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ) Background: Patients with heart failure (HF) have a high incidence of hospital readmissions. However risk models that explore predictors of a single readmission may be less useful at identifying the patients with frequent readmissions who contribute to a disproportionately large proportion of morbidity and health care costs. Methods: A total of 6252 patients enrolled in the Management of Cardiac Failure Program (MACARF) in Northern Sydney Area Hospitals between 1998 and 2015 were randomly divided into derivation and validation cohorts to create and test a risk model for predictors of ≥2 readmissions or death within 1 year of initial hospitalisation for HF. Results: Multivariate predictors of frequent (≥2) readmissions or death were a history of ischaemic heart disease and chronic kidney disease, being unmarried, having anaemia, low serum albumin, elevated creatinine, prolonged hospital stay (>7 days), and not receiving beta blockers on discharge. Event rates increased with a higher risk score (p < 0.001) and the prediction was similar in the validation and derivation cohorts (p = 0.588). The C-statistic was 0.65. Conclusions: Our risk score may assist in focussing health care resources and interventions by identifying the subset of HF patients at increased risk for a disproportionately high burden of disease.	en_US
dc.relation.ispartof	Heart Lung and Circulation	en_US
dc.relation.isbasedon	10.1016/j.hlc.2017.10.024	en_US
dc.subject.classification	Cardiovascular System & Hematology	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Length of Stay	en_US
dc.subject.mesh	Patient Readmission	en_US
dc.subject.mesh	Risk Assessment	en_US
dc.subject.mesh	Risk Factors	en_US
dc.subject.mesh	Retrospective Studies	en_US
dc.subject.mesh	Follow-Up Studies	en_US
dc.subject.mesh	Aged, 80 and over	en_US
dc.subject.mesh	New South Wales	en_US
dc.subject.mesh	Female	en_US
dc.subject.mesh	Male	en_US
dc.subject.mesh	Heart Failure	en_US
dc.title	Predictors of Frequent Readmissions in Patients With Heart Failure	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	28	en_US
utslib.for	1102 Cardiorespiratory Medicine and Haematology	en_US
utslib.for	1117 Public Health and Health Services	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Health
utslib.copyright.status	closed_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	28	en_US

Abstract:

© 2017 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ) Background: Patients with heart failure (HF) have a high incidence of hospital readmissions. However risk models that explore predictors of a single readmission may be less useful at identifying the patients with frequent readmissions who contribute to a disproportionately large proportion of morbidity and health care costs. Methods: A total of 6252 patients enrolled in the Management of Cardiac Failure Program (MACARF) in Northern Sydney Area Hospitals between 1998 and 2015 were randomly divided into derivation and validation cohorts to create and test a risk model for predictors of ≥2 readmissions or death within 1 year of initial hospitalisation for HF. Results: Multivariate predictors of frequent (≥2) readmissions or death were a history of ischaemic heart disease and chronic kidney disease, being unmarried, having anaemia, low serum albumin, elevated creatinine, prolonged hospital stay (>7 days), and not receiving beta blockers on discharge. Event rates increased with a higher risk score (p < 0.001) and the prediction was similar in the validation and derivation cohorts (p = 0.588). The C-statistic was 0.65. Conclusions: Our risk score may assist in focussing health care resources and interventions by identifying the subset of HF patients at increased risk for a disproportionately high burden of disease.

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http://hdl.handle.net/10453/129587