The Quality Chasm Between Administrative Coding and Accurate Phenotyping of Heart Failure

Affiliations

¹ From the Section of Cardiovascular Medicine, New Haven, Connecticut.
² From the Section of Cardiovascular Medicine, New Haven, Connecticut; Center for Outcomes Research and Evaluation (CORE) at Yale University School of Medicine, New Haven, Connecticut.
³ From the Section of Cardiovascular Medicine, New Haven, Connecticut; Center for Outcomes Research and Evaluation (CORE) at Yale University School of Medicine, New Haven, Connecticut. Electronic address: nihar.desai@yale.edu.

Editorial

Sumeet Pawar et al. J Card Fail. 2019 Jun.

. 2019 Jun;25(6):490-492.

doi: 10.1016/j.cardfail.2019.04.010. Epub 2019 Apr 19.

¹ From the Section of Cardiovascular Medicine, New Haven, Connecticut.
² From the Section of Cardiovascular Medicine, New Haven, Connecticut; Center for Outcomes Research and Evaluation (CORE) at Yale University School of Medicine, New Haven, Connecticut.
³ From the Section of Cardiovascular Medicine, New Haven, Connecticut; Center for Outcomes Research and Evaluation (CORE) at Yale University School of Medicine, New Haven, Connecticut. Electronic address: nihar.desai@yale.edu.

No abstract available

Comment on

Accuracy of Administrative Coding to Identify Reduced and Preserved Left Ventricular Ejection Fraction.
Heidenreich PA, Natarajan S, Bahrami H. Heidenreich PA, et al. J Card Fail. 2019 Jun;25(6):486-489. doi: 10.1016/j.cardfail.2019.01.019. Epub 2019 Feb 10. J Card Fail. 2019. PMID: 30743043

Statistical methods versus machine learning techniques for donor-recipient matching in liver transplantation.
Guijo-Rubio D, Briceño J, Gutiérrez PA, Ayllón MD, Ciria R, Hervás-Martínez C. Guijo-Rubio D, et al. PLoS One. 2021 May 21;16(5):e0252068. doi: 10.1371/journal.pone.0252068. eCollection 2021. PLoS One. 2021. PMID: 34019601 Free PMC article.