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Biomedical, Socioeconomic and Demographic Predictors of Heart Failure Readmissions: A Systematic Review
Eun Sun Choi1, Taneal Wiseman1, Vasiliki Betihavas2
1University of Sydney, Faculty of Medicine & Health, Sydney, NSW, Australia.
Insights
Unemployment and Indigenous status predict heart failure readmissions. Biomedical factors like New York Heart Association class, heart rate, and brain natriuretic peptide levels also indicate risk. Integrating these factors improves patient targeting for reduced readmissions.
Area of Science:
- Cardiology
- Public Health
- Health Services Research
Background:
- Heart failure (HF) is a major cause of hospital readmissions.
- Identifying predictors of HF readmissions is crucial for effective patient management and resource allocation.
Purpose of the Study:
- To systematically review and identify biomedical, socioeconomic, and demographic predictors of heart failure (HF) related readmissions in adult patients.
Main Methods:
- A systematic review of publications from 2015-2020 was conducted in March 2020.
- Databases searched included EMBASE, CINAHL, and Medline.
- Articles were reviewed according to PRISMA guidelines.
Main Results:
- Eighteen studies were included, identifying unemployment as a significant socioeconomic predictor (HR=1.09).
- Indigenous status was a risk factor in one study.
- Biomedical predictors included New York Heart Association (NYHA) class, brain natriuretic peptide (BNP) levels, and heart rate.
Conclusions:
- Unemployment, Indigenous status, NYHA class, heart rate, and BNP levels are key predictors of HF readmissions.
- Incorporating demographic and socioeconomic variables into risk models can enhance patient targeting for readmission prevention.
Aims:
To identify the biomedical, socioeconomic and demographic predictors of heart failure (HF) related readmissions in adult patients with HF.
Methods:
This systematic review was conducted in March 2020 using the databases EMBASE, CINAHL and Medline to identify publications between 2015-2020. The resulting articles were systematically reviewed according to the PRISMA guidelines.
Results:
Eighteen (18) studies were included in this review. Unemployment (HR=1.09; 95%CI=1.05-1.14; p=0.03) was the only socioeconomic factor predictive of HF-readmissions. Socio-Economic Indexes for Areas (SEIFA) scores did not predict HF readmissions in adults with HF (p>0.05). All patients included in the studies had pre-existing HF. Based on the included studies, Indigenous status was identified as a risk factor for HF readmissions in 1 study (p<0.05), and age or sex did not affect HF readmission patterns (p>0.05). New York Heart Association (NYHA) class, brain natriuretic peptide (BNP) levels, and heart rate were also predictive of HF readmission (p<0.05). Left ventricular ejection fraction and blood pressure, however, were non-significant risk factors of HF readmissions (p>0.05).
Conclusions:
This review identified unemployment, Indigenous status, NYHA class, heart rate, and BNP levels to predict HF related readmissions in adult patients with HF. Adding demographic and socioeconomic variables to readmission risk models has the potential to more accurately target patients at risk of readmissions.
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