An assessment of race and gender-based biases among readmission predicting tools (HOSPITAL, LACE, and RAHF) in heart failure population-Reference-Cited by-同舟云学术

An assessment of race and gender-based biases among readmission predicting tools (HOSPITAL, LACE, and RAHF) in heart failure population

Published:2021-03-12 Issue:1 Volume:191 Page:205-211
ISSN:0021-1265
Container-title:Irish Journal of Medical Science (1971 -)
language:en
Short-container-title:Ir J Med Sci

Author:

Regmi Manjari Rani^ORCID,Parajuli Priyanka,Tandan Nitin,Bhattarai Mukul,Maini Ruby,Garcia Odalys Estefania Lara,Bakare Maryam,Kulkarni Abhishek,Robinson Robert

Publisher

Springer Science and Business Media LLC

Subject

General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s11845-021-02519-0.pdf

Reference14 articles.

1. Fernandez-Gasso L, Hernando-Arizaleta L, Palomar-Rodríguez JA et al (2017) Trends, causes and timing of 30-day readmissions after hospitalization for heart failure: 11-year population-based analysis with linked data. Int J Cardiol 248:246–251

2. Auerbach AD, Kripalani S, Vasilevskis EE et al (2016) Preventability and causes of readmissions in a national cohort of general medicine patients. JAMA internal medicine 176(4):484–493

3. Park, Christopher et al. (2019) Impact on readmission reduction among heart failure patients using digital health monitoring: feasibility and adoptability study. JMIR medical informatics 7.4: e13353.

4. Donzé, Jacques D et al. (2016) cs. JAMA internal medicine 176.4: 496–502.

5. Van Walraven, Carl, et al. (2010) Derivation and validation of an index to predict early death or unplanned readmission after discharge from hospital to the community. Cmaj 182.6: 551–557.

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